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A 24×7 engineering team you can trust.
10× faster sprints. For the cost of 1 engineer.

A governed & auditable agentic software factory takes your approved intent to tested software, day and night. Driven by intent, spec and tests: agents do the heavy lifting, you decide. Every action is gated and on a tamper-proof ledger.

Why an autonomous engineering team you can trust 2 minutes

Why now

AI writes code fast. Can anyone prove it is right?

Agents ship overnight. Proving it matches what the business asked, and passed the controls an auditor expects, still takes people — and the people cannot keep up.

The backlog outgrows the team.

Sprints land ten times faster — a whole team’s output, no hiring

Knowledge walks out the door.

It stays with the system — and keeps learning

Outages don’t keep office hours.

We’re on it 24×7 — your team sleeps

Engineering teams cost a fortune.

One engineer operates the whole factory — for the cost of one

What you get

Two things we take off your plate. For good.

Get the work done

Intent first. Spec and tests before code.

Agents write the specification and lock the acceptance tests from your approved intent, then build only to them — while you sleep.

  • Spec and tests first
  • Works 24×7
  • Costs < 1 engineer

Keep what you know

A memory that never leaves — and never stops learning.

It learns your systems, answers with sources, keeps itself current, and stays with the system when people move on.

  • Answers with sources
  • Stays when people leave
  • Guards 24×7

What it’s worth

The same result or better. A fraction of the engineering time and cost.

One mid-sized system
Team size: Conventional 8 people, Cognizhi 1 engineer (−88%)
Sprint: Conventional 2 weeks, Cognizhi 4 hours (> 10× faster)
Cost: Conventional 100%, Cognizhi ~10% (~−90%)

Potential saving

Up to 90% less engineering time
Up to 90% less cost

vs. a conventional project

Capacity
A full engineering squad’s output, delivered by one engineer.
Time
More than 10× faster sprints.
Run cost
Less than one full-time engineer a year.

Illustrative for one mid-sized system. We rebuild this with your team size, rates and timelines during the assessment.

Your alternatives, honestly

  • Do nothing
    Risk grows. People leave.
  • Hire
    Months to find. Leaves again.
  • IT services firm
    Eight people. Open-ended bill.
  • Cognizhi
    24×7. Less than one engineer.

Control

Agents do the work. You decide.

Your approval

Nothing moves on until it has earned it.

You approve the intent and the design before. A policy gate checks every agent action. The right role approves the release after — and nobody approves their own work.

Every answer shows its source.

Every requirement traces to its decision, tests, code and results.

Your code never leaves your building.

It runs inside your environment, under rules you can see.

Walk away anytime. Keep everything.

Code, tests, the evidence pack and the knowledge are yours.

Early access

See the real product. Two minutes to unlock it.

Answer a few taps, confirm your email, and open a private preview of both — walked step by step. A founder replies personally.

Questions we are asked

How is this different from an AI coding assistant?

An assistant helps one engineer type faster. This is a delivery factory: it takes your approved intent to a specification and locked acceptance tests before any code, builds only to them, and hands back a signed evidence pack. Your people review outcomes, not keystrokes.

How do we know what it built is right?

Every requirement traces to its decision, its tests, its code and its results. Every sprint leaves a sealed record, and every agent action and approval is written to a tamper-proof ledger an auditor can verify offline.

Does our code or data leave our environment?

No. It runs inside your environment, and nothing is copied out to be worked on elsewhere. A policy gate checks every agent action before it runs, and anything risky waits for a person.

How does the knowledge base stay up to date?

It evolves on its own. As your code, documents and running systems change, it re-learns them — nobody has to write or maintain pages, and every answer shows its sources. Where there’s conflict or ambiguity, a human stays in the loop to validate and confirm. The knowledge stays with the system, not with the team that delivered it.

How much of our team’s time does it need?

Agents do the work; your people decide. That means approving the intent and the design, answering domain questions as they come up, and signing off the release. Each decision goes to the right role — business owner, subject expert, test approver, data owner — and nobody approves their own work.

What happens if we stop?

You keep everything it produced — code, tests, documentation, the evidence pack and the knowledge base. None of it is locked to us.

Is all of this available today?

Not all of it, and we will tell you exactly which parts are live and which are still being built. The private preview shows where each piece stands.

What does early access involve?

You tell us what you would use it for, we show you the product, and a founder talks you through the two ways to work with us: an assessment followed by delivery, or a design-partner track.

About

Cognizhi is a Singapore company building AI for the systems businesses actually run on — and telling you plainly what is finished and what is not.