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How We Replaced Our Entire Search Engine (with an AI writing half the code)

from Founder's blog [alt+shift+b] in programming

I've been dunking on AI pretty consistently on this blog. Not to mention I'm sick of all the AI influencer "built 15 apps in a weekend" crowd, but Claude Code just did something wild for me. Had it help us rip out our entire search engine - we're talking millions and millions of records, thousands of tenants - and migrate it from SQL Server full-text search to a small embedded, in-process Lucene port. Search went from 7-8 seconds down to milliseconds. Why now? For context - we relied on SQL Server full-text search for years and it was... mostly fine. The way a gas station sandwich is "mostly fine" when you're starving. It worked, nobody died, we had bigger problems to deal with. But when your customers are searching across millions of records and staring at a loading spinner for 7-8 seconds - "mostly fine" stops cutting it. I've been trying to approach this project for years and kept chickening out. Not because the search rewrite itself is hard - swapping a search provider is a weekend, maybe two. The thing that kept scaring me off was all the infrastructure around it. Dozens of one-off CLI tools for index rebuilding, compaction, deduplication, gradual rollout, health checks, verification scripts, progress reporting. Plus all the prep work - tech stack evaluation, risk analysis, benchmarking candidate libraries, planning a migration path that doesn't nuke search for thousands of paying customers at once. The kind of work that makes you reconsider your career choices. And this is exactly where AI came in. Not for the search code itself - I wrote that (well, most of it) in an hour. But for churning out dozens of self-contained CLI tools and scripts. Each one is a small, well-defined, green-field task. Clear inputs, clear outputs, no tangled legacy context to lose track of. If you read my jQuery rant - this was the exact opposite. That was brownfield hell, context rot after three files. This was "here's a spec, write me a tool," over and over, and...
23rd Dec 2025

