Method
How we build agents that survive contact with real customers
Most AI agent projects fail the same way: they start as a platform, they answer from nothing, and nobody can see what the agent did. This is the method we use instead — the one we hold our own production agents to.
The sequence
Five phases, in order
- 01
Find the job
We look for one repetitive, text-heavy job with a clear right answer. Not a strategy deck — a job.
- 02
Design the agent
What it decides, what data it can read, which tools it can call, where it must stop and ask a person.
- 03
Build and connect
The agent, grounded in your own data, wired into the systems it needs — CRM, WhatsApp, sheets, accounting.
- 04
Deploy with a human in the loop
It goes live handling a slice of the work, with a person reviewing what it does before the loop widens.
- 05
Operate and improve
We watch traces of real behaviour and tighten it. An agent is a system you run, not a project you finish.
Guardrails
The engineering that makes an agent trustworthy
Grounded in your data
The agent answers from your documents, catalogues, price lists and records. Retrieval over your own material is what separates a useful agent from a confident stranger.
Tools instead of guesses
When the agent needs a fact or needs to change something, it calls a tool in your systems. It does not improvise an answer it has no way of knowing.
An explicit stopping point
We define when the agent must hand off before we design what it says. Every agent we run in our own products ends in a human when it should.
Traceable behaviour
Each decision leaves a trace you can read: what it understood, what it looked up, what it did. Agents you cannot inspect are agents you cannot improve.
Reversible rollout
Agents go live behind flags on a slice of the work, with a person reviewing. If something misfires, it is switched off without taking the business down.
Cost and latency as design constraints
A reply that arrives too late or costs more than the work it saves is a failed feature, however clever it is.
Straight answers
What we won't promise you
This section exists because most AI vendors won't write one.
We will not promise to replace your team. Every agent we run hands work back to a person.
We will not quote efficiency percentages we have not measured in your business.
We will tell you when a plain automation, or a better form, would beat an AI agent.
We will start you on one job, not a platform — because agent projects fail when they start big.
What we connect to
Agents are only useful when they can reach your systems
These are the integrations we run in our own products today — the plumbing an agent needs to actually do something rather than just talk.
Messaging
- WhatsApp Business API
- SMS / DLT
- Email-to-lead
- Google Meet
Lead sources
- Facebook Lead Ads
- Instagram Lead Ads
- IndiaMART
- Justdial
- TradeIndia
Money & compliance
- Razorpay
- Tally
- GSTN / GSTR-1
Data & automation
- Google Sheets
- Zapier
- Webhooks & REST API
- Self-hosted n8n
Anything else with an API, webhook or database can be connected — these are simply the ones already running in production.
FAQ
Common questions
How do you stop the agent from making things up?
Three things together: ground it in your own data rather than general knowledge, restrict what it can say and do to defined tools, and put a human in the loop wherever a wrong answer costs money. Nobody eliminates the risk entirely — anyone who says otherwise is selling.
How long until an agent is live?
A focused first agent handling one job is a matter of weeks, not quarters, provided we resist scope creep. Widening what it handles happens after it has proven itself on the narrow slice.
What do you need from us?
Access to the process you want automated, whatever documents or data the agent must answer from, and one person on your side who knows how the job is actually done today.
Who owns what you build?
You do. We agree ownership and access in writing before the project starts, including where the agent runs and who holds the credentials.
Start with one job
Tell us the task your team repeats every day. We'll tell you whether an agent should do it.