AI-native software company · US and Canada

From approved requirement to production-ready software, in weeks, not quarters

AI does the build; senior engineers own every decision. You accept the result against the evidence it produced.

Check project fit →See a sample specification

What AI-native means here

  1. 01 · Contract

    The Executable Specification is the contract for the work.

  2. 02 · Agents execute

    Agents execute inside it, within boundaries people agreed.

  3. 03 · People decide

    People own every gate, review, acceptance and release.

Nothing on this page is claimed without a measurement.

See how we measure

20+ years

working with US and Canadian customers

US + Canada

our primary market

Enterprise scope

modernization, integrations, products

Measured

before and after on every pilot

01 · What changes

You buy a defined outcome, not engineering capacity

The difference is not AI itself. It is how scope, execution, evidence and acceptance are set up.

Traditional outsourcing

You pay for team time and track progress through status reports.

Team → Hours → Activity → Status → Release

You manageEngineering effort

AI-native delivery

We agree the result and how it will be accepted before work starts.

Outcome → Scope → Acceptance → Execution → Evidence

You manageValidated outcome

02 · What you receive

Three things you can check, accept or reject

Not a promise of "more productivity". Real artifacts you work with from day one.

01You approve it

Executable Specification

What is delivered and how it is accepted. Versioned as the project changes.

02You accept it

Production-ready increment

A bounded piece of software, built, tested and reviewed, ready for sign-off.

03You decide with it

Delivery Evidence Pack

What is done, what remains, and what needs your decision.

You pay for a defined outcome and the evidence to accept it, not for engineering activity.

03 · Specification

One versioned document keeps intent and execution aligned

Instead of being scattered across tickets, chats and people’s heads, the logic lives in a single delivery contract: explicit, versioned, and traceable.

Scope is bounded

Everyone knows what is in and out of the current cycle.

Acceptance is measurable

You know what evidence approves the result.

Change impact is visible

A changed requirement traces to tests, controls and release conditions.

Human gates are explicit

Agents work inside boundaries people agreed.

pilot-04 / executable-spec.md
v3
ObjectiveReduce approval cycle time by 30%
ScopeWeb workflow · API · audit trail
RollbackCritical defect or failed validation
  1. AC-01Functional flow matches business rulesPassed
  2. AC-02Response time within agreed thresholdPassed
  3. AC-03Security controls and checksPassed
  4. AC-04Auditability of every decisionPassed
  5. GATEBusiness-owner acceptanceApproved
4 / 4 criteria validated by agents · human gate approved

04 · Delivery cycle

People open and close every cycle

Agents do the execution. Every decision before and after it belongs to a person.

  1. 01Human

    Specification approval

    Outcome, scope, business rules and acceptance criteria agreed in one Executable Specification.

  2. 02Agent

    Implementation

    AI-assisted execution against the approved specification, inside agreed boundaries.

  3. 03Agent

    Continuous validation

    Automated tests and quality gates run on every change, traced to the acceptance criteria.

  4. 04Human

    Code and test review

    Senior engineers review code and tests. Architecture and security decisions stay with them.

  5. 05Human

    Acceptance and release

    The business owner accepts the result. Release and rollback authority stay with people.

Pilot 04 · governed executionStep 01 / 05

05 · Control

See the project, not a status update

Speed only matters if control, quality and traceability hold.

pilot-04 / delivery-control
Demo
StatusOn track
Progress71%
Scope done34 / 48
Quality gate96%
Discovery and specs100%
Implementation76%
Testing and quality63%
Deployment32%

Demonstration data.

Stays with people

  • Specification approval
  • Architecture and security
  • Code and test review
  • Business acceptance
  • Release and rollback

Next decision

Validate 6 edge cases before acceptance review.

06 · Evidence

Plan against actual on real client scopes

Measured against each client's own baseline. Not a universal guarantee.

Industry

Healthcare Construction Software and SaaS Finance

Healthcare / MedTech

Cardiology diagnostics and ECG analysis

~6×faster than plan
Plan
59 days
Actual
~10 days

Clinical scenario and web platform delivered to production.

Construction / ConTech

Checklist management platform

15.6×faster than estimate
Estimate
78 hours
Actual
5 hours

Automated tests added; existing PR and release process kept.

B2B SaaS / Migration

iOS to Flutter migration

5.2×less engineering effort
Estimate
52 p-weeks
Actual
10 p-weeks

Mobile app moved to Flutter against a measured baseline.

Finance

Case study in preparation

Placeholder for an upcoming client story.

Coming soon

Healthcare

Case study in preparation

Placeholder for an upcoming client story.

Coming soon

Construction

Case study in preparation

Placeholder for an upcoming client story.

Coming soon

07 · Fit

Where AI-native delivery works best

Bounded, testable work in products that already run the business.

Legacy modernization

Move old systems forward in testable slices.

Platform migration

Change frameworks or platforms without stopping releases.

New features

Add capabilities to a product that is already live.

Integrations

Connect systems through clear interfaces.

Refactoring and tech debt

Make the codebase safer to change.

Testing and documentation

Bring test coverage and docs up to date.

Not a good first engagement

We'd rather say it upfront than force the model where it won't work.

  • No clear business owner
  • Result can't be measured or accepted
  • No access to code, systems or data
  • Critical change with no validation window
  • Scope can't be bounded
  • Business rules left open on purpose

08 · Who we are

AI-native execution on top of established engineering

The delivery model is new. Responsibility for complex software is not.

20+years of team experience with customers in the United States and Canada

Programs

Large technical programs

Complex products, long-lived systems, integrations and modernization.

Discipline

Enterprise delivery practice

Architecture, quality, release management and accountable ownership stay in the model.

AI

AI on top of engineering

Applied within mature practice, never as a substitute for it.

09 · How we start

Start with evidence, then expand

Low commitment for you, a measurable baseline for the next decision.

Stage 01

Assessment

Fit, baseline, constraints and the main bottleneck.

Stage 02

Controlled pilot

One bounded initiative with metrics and stop conditions.

Stage 03

More scope

Only after the pilot beats the baseline.

10 · Assessment

Check whether your project fits

Not a commitment. A short description is enough for the first review.

You get a view on

  • Project fit
  • Where time is lost today
  • Baseline to compare against
  • Realistic acceleration to test
  • Risk controls to make explicit
  • A pilot that proves or disproves it
fit-review / project-brief.form
Draft

11 · FAQ

Questions teams ask first

Does AI replace accountable engineers?
No. Architecture, critical decisions, review, acceptance and release stay with people.
How is quality controlled?
Through the specification, automated validation, code and architecture review, quality gates and explicit release and rollback conditions.
What if requirements change?
The change goes into the specification first. Its impact on scope, tests and release is assessed before work continues.
Do you guarantee a speed-up?
No. Acceleration is project-specific. The pilot measures it against your baseline before any wider commitment.
Can we start small?
Yes. A bounded pilot is the preferred way to start.

Next step

Let's see if your project fits

Assess my project →

A structured first conversation, not a commitment.