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Setting up a helpdesk team

Here's a situation we hear about from customers all the time. Someone gets hired as an IT support manager. They inherit two techs, a shared inbox (or a ticketing system nobody likes), and a mandate that sounds something like "build us a proper tiered support team." They have six months to show it's working. It's tempting to start shopping for software. But first you need to find out why everyone hates the current setup. A new ticketing system won't help much if the real problem is that nobody knows who's supposed to approve a laptop. Week one: listen more than you change The worst thing a new manager can do is walk in with a 40-slide transformation plan. Nobody has asked for it yet, and you don't know enough to write it. Instead, talk to as many people as you can, and not only in IT. Department heads, the finance team, sales, and especially the executive assistants. Assistants see every IT failure that annoys their boss, and they will tell you exactly what's broken. Ask what people like about how IT works today and what drives them crazy. You'll get a clear priority list surprisingly fast. Then sit down with your own techs. Ask what wastes their time, what they keep fixing over and over, what they'd change if they could. Pick something you can fix for them. Maybe they're chasing the same approval every week, or sharing one spare laptop between three offices. Sort that out before giving them another process to follow. A few more things to do early: Read the old tickets. If there's any history at all (even an email folder) go through a few months of it with the team. Look for repeat issues, common categories and the stuff that takes forever. This is your first real data. Get the brief from your boss in writing. What does "success" look like in six months? What's the budget? What level of maturity are they actually expecting? "A tiered support team" means something very different at 80 employees and at 2,000. Don't make drastic changes without backing. Changing how people ask for help affects the whole company. If leadership hasn't agreed to it, the first person who complains loudly enough will undo it. Record your starting point Before you change anything, save a few numbers. You'll want them when your boss asks what the last six months achieved: how many requests come in per week, through which channels, how long they take to get a first response, how long until they're resolved, and how many get reopened. The numbers will be rough. That's fine. Six months from now, when someone asks whether the new helpdesk made any difference, you want to answer with "first response went from two days to three hours" rather than "it feels better." The metrics that matter for a helpdesk are well known, so you don't need to invent your own. Agree on what the team supports A ticket can sit untouched because everyone assumes another team owns it. Work out where your team's responsibility starts and ends, including the awkward bits: What do we support, what don't we support, and if we don't, who does? When do we support it? Business hours only? Weekends? Is there an on-call rotation, and who pays for it? What's the difference between an incident (something is broken) and a request (I need something new)? They should be handled differently. Who approves things like software purchases, new accounts or access to sensitive systems? Who orders replacement hardware? Is there an asset inventory, and is it up to date? Is anything monitored, or do we find out about outages when users call? Who owns endpoint security, password management and change management? Write down the gaps too, and take them to whoever can make the decision. "We'll work out who's on call when something breaks" is a miserable arrangement for the person whose phone rings. Pick a ticketing tool. Don't build one You need a ticketing system, but you don't need the perfect one. Almost any modern helpdesk will handle what a team of three needs: tickets, email intake, a portal, a knowledge base, basic automation and reports. Pick something within budget that your team can set up in days, not months, and start using it. Resist the temptation to build something custom or to spend a quarter on a giant ITSM rollout. A team of two doesn't need it, and the time you spend configuring is time you're not fixing anything. (Obviously we'd suggest Jitbit Helpdesk, but the advice holds for any tool.) When you set up the portal, keep this in mind: make it simple for the people asking for help, not for the people answering. Your users don't know how IT works. If someone can't log in, they have no idea whether it's the VPN, their password, an expired license or a permission problem. Asking them to pick from 30 categories and route their own ticket to the "Identity & Access" queue guarantees misrouted tickets and annoyed users. Plenty of helpdesks are designed by helpdesk staff for their own convenience, and to the end user they feel almost hostile. Start with one big button: "I need IT help." Let your tier 1 tech read the ticket and decide where it goes. Once you see which requests come in again and again, add a few specific forms for them (new starter, access request, hardware order) and grow it into a proper category structure from real data rather than guesswork. One front door, and stick to it Once the system is live, every request goes through it. Not a DM to your favourite tech, not a hallway conversation, not a "quick question" in the team chat. Otherwise, a tech can spend all afternoon helping people and look idle in your reports. And when they're off sick, nobody knows what they were working on. This will be unpopular for a few weeks, so be consistent but not rude about it. When someone pings a tech directly, the tech logs the ticket on their behalf and replies with the ticket number. After a while people figure out that filing a ticket is faster. It helps a lot if the tool meets people where they already are, for example by letting them open tickets from Microsoft Teams or by email. The same goes for ticket quality. You're allowed to teach users how to ask for help. A ticket that says "the report doesn't work" should get a polite reply asking which report, what parameters, and what the error said. Better still, put those questions on the form with a ticket template. Templates also make patterns much easier to spot, because the same fields get filled in every time. Documentation: make it easy, not perfect If writing up a five-minute fix takes twenty minutes, the docs will always be out of date. Keep the routine notes quick to write. An informal internal knowledge base, owned by the techs. Every time someone solves something non-obvious, they write a quick entry: what the symptoms were, what the actual cause turned out to be, and how they fixed it. Three paragraphs, no formatting rules. If someone hits the same issue again, they add a short note ("seen again on March 4, this time it was the dock firmware"). Let everyone edit everything, keep backups, and stay out of the way. If every troubleshooting note needs your approval, you've given yourself another queue to clear and your techs another reason to put it off. SOPs for the processes that matter. Onboarding a new employee, offboarding someone, handling a lost laptop, escalating a security incident. Write these together with your techs, not for them. You'll get pushback, and the trick is to sit with them and draft the complex ones as a pair. Ask about the steps they usually leave out because "everyone knows that bit." Those are often the ones a new hire gets stuck on. AI can help turn rough notes into a procedure, but the tech still needs to check it before anyone follows it. Keep the docs near the tickets. Documentation spread across file shares, wikis and someone's OneNote is documentation nobody finds. If your helpdesk has a built-in knowledge base, use it, and link articles from the relevant categories and canned responses. A new tech should be able to find the fix without having to know who wrote it. Ticket history also helps when someone says "IT never told us." It's useful to be able to pull up the actual conversation instead of arguing from memory. ITIL: borrow, don't adopt You'll hear a lot of advice to get certified in ITIL and build everything around it. The concepts are valuable: the incident vs request split, problem management (fixing the root cause, not just the symptom), change management, a service catalog. Learn them. (We wrote a short explainer on ITIL vs ITSM if you need a refresher.) But for a team of three supporting a mid-sized company, a full ITIL implementation is mostly paperwork. Take the parts that solve problems you actually have and skip the rest. You can always add more formality as the team grows. Removing it later is much harder. Automate the repetitive stuff Once tickets are flowing through one system, you'll see exactly where the time goes. A few areas are almost always worth automating early: Joiners, movers and leavers. If your HR system talks to your identity provider, most of the employee lifecycle can run automatically. Account creation, group membership, license assignment and, more importantly, account removal when someone leaves. SaaS provisioning. If your apps support SSO and SCIM, user provisioning and deprovisioning can happen without a ticket at all. Software installs. Most MDM tools let you publish a self-service catalog. Approved software shouldn't need a tech. Password resets. Self-service password reset removes a whole category of tickets overnight. Distribution lists and shared mailboxes. A few simple scripts handle most of these. Triage inside the helpdesk. Auto-assign by category, auto-reply with relevant KB articles, escalate tickets that sit too long, close stale ones. See our list of helpdesk automation ideas for more. Keep track of what these changes save you. When you ask for another hire, it helps to show which repetitive jobs you've already automated and what's still taking up the team's time. Set SLAs and show your numbers Once you have a few weeks of real data, define response and resolution targets and present them to business stakeholders. Be specific about what you can promise. "We'll respond within 30 minutes during business hours" tells people something useful. Promising to resolve every critical incident in four hours is harder to defend when you're waiting on a vendor. Our guide to SLA management covers how to set realistic ones, and ticket priority levels are the other half of the same conversation. Ask your users how it's going, too. Your resolution times can improve while people are still frustrated because they never get an update. Share what you heard and what you're changing. "You told us password resets were painful, so we added self-service reset" earns more goodwill than any satisfaction score. Growing into tiers You don't need tiers on day one. With three people, everybody does everything, and that's fine. Tiers start to make sense when the ticket data shows a clear split between quick, repeatable requests and long, specialist investigations, and when the specialists keep getting interrupted by the quick stuff. A typical progression looks like this: Everyone handles everything, but you track which tickets take minutes and which take days. A dedicated first-line person handles intake, routing and the quick fixes, using the knowledge base the team has been building. Everyone else gets fewer interruptions. Formal tier 1 and tier 2, with written escalation rules: what tier 1 must try before escalating, what information they attach, and how quickly tier 2 responds. Specialist queues (infrastructure, applications, security) once the volume justifies it. For a sense of how many people you'll need at each stage, see how big should your IT helpdesk team be. When you hire, hire for character first. You can teach someone Active Directory. Teaching patience, curiosity and the ability to stay calm with an angry user is much harder. We've written more about the skills good helpdesk staff need. Look after the team you have If a tech tells you they're falling behind, look at the queue with them. Work out what can wait, what someone else can take, and whether you need to tell users there's a delay. If admitting they're stuck earns them a lecture, next time you'll find out from an angry user instead. Give the team time to fix the things that keep slowing them down. That might mean leaving a few non-urgent tickets until tomorrow while someone sorts out the deployment script they've been fighting all month. A rough six-month plan These will overlap. Start writing down fixes as soon as you have somewhere to put them, and agree on urgent-ticket expectations early. The months below give you an order to work through, not deadlines to impose on a team you just met. Month 1: talk to everyone, read old tickets, record baseline numbers, fix one quick pain point for your techs, agree on goals and budget with leadership. Month 2: write down your scope, pick a ticketing tool, launch a simple portal with one "get help" button, enforce one front door. Month 3: review the notes you've collected, document the key SOPs with your techs, add the first request forms based on real ticket data. Month 4: automate the obvious things: onboarding and offboarding, password resets, software installs, ticket routing. Month 5: check whether you're meeting your response targets, ask users what's still frustrating them, and pick something to fix. Month 6: compare against your baseline, present the results, and use the data to make the case for the next hire or the first tier split. Six months in, you should be able to show what comes in, who's handling it, and where the team still needs help. You may still have two techs. At least you'll have something better than "we're busy" when you ask for a third.

