An agent that only talks is a chatbot. We build agents that take actions in real systems — which raises the engineering bar considerably, because now a mistake changes your data.
The moment an AI system can write to your database, book a slot or send a message on your behalf, the interesting question stops being model quality and becomes permissions: what can it do unsupervised, what needs approval, and how do you audit what it did.
That is a systems design problem more than an AI problem, and it is where most agent projects are underestimated.
What we build
Agents with scoped tool access
Explicit, enumerated capabilities — read this, write that, never touch the other thing — rather than broad database access and optimism.
Human-in-the-loop approval
High-consequence actions queue for a person. We work out which actions those are with you rather than deciding unilaterally.
Audit trails
Every action logged with the reasoning and inputs that led to it. Without this you cannot debug an agent, and you certainly cannot explain it to a customer or a regulator.
Multi-step workflows
Agents that complete a real chain of work — intake, enrichment, routing, follow-up — with defined behaviour when a step fails rather than an infinite retry loop.
How we work
- 1
Enumerate the actions
We list every action the agent may take and classify each as autonomous, approval-required, or forbidden. This list is the actual specification.
- 2
Build read-only first
The agent runs in observation mode against real data and proposes actions without executing them. You review the proposals for a period before it is allowed to act.
- 3
Grant write access narrowly
One low-risk action type at a time, with the audit trail in place before the permission is.
- 4
Monitor and constrain
Rate limits, cost ceilings and alerting on anomalous behaviour. An unconstrained agent is a production incident waiting for a trigger.
How we price it
Priced per action-surface rather than per agent, because the cost is in the integrations and guardrails, not the prompt.
Software of ours you can open right now
These are live production sites running on our platform, not mockups. Open any of them, then ask us to walk you through the admin side on a call.
- Bawana Industrial Tools & Hardware
- Delhi Corporate Chambers
- Delhi Skyline Realty
- Dot2Dotz Industrial Marketplace
- Foodlet
- Freelance HUB
- JustLaunch
- Propnal Real Estate
Questions we get asked
How do we stop an agent doing something damaging?
Permissions, not prompting. Instructions in a prompt are a request; a permission boundary in code is a guarantee. Destructive actions should be structurally impossible for the agent to perform, not merely discouraged.
What is the difference between an agent and a chatbot?
A chatbot produces text. An agent takes actions in real systems. The second needs authentication, permissions, audit logging and rollback — which is most of the work and most of the cost.
Can agents work with our existing software?
If it has an API, generally yes. Where it does not, we build the integration layer first, and that is usually the larger part of the project.
When are agents the wrong answer?
When the process is deterministic. If the rules can be written down completely, a rules engine will be cheaper, faster, fully auditable and never wrong in a surprising way.
Talk to us
Tell us what you are trying to build. The first call is a scoping conversation, not a pitch — and if you do not need us, we will say so.