Engineering around the AI layer —
not just prompts.
AI is one layer. The system around it — databases, queues, interfaces, integrations, evaluation, observability — is what makes a product actually work in front of real users. We engineer the whole stack, end-to-end, and hand it to your team to operate.
Execution teams. Results that work in daily use.
We want happy customers — and no one is happy with an AI demo that shines in the pitch and fails in production. That's why we assemble small, focused teams around the system being built: product, design, engineering, AI. They are accountable for the outcome, not for staying busy. We build AI solutions that are actually used, deliver measurable impact, and fit into existing processes. No gimmicks, no showcases without substance.
Three shapes a build can take.
Pick the one that fits where you are. Each one has a defined output and a clear path to transfer. You can move between them as the work evolves — most engagements do.
MVP Build
A new product or a discrete module, built end-to-end in 8–12 weeks. We own discovery, design, engineering and the first production deploy.
- Product discovery + spec
- Full-stack engineering
- Live deploy + transfer
Embedded Execution Team
A senior team plugged into your organisation for a fixed mission — typically one production system or a complex AI initiative — running in two-week cycles.
- Cross-functional senior team
- Single accountable lead
- Two-week shipping cadence
AI Feature into Existing Product
Built into your stack, behind your auth, evaluated against the same SLAs as the rest of your product. Discreet scope, measurable impact.
- Spec'd against current product
- Continuous evaluation
- Behind your code review
Eight disciplines, one engineering muscle.
Every team we form is built out of these — sized to the system, never billed by the seat. Discipline matters: a feature needs UX, a platform needs architecture, a copilot needs both plus AI integration.
Product Discovery
User research, problem framing, opportunity sizing. A spec the team can build from — not a Miro board nobody opens again.
MVP Development
The smallest thing that proves the model — and runs in production. Spec-driven, evaluated, in front of real users by week eight.
UX/UI Design
Interfaces engineered for clarity and use, not for award decks. We design at the level of the workflow — and prototype in code.
Frontend & Backend Development
TypeScript, Python, the boring reliable choices. Production-grade engineering: tests, types, telemetry, on-call.
AI Integration
Models, agents and eval loops wired into the system around them. Behind your auth, your audit, your release process.
Platform Architecture
The shape of the system before the build: services, contracts, queues, deploy targets. We commit to architecture in writing.
APIs & System Integration
SAP, Salesforce, on-prem databases, mainframe APIs, internal services. The new system has to live with what you already operate.
Internal Tools
The small, sharp interfaces your operators use every day — reviewer queues, eval dashboards, admin consoles. Often the highest-ROI surface.
Boring tools when we can. New ones when they earn it.
We choose the stack project by project. Below is the surface area we work in regularly — selections are made after the problem is understood, not before.