16th Jul 2026 • 1 votes
Best AI helpdesk solutions in 2026

Every helpdesk vendor now sells "AI". What they actually ship differs a lot. Some offer a chatbot that answers customers before a ticket exists. Some offer a copilot that drafts replies for agents. Others hand you a platform and a consultant's invoice. The pricing models differ too: per seat, per conversation, per "resolution", or a pool of credits that nobody on the buying committee fully understands. We looked at six options, from a free do-it-yourself build to a full enterprise ITSM suite. Each one gets the same treatment: what it does well, where it falls short, and what it costs as of September 2026. Disclosure: this review is published on Jitbit's blog, and Jitbit is one of the products below. We tried to hold it to the same standard as the others, and we list its weaknesses too. Competitor prices come from public pricing pages and recent third-party breakdowns. Vendors change prices often, so check before you sign. How we evaluated Grounding. Does the AI answer from your documentation and ticket history, or from general model knowledge? Coverage. Does it deflect tickets (customer-facing), help agents (agent-facing), or both? Cost predictability. Can you forecast next quarter's bill without a spreadsheet model? Time to value. Days, weeks, or a multi-month implementation project? 1. Homegrown & Free: a Copilot Studio agent grounded on SharePoint Best for: internal IT support in organizations that already run on Microsoft 365. This option gets overlooked because nobody sells it. If your company already lives in Microsoft 365, you can build a decent self-service IT assistant in an afternoon without buying a helpdesk. The recipe is simple: put your end-user documentation on one SharePoint site, point a Copilot Studio agent at it, and publish the agent to Teams, where your employees already spend the day. Here is how to do it well. How to set it up Create a dedicated SharePoint communication site, for example "IT Help". Keep the knowledge the agent will use on this one site, not scattered across team sites. A single, clean source gives better answers than a large, messy one. Write one page per problem. "Reset your VPN token", "Printer on floor 3 shows offline", "Request a new laptop". Use the error message or symptom a user would type as the page title, and put the fix in numbered steps. Retrieval works on chunks of text, so short focused pages beat a 60-page PDF manual. Avoid scanned PDFs and screenshots-only pages, because the agent cannot read text inside images reliably. Check permissions. The agent answers using the identity of the person asking, so it only sees what that person can see in SharePoint. Give all employees read access to the site. Keep admin-only runbooks on a separate site so they never leak into employee answers. Create the agent in Copilot Studio (copilotstudio.microsoft.com). Add the SharePoint site URL as a knowledge source, and keep authentication set to "Authenticate with Microsoft", which SharePoint knowledge requires. Turn off general knowledge. In the agent's generative AI settings, disable the option that lets the model answer from its own general knowledge. You want "I don't know" rather than a confident, invented fix for your internal VPN. Write short instructions. For example: "You are the IT help assistant for Contoso employees. Answer only from the IT Help site. Give numbered steps. If the answer is not in the documentation, say so and link to the ticket form." Add an escalation path. Change the fallback topic so unanswered questions end with a link to your ticket form or IT mailbox. More advanced teams add an agent flow that opens a ticket directly, but each tool call uses extra credits. Publish to Teams and Microsoft 365 Copilot, then pin the agent in Teams for all employees through the Teams admin center. If people have to look for the agent, adoption stays low. Review analytics every week. Copilot Studio shows which questions went unanswered. Each one is a missing SharePoint page. Write it, and the agent improves by the next morning. This loop matters more than anything else on this list. Pros. There is no new vendor, no procurement cycle, and no new login. Employees ask questions in Teams, where they already are. Identity, permissions and compliance come from your existing Microsoft tenant, so security review is short. The knowledge base is ordinary SharePoint pages that anyone in IT can edit, with no proprietary format to migrate later. For the large share of internal tickets that are really "how do I..." questions (password resets, VPN, printers, Wi-Fi, software requests), a well-written site plus a grounded agent can deflect a meaningful share of volume in the first month. Cons. This is a self-service answer engine, not a helpdesk. There is no ticket queue, no SLA tracking, no assignment, no reporting on agent workload, and no audit trail of who fixed what. When the bot can't help, the issue goes to email or a form, and you still need something to manage it. Answer quality depends entirely on the documentation. A thin or outdated SharePoint site produces thin or outdated answers. Copilot Studio's credit-based licensing is also hard to forecast, and agents can be disabled automatically once a tenant goes 25% over its prepaid capacity. It works for employees only. Do not try to turn it into a customer-facing support bot. Price. Effectively free if your users already have Microsoft 365 Copilot licenses. Microsoft does not charge credits when licensed users talk to employee-facing agents, within fair-use limits. Without those licenses, Copilot Studio bills in credits: $200 per month for a pack of 25,000, or $0.01 per credit pay-as-you-go through Azure. A generative answer grounded on a knowledge source costs 2 credits. With the optional tenant-graph grounding it costs 12. In practice, that is roughly two to twelve cents per answer, and a few hundred dollars a month covers a mid-sized company's internal IT questions. The real cost is the staff time to write and maintain the SharePoint pages. You would need that documentation with any tool on this list anyway. 2. Jitbit Helpdesk Best for: mid-sized support and IT teams that want a full ticketing system with AI included, not billed separately. Pros. AI is built into the ticketing workflow, not added as a separate product. An AI assistant panel in every ticket drafts replies grounded on your knowledge base, indexed external documentation, canned responses, and similar closed tickets. It also summarizes long threads, cleans up agent drafts, and turns solved tickets into new KB articles, which helps teams that are just starting a knowledge base. Automation rules can run AI triage on every incoming ticket (sentiment, category and priority in one pass) and can post first-line AI replies either directly to the customer or as internal notes for review. The live chat widget has an AI auto-responder that hands off to a human when the visitor asks for one. For technical teams, the AI can call your own HTTP endpoints or MCP servers, so it can look up an order status or a subscription without an agent. Model choice is unusually open: GPT and Gemini are included, or you can bring your own key for Claude, Azure OpenAI or AWS Bedrock. That matters for data-residency and HIPAA reviews, and Jitbit signs a BAA on its Enterprise plan. It is also one of the few products here that still offers a self-hosted, on-premise edition with the same AI features. Cons. Jitbit is a smaller vendor, and its integration marketplace is much smaller than Freshdesk's or ServiceNow's. Its customer-facing bot is a helpful extra on top of a helpdesk, not a dedicated conversational platform. Teams with very high chat volume in B2C, which is Fin's specialty, will find fewer controls for multi-step procedures and channel orchestration. Like every grounded AI, it only performs as well as the knowledge base behind it. On-premise customers who want semantic search and document indexing must run an extra Docker-based add-on, and they supply their own model API keys. The entry-level Freelancer plan does not include AI credits. Price. Flat plans with no per-resolution or per-session fees: Freelancer $29/month (1 agent), Startup $69/month (4 agents), Company $129/month (7 agents), Enterprise $249/month (9 agents, $29 per extra agent). Annual billing saves about two months. Unlimited AI credits are included from the Startup plan up. For a seven-agent team, that works out to about $18 per agent per month with AI included. On most of the other paid products here, AI alone costs more than that per agent. 