Work completed, not answered
The measure is tasks closed end to end. We benchmark against the people doing that job today and publish the gap either way.
AI Core — Where we lead
AI Agent Development
Software that holds context across steps, calls your systems, and finishes the task instead of describing it.
- Single and multi-agent architectures
- Tool-use, function calling and API orchestration
- Memory, retrieval and long-horizon planning
- Evaluation harnesses and guardrails
- Engagement shape
- Fixed-scope proof of value on one workflow, then a production build with your engineers in review.
- Typical duration
- Three to four weeks to proof, six to twelve weeks to production.
- Starting point
- One workflow with measurable volume and a clear definition of a finished task.
Overview
What the work involves.
An agent is not a chat window with a better prompt. It is a service with a goal, a set of typed tools over your systems, a memory of what it has already tried, and a record of every decision it made along the way.
So we build them the way we build any production service. Tool definitions are versioned. Destructive actions sit behind an approval gate. Every run is scored against an evaluation set you own, and a regression blocks a deploy exactly the way a failing test does.
Most of our agents run against a queue rather than in front of a user — clearing invoices, qualifying leads, triaging tickets, drafting replies for a person to sign. The interface, where there is one, comes last.
Outcomes
What you get.
A tool layer you own
Typed, permissioned functions over your CRM, ERP and internal APIs. The next agent reuses them rather than rebuilding them.
An evaluation set that holds
A graded set of real cases, run on every change, so quality moves in one direction and you can watch it move.
Auditable behaviour
Every step, tool call, token and cost logged and replayable, with approval gates on anything touching money or a customer.
Deliverables
What lands in your hands.
- Agent architecture and tool specification
- Typed tool layer over your systems of record
- Memory and retrieval design with retention rules
- Evaluation harness with a graded case set
- Approval gates and rollback paths for destructive actions
- Observability dashboard for cost, latency and success rate
- Runbook and code handover for your engineers
Approach
How we run it.
Define done
We write the acceptance test before the agent. What counts as a finished task, what it may never do alone, which cases must escalate, and what a good week looks like in numbers.
Build the tools first
The tool layer is the hard part. Your systems get wrapped in typed functions with permissions enforced server side, then tested with no model in the loop at all.
Wire the loop
Planner, memory, retrieval and self-critique, using the cheapest model that clears the bar at each step. Runs are logged and replayable from the first day.
Harden and hand over
Failure, load and adversarial testing, then approval gates, spend caps, alerting and a runbook. Your engineers review the code before anything goes live.
Each phase ends with something you can read and act on. If the evidence says stop, stopping there is a supported outcome rather than an awkward conversation.
Stack
What we build it with.
- Anthropic Claude
- OpenAI
- LangGraph
- Model Context Protocol
- Temporal
- PostgreSQL
- Redis
- LangSmith
Tooling is a decision we make per project, against your constraints and whatever your team already runs. Nothing on this list is a requirement, and we will work inside your existing stack where it holds up.
Questions
What clients ask about AI Agent Development.
Three things. Tools are permissioned server side, so it cannot reach what it was never granted. Destructive actions need a human approval. And spend caps end a run before a loop becomes an invoice.
Whichever clears the evaluation set most cheaply, chosen per step. Routing is a configuration value rather than an architecture decision, so changing model is a deploy, not a rebuild.
That is the usual shape. The agent absorbs the routine volume and drafts the rest for a person to approve, so the team spends its day on exceptions and judgement instead of the queue.
Ready to scope AI Agent Development?
Tell us where the work sits today and what is holding it up. We will come back with the shape of a first phase, what it would prove, and what running it takes.
+91 97915 97993