End-to-end product builds
From architecture through UX, backend, AI systems and infrastructure — one accountable team.
AI Engineering
Custom Production AI Development
From discovery through deployment, we engineer AI products and internal systems built for scale, security, and ROI.
- 100%IP ownership stays with you
- 8–12 wkstypical first production release
- Seniorengineers only — no bait and switch
Capabilities
Full-stack AI engineering on demand
End-to-end design and build of production-grade custom AI systems for the enterprise.
AI system integration
AI woven into your existing products and platforms without destabilizing them.
Legacy modernization
Aging systems extended with AI capabilities — or strangled and replaced deliberately.
Team augmentation
Senior AI engineers embedded with your teams, transferring capability as they build.
How it works
The build partner for what doesn't exist yet
When your use case doesn't fit a product off the shelf, you need engineers who've shipped AI to production — repeatedly.
Engineering craft
Production standards from commit one
Typed codebases, tests and evals in CI, infrastructure as code, security reviews and observability — the practices that make AI systems maintainable after the launch party.
- Evals, tests and security checks in every pipeline
- Infrastructure as code on your cloud accounts
- Documentation and runbooks as deliverables, not afterthoughts
// Route work to the right model const result = await ai.run({ task: "contract_review", context: retriever.fetch(doc), guardrails: ["pii", "grounding"], fallback: "gpt-4.1", });
RESTSDKWebhooksMCP
Delivery rhythm
Working software every two weeks
Short cycles, demos on real data, and course corrections while they're cheap. You see progress in software, not status decks.
- Two-week sprints with demoable increments
- Real-data milestones over synthetic demos
- Transparent backlog and burn you can inspect anytime
Invoice exception workflowRunning
✓Extract invoice fields1.1s
✓Match against PO0.6s
Resolve mismatch with agentrunning
·Post to ERPqueued
Capability transfer
Your team stronger after we leave
We build with your engineers, not around them — pairing, reviews and handover built into the plan, so the system's owners understand it deeply by launch.
- Pairing and code review with your engineers
- Architecture decision records for every major call
- Structured handover with on-call shadowing
Copilot
Draft renewal summary for Acme Corp
3 accounts show churn risk — view analysis
Ask anything…
Use cases
Where custom ai development delivers value
Bespoke AI products
Systems too specific for off-the-shelf tools, built to your workflow.
AI feature delivery
Capabilities added to existing products under tight release trains.
Prototype-to-production
Promising POCs re-engineered to survive real users and real load.
Complex integrations
AI stitched across ERP, CRM and legacy estates with proper contracts.
Regulated builds
Systems delivered under compliance, audit and validation regimes.
Embedded senior teams
AI pods accelerating your roadmap inside your rituals and tools.
Delivery
How we build it
We start from the business outcome, then design agents, models, tools and guardrails that can survive production — not just a demo.
- Production-ready architecture
- Secure tool integrations
- Measurable business KPIs
- Operate & improve playbooks
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1
Discover
Map workflows, data, constraints and ROI.
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2
Architect
Define models, tools, memory and trust boundaries.
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3
Build
Ship a production-ready system with evals and observability.
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4
Scale
Optimize cost, quality and adoption across teams.
Third partner we tried. First one where the seniors who scoped the work actually wrote the code — and where our own engineers came out the other side able to extend the system without help.
Works with your stack
Built on the tools you already run
We integrate with your models, clouds, data platforms and enterprise systems — no rip-and-replace.
- Python
- TypeScript
- React
- Next.js
- Node.js
- Go
- Postgres
- Kubernetes
- AWS
- Azure
- Anthropic Claude
- OpenAI
FAQ
Common questions
How do you scope custom work honestly?
Discovery first: we prototype the riskiest assumption on your real data before quoting the full build. Fixed-scope phases with demoable milestones keep estimates honest and exits clean.
Who owns the code and models?
You do, entirely — repositories in your org, infrastructure in your accounts, IP assigned in the contract. No platform dependency on us survives the engagement.
What if requirements change mid-build?
They will. Two-week cycles absorb change without drama: we re-prioritize the backlog together and re-forecast openly. What we won't do is silently absorb scope until quality breaks.
Can you work within our security constraints?
Yes — your cloud, your VPC, your access controls, your review processes. We've delivered under healthcare, financial-services and public-sector regimes.
Next step
Build what off-the-shelf can't
Bring the problem no product solves — we'll scope it honestly and build it properly.