3. Fin (by Intercom) Best for: high-volume customer-facing support where deflection rate is the main metric. Pros. Fin is arguably the most capable customer-facing AI agent on the market, and it is the product the rest of the category measures itself against. It handles multi-turn conversations well, follows written "procedures" for multi-step tasks such as refunds or account changes, and works across chat, email, and voice. Importantly, Fin does not require Intercom's helpdesk. It can run on top of Zendesk, Salesforce, Freshdesk, Front, and others, so you can add it to an existing stack without migrating. Its reporting is built around resolution rate, which makes the ROI case easy to present to a CFO. Cons. Outcome-based pricing is fair in theory and hard to budget in practice. Fin counts an "assumed resolution" when a customer simply stops replying after its last answer. That includes customers who gave up. Your bill grows with volume, not with headcount, so a seasonal spike or a product incident that floods support also increases your AI spend. Fin is built for customer-facing deflection. Agent-side features are stronger inside Intercom's own inbox, so standalone deployments on other helpdesks get less of the product. For internal IT support, it is the wrong tool. Price. $0.99 per billable outcome (a resolution, a procedure handoff or a disqualification), and $9.99 per qualified sales lead. Running standalone on another helpdesk has a minimum of 50 outcomes a month. Inside Intercom, you also pay for seats: Essential $29, Advanced $85, or Expert $132 per seat per month on annual billing. A ten-seat Advanced team resolving 2,000 conversations a month pays roughly $2,800, and about 70% of that is Fin. 4. Tidio (with Lyro AI) Best for: small e-commerce stores that mainly need a website chatbot. Pros. Tidio is one of the fastest ways to get an AI chatbot onto a website. Lyro, its AI agent, learns from your FAQ and site content in minutes, and setup takes almost no technical skill. It integrates well with Shopify, WordPress, and the common e-commerce stack, so it can answer order and shipping questions that make up most of a small shop's inbox. The visual Flows builder handles cart-abandonment nudges and lead capture alongside support. For a one- or two-person store, the free tier is enough to try it before paying. Cons. Tidio is chat-first, and the ticketing side is basic. There is little in the way of SLAs, complex routing, asset management, or the reporting a growing support or IT team eventually needs. Lyro is billed by conversation, and the free and Starter plans include only 50 Lyro conversations in total, not per month. After that, it stops answering. The plan structure has a big gap: the jump from Growth to Plus is more than tenfold, with no middle tier. Teams often report that real costs run two to three times the advertised price once AI and Flows add-ons are included. It is not designed for B2B, internal IT, or regulated industries. Price. Starter $29/month, Growth from $59/month (scaling to about $349 depending on volume), Plus $749/month, and Premium from $2,999/month. Lyro AI is a separate add-on starting at $39/month, and Flows costs another $29/month. A typical Growth setup with Lyro and Flows costs around $127/month before overages. Annual billing saves about 17%. 5. Freshdesk (with Freddy AI) Best for: mid-market customer support teams that want a mainstream, feature-complete suite and can live with add-on pricing. Pros. Freshdesk is a mature, full-featured helpdesk with omnichannel support, a large app marketplace, solid automation, and a familiar interface that new agents learn quickly. Freddy AI covers both sides of the job. The Freddy AI Agent deflects questions on chat, email and the web widget. Freddy Copilot helps human agents with reply drafts, summaries, tone adjustment and suggested solutions. Freshworks also sells Freshservice for internal IT, so organizations can standardize on one vendor for both customer and employee support. Cons. AI costs are split across several meters and plan requirements. Copilot is available only on Pro and Enterprise, so Growth customers cannot buy it at any price. The customer-facing AI Agent is billed by session, and unused sessions expire at the end of each billing cycle instead of rolling over. Freshworks raised plan prices in 2026 for the first time in five years and cut the free plan to a six-month program for one or two agents. Model choice and on-premise deployment are not available. Price. Growth $19, Pro $55, Enterprise $89 per agent per month (annual billing). Freddy Copilot adds $29 per agent per month ($35 on monthly billing). The AI Agent includes 500 sessions, then costs $49 per 100 sessions. The realistic entry point for agent-side AI is $84 per agent per month (Pro plus Copilot). A five-agent team on Pro with Copilot and moderate bot usage spends roughly $650-700 a month. 6. ServiceNow (with Now Assist) Best for: large enterprises running IT, HR and facilities service management on one platform. Pros. ServiceNow is the default choice for enterprise ITSM, and its AI benefits from being close to all of that data. Now Assist summarizes incidents, drafts resolution notes, generates KB articles from resolved cases, and powers a Virtual Agent that can complete requests end to end instead of just answering questions. Because it sits on the same platform as the CMDB, change management, and HR and facilities workflows, the AI can act on real records: reset an account, provision software, or open a change request. No other product here offers that level of process depth, governance, and audit trail. In 2026 ServiceNow moved to AI-native tiers, so AI is now included by default rather than sold as a separate SKU. Cons. Cost and complexity. Implementations usually take months and a certified partner, and the platform typically needs dedicated administrators after go-live. Pricing is quote-only and heavily negotiated, so two companies of the same size can pay very different amounts. AI usage now draws from consumption-based "Assist" pools, which adds another capacity figure to forecast and renegotiate. For organizations under about a thousand employees, ServiceNow is usually more platform than they need. Price. There is no public price list. In April 2026, ServiceNow replaced its Standard/Pro/Pro Plus/Enterprise tiers with Foundation, Advanced and Prime, and older SKUs reached end of sale in mid-2026. As a reference point, legacy ITSM Pro licenses were widely reported at around $100-135 per fulfiller per month. Adding Now Assist (Pro Plus) raised that by an estimated 50-60%, to roughly $200-215 per fulfiller per month. Minimum seat commitments, platform fees and implementation services often make the first-year total a six-figure amount. Side-by-side Solution Best fit Pricing model AI included? Copilot Studio + SharePoint Internal IT, Microsoft shops Credits, or free with M365 Copilot licenses Yes (it's only AI, no ticketing) Jitbit SMB and mid-market support and IT Flat monthly plans Yes, unlimited from Startup plan Fin High-volume customer support $0.99 per outcome, plus seats in Intercom It is the product Tidio Small e-commerce Plan plus Lyro conversation add-on Add-on from $39/month Freshdesk Mid-market customer support Per agent, plus Copilot seats and bot sessions Add-on, $29/agent plus sessions ServiceNow Large-enterprise ITSM Quote-only, per fulfiller, plus Assist pools Bundled in 2026 tiers The bottom line Start with the question you're really trying to answer. If you want employees to stop emailing IT about VPN passwords and you already pay Microsoft, build the SharePoint and Copilot Studio agent first. It costs almost nothing, and the documentation you write for it will make any helpdesk you buy later work better. If you need an actual ticketing system with AI included and a predictable bill, Jitbit and Freshdesk are the main choices, and they differ mostly in how AI is charged. If deflecting a large volume of customer chats is the whole goal, Fin sets the standard, as long as you are comfortable with a bill that grows with volume. Tidio fits small online stores. ServiceNow fits organizations large enough to need a service-management platform, with a budget to match. Whatever you choose, AI quality comes from your knowledge base, not the model. Every product here gives better answers with better documentation, so start writing it now.

