Make your product AI-native
— discoverable, usable, built for what's next.
Agents and models are the new interface. We embed the AI layer your roadmap needs: MCP servers, agent-ready docs, AI-first UX, and production AI features — the same engineering discipline we use on enterprise AI systems.
Our team has worked with
Pricing by scope
Engagement type
Structure
Expertise
Is this track right for you?
Built for teams that need their product discovered, integrated, and shipped with real AI — not slide-deck AI.
This track is for you if
You ship a SaaS or API and want AI agents and developers to use it reliably
Your docs and APIs are human-first and you need them agent-ready
You are adding AI features and want production-grade guardrails, not demos
You need MCP, RAG, or LLM integrations designed for how you actually run
Consider a different track if
You only need generic content writing or a ChatGPT wrapper — use a freelancer
You have no product yet — start with Foundational Build or Engineering Leadership
Your blocker is unstable core product or infra — stabilise with Tech Rescue first
What we deliver
Four layers. One engagement, scoped to what you need.
Each layer is optional — we agree scope before work starts. Together they make your product usable by agents, legible to models, and shippable with real AI features.
Make your product natively accessible to AI agents.
MCP is the emerging standard for agents calling your tools. We design and ship MCP servers so agents can use your product safely and predictably.
- MCP server architecture design
- Tool definition and schema design
- Authentication and permission scoping
- Testing with major agent frameworks (Claude, OpenAI, LangChain)
- Documentation for agent developers
- Version management and compatibility planning
Who this is for: Founders with SaaS or API products who want to be usable by AI agents and visible in AI-first workflows.
If AI can't understand your product, it can't use it.
We turn human-only docs into structured, agent-readable surfaces — OpenAPI, tool descriptions, and integration paths models can actually consume.
- Documentation audit against agent consumption standards
- OpenAPI specification review and enhancement
- Structured data layer for agent discovery
- Tool descriptions optimised for LLM consumption
- README and integration guide rewrite for agent audiences
- Ongoing documentation maintenance process
Who this is for: Founders whose product has an API or developer-facing interface that isn't getting the adoption it should.
Make your product easy to use — for humans and agents.
Naming, navigation, and outputs are structured so humans and agents get predictable paths — fewer dead ends, clearer actions, better discovery.
- AI-first UX audit (navigation, naming, affordances)
- Structured output patterns for agent consumption
- Error message and state clarity improvements
- Consistent action naming and schema
- Discoverability improvements (search, metadata, indexing)
- Product taxonomy and categorisation review
Who this is for: Founders whose product is functionally strong but struggles with adoption — both from human users and AI integrations.
Add AI capabilities to your product — built properly, not bolted on.
RAG, evals, guardrails, and deployment — we ship features that survive real traffic, not demo-day demos.
- AI feature scoping and architecture
- LLM integration (OpenAI, Anthropic, open-source models)
- RAG pipeline design and build where applicable
- Fine-tuning on product-specific data where beneficial
- Guardrails, fallbacks, and human-in-the-loop design
- Evaluation framework so you know when the AI is working
- Production deployment and monitoring
Who this is for: Founders who want to add meaningful AI capabilities to their product — not as a badge, but as a genuine user experience improvement.
Why us
We don't just know AI. We build and deploy it at scale.
Production AI experience
We've built and deployed AI agents, fine-tuned models, and RAG systems for enterprise clients. Not proofs of concept — running systems.
HIPAA-certified AI
BrainCompass is a live, HIPAA-compliant AI platform we built. We know what it means to build AI that's safe, compliant, and production-ready.
Full-stack depth
We don't just build the AI layer. We build the data pipelines, the infrastructure, the APIs, and the user-facing interfaces. End to end.
Same team as enterprise AI delivery
The same team that builds enterprise AI systems for mid-market companies — fine-tuned models, RAG pipelines, agentic systems with guardrails — is the team building AI features into your startup product. The difference between an AI feature that works in a demo and one that works in production is the engineering behind it. That's what we bring.
Ready to make your product AI-native?
Book a free 30-minute intro call. We'll look at your product, identify which of the four AI enablement areas would have the most impact, and scope an engagement around that. No commitment on the call.