AI & Data
Agents that finish the work,not just answer questions.
Autonomous agents that read your data, act in your systems, and know when to hand over to a person.
Sound familiar?
- “Your chatbot answers questions but can't actually do anything, so every real request still becomes a ticket.”
- “Support agents spend their day looking up the same information across four systems.”
- “Leads sit unqualified for two days because nobody has time to research them first.”
If any of those land, this is the page for you. Here's how we approach it.
What you get
What ai agents actually changes.
Takes action, not just answers
Agents that update the CRM, issue the refund, book the slot or draft the proposal — inside your systems.
Escalates instead of guessing
Explicit boundaries on what an agent may do alone, with everything else routed to a person.
Tested before it's trusted
Evaluation suites that measure accuracy on your real cases, so quality is a number rather than an impression.
Every action logged
A complete record of what the agent did, what it read, and why — auditable after the fact.
Cost ceilings enforced
Per-conversation and per-day spend limits, so an unexpected loop can't produce an unexpected bill.
Improves with use
Failures become test cases, so the same mistake doesn't recur.
What's included
Everything in the engagement.
Tool use
Agents that call your APIs and act in your systems.
Retrieval over your data
Grounded in your documents and records, with citations.
Multi-step reasoning
Plans and executes tasks that take several dependent steps.
Guardrails
Explicit boundaries on permitted actions and data access.
Human handoff
Clean escalation with full context passed to the person.
Evaluation suite
Regression tests on your real cases before every release.
Observability
Traces of every step, tool call and decision.
Cost controls
Hard spend limits and model routing by task complexity.
How we deliver
You'll know where it stands every week.
Discovery
1–2 weeksScope document, risk list and a fixed estimateDesign & architecture
2–3 weeksClickable prototype and system designBuild
6–16 weeksA working demo at the end of every sprintTest & harden
ContinuousAutomated test suite, UAT sign-off, security reviewLaunch
1 weekProduction deployment, monitoring and full handoverSupport
90 days includedSLA-backed fixes and a roadmap for what's nextTechnology
What we build it with.
- Anthropic Claude
- OpenAI
- LangChain
- LlamaIndex
- Python
- pgvector
- Redis
- AWS
We choose on fit, hiring pool, total cost and how easily you could leave — not on what we most enjoy writing.
Industries
Where we've done this.
- Finance & FintechKYC, lending and payments built to audit.
- HealthcareABDM-ready systems for hospitals, clinics and diagnostics.
- Retail & E-commerceStock, storefront and marketplace in sync.
- Real EstateLead to site visit to booking, without a spreadsheet.
- TravelGDS, payments and itineraries in one booking flow.
- Logistics & Supply ChainEvery consignment traceable from pickup to POD.
Engagement models
Pick the risk model that suits you.
Indicative starting points. We give a firm number after discovery — a fixed price quoted before we understand the scope is a number designed to be revised.
Fixed scope
₹8,00,000
starting from
A clear brief you want delivered to a firm budget
- Fixed price agreed after discovery
- Defined deliverables and milestones
- Change requests quoted separately
- 90 days post-launch support
Dedicated team
₹3,50,000 / month
starting from
Evolving requirements, or an in-house team that needs capacity
- Senior engineers embedded in your standups
- Scale the team up or down monthly
- You set the priorities each sprint
- Direct access — no account manager layer
Retainer
₹1,20,000 / month
starting from
Ongoing improvement, maintenance and support after launch
- Agreed monthly hours
- Guaranteed response times
- Monitoring, patching and dependency upgrades
- Quarterly roadmap review
A chatbot retrieves information and replies. An agent has tools — it can query your database, call an API, update a record, send an email. That difference is why an agent can close a request rather than describing how to close it.
Constrained tools rather than open access, permission scoping per action, mandatory approval for anything irreversible or financial, spend caps, and full logging. The agent can only do what we explicitly gave it the ability to do.
We build an evaluation set from your real cases and score against it on every change. Without evals you're relying on impressions, which is how agents quietly degrade after launch.
Whichever fits the task, cost and privacy constraints — often several within one system, with cheaper models handling routine steps and stronger ones reserved for hard reasoning. We're not tied to a vendor.
Yes, using open-weight models in your VPC or on-premise where data residency or policy requires it. Quality is lower than the frontier hosted models for hard reasoning, and we'll be direct about that trade-off.
Related services
Often needed alongside.
Start the conversation
Tell us what you need.
An engineer replies within 4 business hours — with questions, not a brochure.
NDA available before you share anything.