27th Jun 2026 • 1 votes
Jitbit Helpdesk Bot is now in the Microsoft Teams Store

Our new Microsoft Teams app just passed Microsoft's certification and is live in the Teams Store: Jitbit Helpdesk Bot. Search "Jitbit" in the Teams app store and it's right there - no custom app uploads, no admin-center gymnastics. Unlike our old webhook integration (one-way channel notifications, now deprecated), this is a proper two-way bot: End users create tickets in chat - type new and get a real form with category and priority, or turn any Teams message into a ticket from the "..." message menu. my tickets lists your open requests Technician replies come back to Teams - as cards with an inline answer box, so the whole conversation can happen without opening the helpdesk Channels get actionable ticket cards - @mention the bot, type subscribe, and every new ticket shows up with Take it / Reply / Close buttons. Cards update in place when the ticket changes - whether that happens in Teams or in the web app Setup takes about two minutes: install the app, click "Generate pairing command" on the helpdesk admin page, paste the command into a chat with the bot. Users are matched by their Microsoft 365 email automatically. Self-hosted customers run their own private bot, so ticket traffic never touches our servers. The bot is included with all plans. Details and setup steps: the integration page and the documentation.

8th May 2026 • 1 votes
Top 20 Helpdesk Interview Questions (with answers)

