AI Agents That Do the Work, Not Just Answer Questions
Agents wired into the systems you actually run — IoT platforms, ERPs, WhatsApp, payments, KYC. They take action, escalate what they are unsure about, and log everything they touch.
Where Agents Actually Pay
Most agent ideas should not be built. These four conditions separate the ones that earn their cost from the ones that get switched off in month three.
The task runs hundreds or thousands of times a month — agents are a fixed cost amortised over volume
It spans several systems, so the work is coordination rather than a single lookup
Being occasionally wrong is recoverable, and there is a natural point where a person reviews
Someone owns the outcome and will act when the agent escalates
If an idea fails two of these, we will tell you. More on the reasoning in our honest ROI check.
What We Build
Six kinds of agent, all of them defined by the systems they act on rather than the model behind them.
Operations & Field Agents
An agent watching your machines, fleet or sites — spotting faults, ranking what needs attention, raising the ticket, and telling the right technician. Built on the same IoT platforms we already run.
WhatsApp Support Agents
Handles the repetitive 80% of customer conversations on the channel Indian customers actually use — order status, bookings, refunds, FAQs — and hands the rest to a human with full context.
Back-Office Document Agents
Reads invoices, POs, claims and forms, checks them against your records, and files what is clean while routing the exceptions. Not extraction alone — the decision and the follow-up action.
Lead Qualification Agents
Works inbound enquiries the moment they arrive, asks the qualifying questions, books the call, and writes it into your CRM. Stops good leads going cold overnight.
Integration & Workflow Agents
The glue work: moving data between ERP, payments, KYC and logistics systems, reconciling mismatches, and escalating what does not tally. This is where most real agent value sits.
Internal Knowledge Agents
Answers staff questions from your own documentation, SOPs and past tickets — with citations, so people can check the source rather than trust a confident guess.
How We Build Them Safely
An agent with broad permissions and no oversight is a liability. Four things we insist on.
Scoped permissions, not open-ended access
An agent gets the narrowest set of actions that does the job. Read-only where reading is enough. Anything that moves money, changes a record of consequence, or contacts a customer needs an explicit approval step.
A human on the uncertain cases
Confident work flows through; anything the agent is unsure about goes to a person, with the reasoning attached. The threshold is a dial you can turn as trust builds — not a rewrite.
Every action logged and reversible
What the agent did, why, and on whose behalf — recorded. When something goes wrong you need to answer that in seconds, and be able to undo it.
Measured against the manual baseline
We record how long the task takes and how often it is wrong today, before building. Without that number there is no honest way to say whether the agent helped.
We have written up this pattern in detail in Human-in-the-Loop AI.
Common Questions
Got a Workflow That Eats People's Days?
Describe it and we will tell you honestly whether an agent is the right answer, what it would cost, and where a human still needs to sit in the loop.