Product engineering for AI applications and important workflows
Take ownership of the product layer around an AI feature or operational process: interfaces, integrations, release discipline and the engineering details that make it dependable.
Use this when the product layer needs experienced ownership
Good fit
A real product constraint needs solving
- You are integrating AI, replacing a fragile workflow or shipping a product with meaningful operational consequences.
- There is an accountable product or technical owner on your side.
- You need architecture and delivery ownership—not only individual tickets.
Bring to the brief
The context that makes planning useful
- The user journey, existing system and decision the product must support.
- Known integrations, data boundaries, reliability concerns and deadline.
- Who will own the product after the first release.
Receive
A product foundation your team can use
- A practical architecture and implementation plan.
- Release, observability and handover work proportionate to the product risk.
- Clear decisions on what to build now, defer or simplify.
Built from proven components, not from scratch
The fastest path to production isn't reinventing the wheel. We use Supabase for auth and database, established cloud platforms for hosting, battle-tested libraries for everything repetitive. Our engineering time goes into your product logic, not infrastructure plumbing.
This means faster delivery and — critically — an application your team can maintain and extend without us. We optimize for your independence, not our recurring contract.
What we deliver
- Discovery & technical architecture (week 1)
- UI/UX design in Figma with client review
- Production-ready frontend (React / Next.js / TypeScript)
- Backend API with OpenAPI spec and full documentation
- Database design, migration strategy, and backup plan
- Third-party integrations (auth, payments, CRM, email)
- Cloud infrastructure, CI/CD pipeline, staging environment
- QA, security review, performance testing
- Monitoring, logging, alerting setup
- Long-term post-launch partnership
Technology we work with
Opinionated choices chosen for production reliability, maintainability, and the size of the talent pool available to you after we're done.
Frontend
Backend
Platform
Cloud
AI layer
Tooling
How we work together
Three engagement models depending on where you are. Scope is always agreed upfront — no surprises mid-project.
Focused product release
A bounded release around one user outcome, with an architecture and delivery plan agreed before build.
Product Build
A product programme with several modules and integrations, sequenced around operational risk and user evidence.
Team Extension
Senior engineers embedded in your team. We contribute to architecture, code, and product decisions — not just tickets.
Choose a more specific path when one exists
AI inside an existing product
Integrate an AI workflow or RAG
For reliable retrieval, evaluation and human-review design around a working product.
Explore AI workflow integration →New product opportunity
Launch a focused AI MVP
For a defined user problem that needs a bounded first release and clear product ownership.
Explore AI MVP delivery →Ready to build your product?
Share the workflow, product constraint and current system. We will use it to identify the most useful product-engineering path.