Help desk interviews usually test two things at once: whether you understand the technical basics, and whether you can explain those basics to a person who may already be annoyed, confused, or late for a meeting. That combination matters. A support technician who can diagnose a network issue but makes the user feel stupid will struggle. So will a friendly person who guesses randomly at technical problems. The best candidates show both: methodical troubleshooting and calm, useful communication. Below are common help desk and desktop support interview questions, with sample answers you can adapt to your own experience. Technical Help Desk Interview Questions 1. Can you tell me about yourself? Keep the answer focused on the job. Mention your IT training, support experience, certifications, customer service background, and the kind of technical problems you have handled. Avoid turning it into a life story. A good answer gives the interviewer several useful follow-up paths. For example: "I have been building my support skills through Windows troubleshooting, networking fundamentals, and customer-facing work. I enjoy breaking problems down, documenting what I find, and helping users get back to work without making the process more stressful for them." 2. A user says their monitor is not working. What do you check first? Start with the simple physical checks before assuming a complicated failure. Confirm that the monitor has power, the brightness is not turned all the way down, the video cable is connected securely, and the computer itself is powered on. If the monitor has multiple inputs, make sure the correct input is selected. If those checks do not solve it, continue with another cable, another monitor, or another port. From there, you can investigate graphics drivers, docking stations, sleep state problems, or hardware failure. 3. What is Safe Mode used for? Safe Mode starts Windows with a limited set of drivers and services. It is useful when a normal startup fails, when a bad driver causes crashes, or when you need to remove unwanted software that loads during a standard boot. The exact steps depend on the Windows version, but the general idea is to restart into the recovery or advanced startup options and choose Safe Mode or Safe Mode with Networking. 4. What is an IP address? An IP address identifies a device on a network so other devices know where to send traffic. On a typical office network, a computer may receive its IP address automatically from DHCP, although servers, printers, and network equipment often use fixed addresses. On Windows, you can check the assigned address with ipconfig or ipconfig /all in Command Prompt. You can also find it in the network adapter settings. 5. What is a default gateway? A default gateway is the device a computer uses when it needs to reach something outside its local network. In many offices and homes, that gateway is a router or firewall. Without a working gateway, a computer may still talk to nearby devices but fail to reach the internet or other remote networks. 6. What is Active Directory? Active Directory is Microsoft's directory service for managing users, computers, groups, permissions, and policies in a Windows domain environment. In practical help desk work, you may use it to reset passwords, unlock accounts, check group membership, or confirm which computers belong to the domain. 7. What is a windows domain? A domain is a centrally managed group of users, computers, and resources. Instead of each PC having completely separate local accounts and permissions, a domain lets administrators manage access from one place, usually through Active Directory. For help desk work, this matters because a user's ability to sign in, access file shares, use printers, or launch certain applications may depend on their domain account and group memberships. 8. A printer is printing strange symbols or garbled pages. What might cause that? A common cause is the wrong printer driver or a corrupted print job. I would first clear the print queue, confirm the correct printer model and driver, and reinstall or update the driver if needed. I would also check whether other users are affected, because that helps determine whether the issue is local to one workstation or shared across the printer or print server. 9. What are common Ethernet cable categories? Common twisted-pair Ethernet cable categories include Cat5e, Cat6, and Cat6a. Cat5e is widely used for gigabit networking, Cat6 is also common for gigabit and shorter 10 GbE runs, and Cat6a is designed for 10 GbE over longer distances. In an interview, it is usually enough to show that you understand the categories affect supported speed, distance, and installation quality. 10. What is a blue screen? A blue screen, often called a BSOD, is a Windows stop error. It can be caused by failing hardware, bad drivers, memory problems, disk issues, overheating, or low-level software conflicts. A sensible troubleshooting path is to note the stop code, check recent changes, review Event Viewer, update or roll back drivers, run hardware diagnostics, test memory, and look for patterns such as crashes only after docking, printing, or launching a specific application. 11. What does DHCP do? DHCP stands for Dynamic Host Configuration Protocol. It automatically gives network settings to devices, including IP address, subnet mask, default gateway, and DNS servers. Without DHCP, users or administrators would have to configure those values manually on each machine. 12. What does DNS do? DNS translates names people can read into IP addresses computers can use. For example, when someone visits a website, DNS helps find the server behind that domain name. In support work, DNS problems can look like "the internet is down" even when the network connection itself is working. Useful checks include trying another site, using nslookup, checking the DNS server address, and flushing the local DNS cache when appropriate. 13. What is a VPN? A VPN creates an encrypted connection from a user's device to a private network. Remote employees often use VPNs to access internal applications, file shares, intranet sites, or administrative systems that are not exposed to the public internet. When troubleshooting VPN issues, check credentials, MFA prompts, internet connectivity, client version, certificate problems, and whether the user is on a restricted network. 14. What is the ping command used for? ping sends test packets to another host and reports whether replies come back. It is a quick way to check basic reachability and latency. It does not prove that a website, file share, or application is working, but it can help narrow down whether a device can reach another device at all. 15. What is Group Policy? Group Policy is a Windows feature used to apply settings across users and computers in a domain. Administrators can use it to configure password rules, mapped drives, desktop restrictions, security settings, software deployment, browser settings, and many other policies. For a help desk technician, Group Policy is often relevant when a user cannot access a feature that someone else can, or when settings keep changing back after a reboot or login. 16. What is a PST file? A PST file is an Outlook data file, commonly used to store email, calendar items, contacts, and archives locally. In support scenarios, PST files come up during Outlook migrations, archive recovery, mailbox troubleshooting, and storage cleanup. 17. How would you change folder permissions? First, confirm who should have access and whether the folder is local, on a file server, or controlled by a broader policy. On Windows, folder permissions are usually managed from the Security tab in the folder properties, where an administrator can add users or groups and assign permissions such as Read, Modify, or Full Control. In a company environment, it is usually better to grant access through security groups rather than adding individual users one by one. 18. What is the difference between a hub and a switch? A hub sends traffic out to every connected device, whether the traffic is meant for that device or not. A switch is smarter: it learns which devices are connected to which ports and forwards traffic only where it needs to go. That makes switches much more efficient and secure for modern networks. Hubs are mostly obsolete, but interviewers still ask the question because it tests basic networking knowledge. 19. How would you recover files from a virus-infected computer? Do not rush to copy files from an infected machine onto the network. First isolate the computer, document symptoms, and follow company security procedure. If recovery is approved, use a clean, trusted environment and scan the drive with updated security tools before moving any files. Depending on the incident, the correct answer may involve escalating to security, preserving evidence, or restoring from a known-good backup rather than manually extracting files. 20. Why should we hire you? Use this answer to connect your skills to the role. Mention technical fundamentals, reliability, communication, willingness to learn, and any experience that proves you can handle real users under real pressure. A strong answer is specific: "You should hire me because I can troubleshoot methodically, explain technical issues clearly, and stay patient when users are stressed. I also document my work, ask for help before wasting time, and keep learning so I can solve more problems independently." Customer Service Help Desk Interview Questions Technical answers matter, but help desk work is still service work. Interviewers want to know how you behave when the problem is unclear, the user is frustrated, or the ticket queue is already full. 1. What makes someone good at help desk work? A good help desk employee listens carefully, asks clear questions, and explains the next steps without drowning the user in jargon. They also know when to keep troubleshooting and when to escalate. Speed matters, but accuracy, documentation, and the user's experience matter too. 2. What do you do when you cannot solve an issue? I would gather the important details first: what changed, who is affected, what error appears, what has already been tried, and how urgent the issue is. If I still cannot resolve it, I would escalate with clean notes so the next person does not have to start from zero. 3. How do you handle an angry or frustrated user? Stay calm and avoid arguing. Let the user explain the problem, acknowledge the impact, and move the conversation toward the next useful action. A simple sentence like "I can see why that is frustrating; let's check the fastest things first" can lower the temperature without making unrealistic promises. 4. Tell me about a conflict you had and how you resolved it. Choose an example where you stayed professional and solved the actual issue. The best answers are not dramatic. A misunderstanding about priority, a handoff problem, or a disagreement about procedure can work well if you explain what you learned and how you prevented it from happening again. 5. How would you rate your troubleshooting ability? Be confident but realistic. If you are early in your career, a four out of five is often more believable than claiming perfection. Explain that you are strong at structured troubleshooting, documentation, and asking good questions, while still knowing when to escalate unfamiliar problems. 6. How do you keep your IT knowledge current? Mention specific habits: reading vendor documentation, practicing in a lab, following release notes, taking courses, studying for certifications, or learning from tickets after they are resolved. Interviewers like answers that show steady curiosity rather than vague "I read online" statements. 7. Why do you want to work in help desk? A good answer connects problem-solving with service. You might say that you enjoy figuring out technical issues, helping people get unstuck, and learning a wide range of systems. Help desk roles expose you to many parts of IT, which makes them a strong starting point for a support career. 8. How do you stay organized? Talk about your system. For example, you might prioritize tickets by urgency and impact, keep notes inside the ticket, use reminders for follow-ups, and close the loop with users before marking work complete. The point is to show that you do not rely on memory alone. 9. Is teamwork important in help desk? Yes. Support teams depend on clean handoffs, shared knowledge, and good escalation notes. No one knows every system, and many incidents require cooperation between help desk, infrastructure, security, vendors, and department managers. 10. Which ticketing systems have you used? If you have used a ticketing system before, name it and describe what you did with it: creating tickets, assigning priorities, documenting work, escalating issues, using canned responses, or building a small knowledge base. If you have not used one professionally, say so honestly, then explain that you understand the core workflow: capture the request, categorize it, prioritize it, document progress, communicate updates, and close the ticket when the user confirms the issue is resolved. Final Tips Before the Interview Practice explaining technical ideas in plain language. Prepare a few real examples from school, work, home labs, or previous customer service jobs. Do not pretend to know something you do not know. Explain how you would find out. When answering troubleshooting questions, start simple and move step by step. Show that you care about documentation, follow-up, and the user's experience. The strongest help desk candidates do not sound like they memorized a script. They sound like people who can stay calm, think clearly, and keep a user informed while working through the problem.

