Kamaan NativeX · Software

Built in, not bolted on.

NativeX builds custom software with AI in the foundation from line one — in the data model, the workflows, the interface. Not a legacy app with a chatbot stapled to the side. Software that's AI-native, not AI-retrofitted.

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AI in the foundation

Architected around AI from the first schema.

Governed by design

Human review and evidence gates built into the product itself.

You own it

Full source, architecture, and handoff. It's your software.

The problem

Bolting AI onto old software gives you friction and half-measures.

Most "AI features" are retrofits — a model wedged into an architecture that was never designed for it. The data isn't structured for it, the workflows fight it, and the AI ends up as a demo that never quite becomes core.

NativeX builds the other way: the software is designed around AI from the start, so the intelligence is load-bearing — not decoration.

How we build

Project-based, scoped to what you're building.

Phase 1

Audit

We design the AI-native architecture — data, agents, workflows, review points — and scope the build before writing production code.

Phase 2

Build

We build the software with AI native to it, shipping in reviewable increments against evidence gates.

Phase 3

Grow

Full handoff with documentation, or an ongoing engagement to run and extend it. You own the code either way.

How pricing works: every NativeX project starts with a fixed-fee Blueprint (₹3.5L + GST, 2 weeks) — the same architecture sprint as AIOS and RevX, scoped to your software instead. You get the full design and a fixed build quote before any code is written.

A spec comes in. The Manager routes it and holds the context. Specialist agents build, review, and stage the change, then pass the eval bench before anything touches production. The result lands in the repo and tools you already run — and a human on your team approves before it ships. When a bug surfaces in production, that report loops back to the Manager in real time, so the next build addresses the real regression.

The part most vendors skip: your team reviews every change before it merges, and each agent earns more autonomy only as the evidence supports it. Shipping to production always stays human.

What we build with: Claude, LangGraph, Temporal, Langfuse, MCP, PostgreSQL + pgvector, ClickHouse, Airbyte, Redis, Pydantic AI, Promptfoo, Sentry, Docker, GitHub Actions. Model-agnostic by design: every LLM call routes through our own abstraction layer.

Security & ownership

Your servers. Your IP. Your control.

Deployment

Hosted in your environment

The software deploys to your infrastructure — your servers or your cloud. Your product data and your users' data never leave your control.

Ownership

The IP stays with you

Full source code, architecture, and documentation are yours — in your repositories, under your name. Software you own outright, not a platform you rent.

Security

Enterprise-grade by default

Encryption in transit and at rest, least-privilege access, and audit trails engineered into the product from the first commit — not patched in for a compliance review.

Built governed from day one — not patched for compliance later.

The Kamaan guarantee

Nothing goes live on a promise.

At week 8 of every Build, your own team reviews what the AI produced. If they don't approve at least 90% of it, it doesn't go live. We rescope or refund. You own everything we build: the code, the rules and the documents.

See what the Blueprint includes

Before you hire the next person

What would one AI assistant cost vs one more hire?

Put in a salary and the number of hires you're planning. See the 3-year cost of each and the month the AI pays for itself.

Run your numbers · 2 min

Build it AI-native from day one.

Tell us what you're building. We'll scope an AI-native architecture and show you what it makes possible.

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