3–5× Delivery Speed
AI-assisted generation, enforced coding standards, and bounded feature specs mean we ship the same scope in a fraction of the time — without accumulating technical debt.
The Mansoori AI Development Harness
HowWeShip3–5×FasterWithoutCuttingCorners
AI handles approximately 60% of boilerplate. Engineers own architecture, review every output, and enforce compliance. This is the six-phase process we run on every healthcare and fintech engagement.
How we work
How We Build & Scale Your Product
A structured AI-powered process designed to deliver fast, secure, and scalable products.
Step 01
Discovery & SRS
We begin with discovery and convert your idea into a clear Software Requirement Specification.
Step 02
Product Planning
We map requirements into PRDs, epics, and user stories for predictable sprint execution.
Step 03
AI-Assisted Development
We use AI-assisted engineering workflows to accelerate delivery while keeping architecture clean.
Step 04
Weekly Sprints & Demos
You see measurable progress every week with regular demos and early feedback loops.
Step 05
CI/CD + Cloud Delivery
We set up development, staging, and production with automated deployment pipelines.
Why top 20%
What separates us from the other 80%
Most development shops use AI as a drafting tool and ship whatever it produces. We run a structured harness that enforces quality, auditability, and compliance at every phase.
Compliance-First Architecture
HIPAA and GDPR are not afterthoughts. We specialize in healthcare and fintech, where data protection requirements shape architecture decisions from day one.
Auditability at Every Step
Every AI decision is logged, every code review is tracked, and every compliance checkpoint is documented. Clients and their legal teams can see exactly what was built and why.
The six phases
Every project, every time
This process is not aspirational — it is enforced. Every engagement runs through all six phases in sequence.
Phase 01
Spec & Context Loading
Before any code is generated, we inject project maps, coding standards, architectural constraints, and domain-specific compliance requirements into the AI context window. The AI works inside your architecture from day one.
This means no hallucinated library choices, no HIPAA violations from an uninformed model, and no AI-generated code that contradicts your existing conventions.
Phase 02
Feature Scoping
Each deliverable is written as a bounded FEAT-XXX file that defines scope, acceptance criteria, edge cases, and compliance checkpoints. AI agents receive precise, scoped context — not vague prompts.
Bounded features prevent scope creep and allow AI to generate high-quality, targeted output. Engineers review the spec before generation begins.
Phase 03
AI-Assisted Generation
Claude and GPT-4 draft implementation while senior engineers review, correct, and own every line. AI handles approximately 60% of boilerplate; engineers own architecture, business logic, and all compliance-sensitive code.
This ratio is deliberate. AI speeds up implementation without replacing engineering judgment. No generated code ships without a human approval gate.
Phase 04
Automated QA
Vitest unit tests, Playwright end-to-end tests, and TypeScript strict-mode run on every commit via CI. Nothing ships without a passing automated gate.
Test coverage targets are enforced per feature, not globally. AI-generated tests are reviewed for meaningful coverage — not just line coverage.
Phase 05
Compliance Check
HIPAA and GDPR requirements are enforced at the architecture level — not retrofitted after launch. PHI handling, audit trails, data residency, and access controls are reviewed before every deploy.
For healthcare clients: PHI fields are identified and classified in the data model before development begins. For fintech clients: GDPR data flows, consent management, and right-to-erasure hooks are wired from the start.
Phase 06
Metrics & Retrospective
AI contribution percentage, delivery velocity, and defect escape rate are logged per sprint. We benchmark every project and share honest outcomes with clients in post-sprint reviews.
Transparency builds trust. If AI created a bug that escaped QA, we log it, learn from it, and improve the harness. Clients see the data.
Our niche
Healthcare & Fintech AI Product Studios
We are not a generalist agency. We specialize in AI-powered software for healthcare and fintech — where compliance, data sensitivity, and reliability are not optional. If you are building in one of these verticals and need an engineering partner who understands the domain, we should talk.
60%
AI-generated boilerplate
40%
Engineer-owned logic