8th Mar 2026 • 1 votes
AI features now run on-premise

Short version: every AI feature we ship on the hosted helpdesk now runs on the self-hosted edition too. It's a separately licensed Docker add-on, perpetual license, one-time payment. Customer data stays on your network. Requires Jitbit Helpdesk v11.22 or newer. Why this took a while Our AI stack isn't a thin wrapper around an LLM API. It's a Python service running a local vector database (Qdrant), embedding models, and a RAG pipeline tuned against support-desk content. That's what makes "similar KB articles" surface the right article, and what keeps reply drafts grounded in your own documentation instead of hallucinated. Running that stack on our own hosting is one thing. Packaging it so your IT team can stand it up on your own hardware without babysitting Python dependencies is another. We sat on it until we had something we'd be comfortable supporting. What you get Similar-article suggestions inside tickets - ranked by semantic similarity, not keyword overlap Semantic KB search for end-users - results ranked by meaning AI-generated reply drafts grounded in your KB, writing-style rules, and the ticket context External documentation indexing - crawl your own docs, wiki, or any internal site and use it as AI context alongside the KB Choice of embedding model - free local model that runs on CPU, or OpenAI embeddings with your own key Generative provider - OpenAI, Azure OpenAI, or AWS Bedrock, customer brings their own key Feature parity with SaaS. No caveats about "basic" ChatGPT integration. How it ships A Docker Compose stack you drop in next to your existing Helpdesk install. Runs on Windows or Linux, bare metal or VM, Intel/AMD or ARM. Upgrades are zero-downtime and preserve Docker volumes — indexed data and cached models carry over. Full setup and system requirements are in the manual. Privacy This is the reason we finally built this. With the bundled local embedding model, nothing about your tickets, KB articles, or indexed documentation leaves your network. No embeddings sent to OpenAI. No vectors stored in a third-party service. The vector DB is a container on a host you own. If you want a generative model for reply drafts, you bring your own API key. Azure OpenAI and AWS Bedrock keep everything inside your existing cloud tenancy, with a BAA if you need one. For regulated on-prem buyers — healthcare, defense, financial services, government — this was the #1 reason you told us you couldn't adopt our AI features. It's no longer a reason. Pricing Licensed separately from the core Helpdesk product. Perpetual license, one-time payment, 1 year of updates included - same model as the rest of the on-prem lineup. No subscription, no per-agent add-on, no per-request fees. See the pricing page for the current price, and the on-prem AI landing page for the full feature list and requirements. Setup instructions live at jitbit.com/docs/ai-on-premise.

10th Feb 2026 • 1 votes

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The Future of CSS ✨

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2 days ago • 1 votes
Speeding up code review with `small-change`

