Support triage
Reads a new ticket, classifies it and pulls the customer's history. It drafts a reply and hands anything it's unsure about to a person.
AI agent development company in India
AI agents that do multi-step work in your systems — read-only until they earn your trust.
We build agents that read your tickets, records and documents, work through the steps and draft the result. Every agent starts read-only: a person approves each action until the agent's track record earns it wider access. Before launch, our security team checks what each tool can reach, tightens its permissions and sets up logging. When it finds a problem, it checks the fix too.
- Read-only first release
- Every tool call logged
- Agent security review before launch
In brief
- What it is
- Software that works toward a goal on its own. It picks a tool (such as looking up an order), reads the result and decides the next step, until the job is done or it needs a person.
- Why it matters
- A chatbot that's wrong gives a bad answer. An agent that's wrong can issue a refund or email the wrong customer. Its mistakes cost more, so it needs firm limits.
- What you get
- An agent that starts read-only, logs every prompt and tool call, and earns permission to change things (write access) one stage at a time. Our security team reviews it before launch.
Common requests
Agents clients ask us to build.
Most of them read, gather and draft, and leave the decision to a person.
Invoice reconciliation
Matches invoices to purchase orders and delivery notes. It flags each mismatch with the reason and leaves a clear audit trail for finance.
Claims and case prep
Gathers the documents in a case and pulls out the fields that matter. A person reads its summary and makes the decision.
Scheduled research
Checks your sources on a schedule and reports only what changed since its last run.
Internal operations copilots
Answers process questions from your own documentation. It can also take small, bounded actions, such as raising a ticket or booking a slot.
Something else?
If your task isn't listed, describe it. We'll tell you whether an agent fits or a simpler automation would do the job.
What an agent is
An agent picks its own next step.
That's what makes it useful. It's also why most of our engineering goes into its limits.
An AI agent works toward a goal on its own. You give it the goal and a set of tools, such as reading a ticket, looking up an order or searching a policy. It picks a tool, reads what comes back and keeps going until the job is done or it needs a person.
What we set before it runs
- What it may read. Each tool reaches only the systems and data the task needs. This is least privilege: the smallest access that does the job.
- What it may change. Nothing at first. Every change waits for a person until the agent earns the right to make it, and we make actions reversible where we can.
- Where it must stop. A person approves anything consequential, and rate limits cap how often it can act.
- What it leaves behind. A log of every prompt and tool call, so you can see later why it did what it did.
For example, a support agent reads the ticket, looks up the order, checks the refund policy and drafts a reply on its own. The refund itself waits for a person, and the log records who approved it.
Is an agent the right tool?
Not every question needs an agent.
An agent fits when the next step depends on what it finds along the way. If your question is closer to one of these, another page answers it better.
- How much of this process should we automate, and what stays with a person?AI automation
- We need AI inside our ERP or CRM without rebuilding them.AI automation and integration
- We want an assistant that talks to customers without inventing answers.AI chatbot development
- We want AI to draft documents and answers from our own knowledge.Generative AI development
- How do we know our document search finds the right passages?RAG development
- Which model should we use, and does it need our own documents or further training?LLM development
- We want to add a hosted model to software that is already running.AI integration
- We already run an agent. Has anyone checked what its tools can reach?AI security
Not sure which one you need? See everything we build under AI development, or ask an engineer.
How we ship them
An agent earns write access in four stages.
Each stage has a gate. You decide when the agent moves up, after reading what it did at the stage below. Nobody skips a stage to hit a date.
Shadow mode
The agent runs on real work and records what it would do, but executes nothing. For two weeks you compare its decisions with your team's, and find out where it's wrong before anyone is affected.
Draft mode
It drafts each reply, ticket or entry, and a person approves every one. The gate is a number: an approval rate above 85%. If the rate won't climb, we tell you the agent isn't ready, and it stays in draft mode.
Narrow write access
It gets one reversible action, rate-limited and logged. Its other tools stay off. You review that audit trail before it gets a second tool.
Widen slowly
Each new tool is a separate decision. We try it in a sandbox, a test setup cut off from your live systems, before the agent can use it. Each tool also gets a way to undo its actions (a rollback path) and limits on what it can reach.
What you can hold us to
Read-only first, fully logged, reviewed before launch.
A read-only first release
The first release watches and drafts. An agent that acts before you can check its decisions is one you hear about from a customer.
Every prompt and tool call logged
You can reconstruct what the agent did, why it did it and who approved each action.
A security review before launch
Our security team checks each agent for excessive agency (more access than the job needs), runaway loops (repeating steps without stopping) and prompt injection (instructions hidden in text the agent reads), and re-checks every problem once it's fixed. We also limit each tool's reach, so an injection that gets through has little to work with. We run the same agent security reviews on agents other teams have built.
What our testing can't promise. Prompt injection has no complete fix. We test for it and limit what each tool can reach, but we can't rule it out. Our test results hold for the agent as tested, and each tool added later passes its own gate first.
FAQ
Questions about AI agent development.
What agents are, how we build them and how we keep them in bounds. Can't find your question? Ask an engineer.
AI agent development is building software that decides its own next step instead of following a fixed script. You give it a goal and a set of tools. It picks a tool, reads the result and carries on until the job is done or it gets stuck. Most of the engineering is about limits: which tools it can reach, what it may change, and when it must stop and ask a person.
Yes. The agents we're asked for most are support triage, invoice reconciliation, claims preparation, scheduled research and internal operations copilots. Every agent we ship starts read-only, so you can compare its decisions with your team's before it's allowed to act.
A chatbot returns text, so when it's wrong you get a bad answer. An agent takes actions in real systems, so its mistakes cost more. A wrong agent can issue a refund, email the wrong customer or write to a production database. That's why our agents start read-only.
We use LangGraph or LlamaIndex when the control flow is complex enough to need them. When it isn't, a plain state machine does the job, and that happens more often than you might expect. The framework matters much less than how the tools are designed and what each one is allowed to do.
We use several layers: least-privilege tools, reversible actions where possible, rate limits and a person approving anything consequential. We also log every prompt and tool call, so you can reconstruct what happened. Then we test the agent. The most common serious issue we find is an agent that can be steered by a document it retrieves.
Yes. An agent security review covers tool scope, permission boundaries, indirect prompt injection, cross-session influence and blast radius: how far one bad action could spread. It's one of the AI security services we're asked for most.
Let's talk
Have a process an agent could take on?
Tell us the task, the systems it touches and who signs it off today. We'll tell you where an agent could start and what it should leave alone. We reply within one working day.