Bharat Byte Tech
After the last post, a few people asked what agentic AI actually looks like once you stop talking about it in the abstract. Fair question. Here are four narrow, specific builds we’ve shipped recently under what’s now its own line of work for us - Agentic AI Development - not a hypothetical roadmap slide.
A support ticket triage agent
A retail client had one person spending two hours every morning reading overnight support tickets and routing them to the right team. The agent now reads each ticket, checks it against order and account data, tags it, drafts a first-response for the routine 70%, and routes anything unusual to a human with the relevant context already attached. The person who used to do this now reviews drafts instead of starting from a blank screen.
An invoice processing agent
A manufacturing client was manually keying supplier invoices into their accounting system. The agent reads incoming invoices, matches them against purchase orders, flags anything that doesn’t reconcile, and only pushes the clean ones through automatically. Mismatches stop at a human. It doesn’t touch anything it isn’t confident about, which was the client’s one non-negotiable requirement.
A deployment readiness agent
For a client with a fairly complex release process, we built an agent that runs the pre-release checklist itself - tests pass, migrations are reversible, monitoring is in place, rollback plan exists - and blocks the release with a specific reason if any of it isn’t true. It replaced a manual checklist that occasionally got rushed under deadline pressure. The agent doesn’t get tired at 6pm on a Friday.
A reporting agent
An education client wanted a weekly summary of enrolment, attendance and revenue trends without anyone building it by hand each Monday. The agent pulls from three separate systems, reconciles the numbers, and drafts the summary with the notable changes flagged. A person still reads it and sends it - we didn’t automate the judgment about what’s worth mentioning to leadership, just the two hours of assembly before it.
The pattern across all four
Every one of these started as one specific, currently-manual, currently-annoying task - not a company-wide “AI transformation.” Every one has a hard boundary on what it’s allowed to do without a human. And every one is small enough that if it turned out to be a bad idea, we’d have found out in a week, not a quarter.
If you’ve got a task that looks like one of these sitting on someone’s plate right now, that’s usually where to start - tell us about it.