Imprint’s average engineer is merging 4x more PRs than 2 years ago. Yay. Aggregated behind the average is something even more interesting: we have two teams that are merging 10x their PRs over that period. One engineer is merging 25x the PRs per week of our average engineer two years ago, and a number are merging 10x. That’s pretty neat, and the slope of the line suggests our average in a year is going to look much closer to today’s p90 than today’s p50. Even more importantly, we aren’t just shipping more, our quality has improved: incidents are down 42% half-over-half, and critical incidents are down 78% half-over-half. I think we’ve always known the quality/velocity tradeoff wasn’t a particularly useful construct, but that’s undeniable today. As we’ve walked this path, we–like everyone else progressing down it–have run into the problem of pull request review. The p50 pull request review took about 33 minutes to complete 2 years ago, but now takes us about 77 minutes. The slope here correlates tightly with the number of pull requests getting merged. Tightly enough that addressing it became one of my priorities for the week. We solved it! Just kidding, we’ve absolutely not solved it, but I think our current approach is an interesting one, which we call the small-change. The work discussed here was shaped and done by many folks at Imprint including Dan, Joy, Daniel, Lenny, Taylor, Ted, and Annie, among many others. Why review pull requests? There are four reasons we review pull requests: Knowledge sharing between author and reviewer – software engineering is generally learned via apprenticeship, and reviews are a primary mechanism of experienced engineers teaching others what good software looks like. We believe the current volume means that this knowledge sharing will have to move towards operating on clusters of pull requests, rather than individual pull requests Preventing errors – review has always been an expensive time to catch errors, and we believe that effective CICD along with harness verification techniques like poteto’s pstack are more effective mechanisms for preventing errors than review Preventing malicious behavior – my experience is that even careful code review will generally miss competent malicious behavior, although fortunately most malicious behavior is incompetent. We believe both sorts of behavior are best identified using a combination of fixed rules (modifying these specific objects/classes/files requires review), anti-abuse mechanisms that we’ve refined in our LLM-based member support experiences, auditing, and audit log inspection Compliance obligations in our documented controls – these can be changed, but today they require that an independent human reviews changes in a subset of our repositories In the modern development paradigm, we think there is a better solution for each of these problems. But, we also want to make these changes very cautiously. Small steps with small-change We believe we move fast by finding narrow, contained ways to validate new practices, so to iterate our way into an effective solution, we’ve developed the concept of a small-change. Here’s how it works: When a pull request is marked ready, CICD determines whether it is eligible to be a small-change. This is represented as a passing Github check. There is also a label for visibility, but it is the check itself, managed by the build and not human modifiable, that determines eligibility. (The label is used for initial filtering, but the check is still independently verified.) Something is a small-change if it meets all of these criteria: It is less than 1,000 lines of code There are no p1 or p2 findings from our ai-code-review automated review bot The author has “experience” in the service or application, defined as 10+ prior merged pull requests into that service or application’s directories. For changes working across multiple services or applications, the author must have experience in all of them to qualify Impacts fewer than N distinct services or applications. N is 1 on our frontend monorepo, and N is 3 in our backend monorepo, where typical changes will modify both a gRPC service and a common HTTP gateway Shared libraries and utilities files are not eligible for small-change Each repository has a .small_change file which allows per-path customization while we continue to tune the behaviors. For example, a service dealing with money movement can be excluded Our Slack automation tags every reference to a pull request with reacji labeling the state of that pull request, for example if it has failing tests, if it has been approved but tests are still running, or if it is ready to merge. We added a small-change reacji that indicates which of those pull requests meet the small-change criteria In our internal skills repository, we created two skills that have been distributed across harnesses: review-small-change which takes a list of repositories and reviews all open, non-draft, small-changes, including providing approval if they meet the review’s criteria (all checks pass including small-change check, and not touching on sensitive topics such as payments and security) review-pr-cluster which reviews batches of pull requests to identify common themes that came up, and suggest opportunities for discussion and adding verifications We set the social expectation that any error caused by a small-change is a failure in our system, and has to be solved at the system level: improvements to ai-code-review, to our verification mechanisms, to our CICD, to our harness, etc. This took about two days of infrequent attention to implement and rollout, although I imagine we will be tuning the knobs here for a long time. Maybe forever. fleet: centrally orchestrated harness I’ll briefly mention our other approach to reducing code review volume, which anchors on our centrally-orchestrated harness, fleet. (Which is similar to Stripe’s Minions although not following the one-shot approach in particular). We rely on fleet to implement and verify software in a highly controlled harness running in the cloud, with independent evaluation mechanisms to identify the correct number of independent reviewers for any given change. That number can be as low as one (e.g. fleet writes, one human reviews) for changes evaluated as safe. Results / next steps / reception I’ll be honest, it’s too early to give a useful result here. From early results, about 10% of changes qualify as a small-change. Those are now eligible for very fast approval, and generally get it unless they trip a flag, generally due to touching a security or money adjacent topic. While 10% is a small percentage, the core concept here is working, and ultimately will succeed or fail based on our ability to expand that percentage over the next few months in tandem with expanding our verification mechanisms to be increasingly comprehensive. This is ultimately going to fail or succeed depending on our ability to improve our verifications, which does require more difficult sorts of techniques to accomplish in low scale-complexity, high domain-complexity software than in the high scale-complexity, low domain-complexity products where many techniques like incremental rollouts are exceptionally effective. (Don’t get me wrong, they still work, they just provide less coverage when most users have different configuration and behavior.) Folks have not been uniformly excited about this, it’s a substantial change from how we’ve learned to be good engineers, and it’s uncomfortable to reevaluate whether a long-held best practice has become merely dogma. The most energizing part of the current cycle is that we get to reevaluate these practices we grew up on every week; the most painful part of the current cycle is that we’re likely to fall behind if we ever stop reevaluating them.

5 days ago • 1 votes
Building a Chestnut Launcher

The park near my house has lots of chestnuts and my kids have been collecting them like crazy (it’s actually their favorite post-school activity). We accumulated quite a hoard. I thought it would be fun to make a launcher so we had something to do with our new chestnut collection. I wanted to go with a very simple crossbow-style design (like the famous D2 item) using latex tubing and a leather pouch for holding the chestnuts. This is what I came up with. It launches chestnuts about 220 feet, and it’s simple enough to build in an afternoon. The frame is a 42 inch 2x2 and a spare IKEA bed slat for the crossbeam, glued and screwed together. A 3/8 inch eye bolt goes through each end of the crossbeam, and the latex tubing is tied to those and to the pouch from a leather shepherd’s sling. Tying the tubing was the fiddliest part. It has to be stretched while you wrap it with butcher’s twine, so I clamped a couple of scrap blocks to my workbench to hold it. I like this design because the tubing can be wrapped around the eye bolts to easily add more tension and power. The Trigger My favorite part of the design was that I decided to use an archery release like this one for the trigger. It provides a safe and reliable way to hold the tubing back, and it’s made to let go cleanly. I 3D printed a little housing that mounts the release securely to the back of the stock, and the release clips onto a loop of archery D-loop cord on the back of the pouch. Then I added a dowel for a rear grip and an old handle I had previously removed from my shop vac. How Well Does It Work? We tried it at the park and it works surprisingly well. Aimed at about 35 to 40 degrees, it sends our chestnuts (on the small side, about 10 to 15 grams) about 220 feet. Thanks to the archery release, we haven’t had a single misfire. I got curious and did some rough math. To go that far with air drag, the chestnuts are leaving at somewhere around 85 to 100 mph, which works out to about the same energy as a paintball. So safety glasses are important and you never point it at anyone. You can find the 3D print on Printables and a full build guide on Instructables. Make sure to always use it with adult supervision :)

5 days ago • 1 votes
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