You've got the idea. We ship the working product.
We design, build and ship production AI products, the kind that usually need a full engineering team and six months. MVP to live in about a month, then we hand you the keys.
Claude
Codex
Cursor
Lovable
Gemini
ClaudeSound familiar?
If two of these are true, your AI is stuck in the demo stage.
- A slick AI demo was built, but it never reached production
- Token bills climb every month and nobody can say why
- Agents work in testing, then break on real inputs
- No one on the team can actually ship it and keep it running
- You can't see what an agent did, or why it failed
- Every new feature waits on a dev team you don't have
The shift
From "it mostly works" to "it's engineered to last"
- Works on the happy path, breaks on real inputs
- Prompts copy-pasted, no versions, no tests
- One big model for everything, tokens everywhere
- Fails silently, you hear about it from users
- Only the person who built it understands it
- Shipped to production, handles real load
- Prompts and agents in code, versioned and tested
- Right model per task, token cost tuned down
- Retries, fallbacks and alerts when something's off
- Documented, with your team trained to run it
What we build
What we can build for you
These are the exact skills behind the products below. Take one piece, or hand us the whole build.
AI products & MVPs
Full, AI-native web apps, from a blank repo to a live product your users can actually touch.
Production AI agents
Multi-step agents that do real work on a schedule, with guardrails, retries and fallbacks.
Choose the right stack
We pick the tools and infrastructure that fit your product and budget, not our habit, and you own all of it.
REST APIs
Clean, documented APIs so your product becomes something other software and teams can build on.
MCP servers
Make your product Claude-native, usable directly by Claude Code, Cowork and other agents.
AI cost optimization
The right model per task, caching and tighter prompts, so token bills drop without losing output.
Monitoring & model logic
Dashboards, alerts and routing so you see every run and catch drift before your users do.
Fractional AI CTO
We own the architecture and the build calls on a retainer, so you get senior judgment without the hire.
Team training
Your team learns to ship with Claude, Codex and Cowork, and to build agents that hold up.
The systems we design and build.
These are the shapes of work we take on. Each one is a real engineering project, not a prompt pack, and each has a failure mode that only shows up in production. That is the part we are hired for.

Multimodal biometric verification
Five separate modalities, each its own research and engineering track: palm vein, iris and eye socket geometry, fingerprint, face, and speech. Different sensors, different model architectures, different accuracy and latency tradeoffs, fused into one identity decision with a confidence score you can defend.

Face recognition at national scale
A recognition pipeline built from first principles rather than wrapped around an SDK: detection, alignment, embedding and one-to-many matching, tuned to hold accuracy at airport throughput. The hard part is not the model, it is holding precision steady as the gallery grows into the millions.

Geospatial and satellite intelligence
Ingestion pipelines for satellite imagery, feature extraction from multi-spectral bands, and analytical models that turn raw scenes into something a non-specialist can act on. Cloud masking, revisit gaps and calibration drift are where these projects usually fail.

Anomaly detection at exchange scale
High-throughput transaction monitoring where the volume is enormous and the false-positive budget is tiny. Statistical detection finds the outliers, then Claude reads each flagged event in context and explains what it appears to be, so the analyst queue becomes a ranked shortlist instead of a wall.

Clinical and compliance documentation
A conversation or case file in, the structured record a regulator expects out. Speaker separation, transcription with domain vocabulary rather than generic speech models, then mapping to standardised fields. A human approves before anything commits, and every field links back to its source line.

Real-time video analytics
Object detection, activity recognition and event triggers running on live camera feeds, at frame rates that make the output useful rather than forensic. Built to survive bad lighting, occlusion and cameras nobody has cleaned in a year.

Ask your database in plain English
A retrieval layer resolves a plain-language question against your actual schema, Claude writes the SQL, and the answer returns with the query it ran. Grounded in the real table structure, so it cannot invent a column or a join. Reporting answered in seconds instead of a BI queue.

Document and imaging pipelines
Handwriting, scans, forms and photographs turned into clean structured fields your systems accept. The unglamorous work that quietly consumes a back office, and the place where accuracy on the worst ten percent of inputs decides whether anyone trusts the system.

Enterprise data harmonisation
Disparate sources reconciled into one analysable layer: schema mapping, deduplication, identity resolution and pipelines that keep working when an upstream system changes shape without telling you.

An MCP server for your product
Your product becomes a set of tools Claude can call directly, with permissions approved one tool at a time. Customers stop exporting data to paste into a chat window, and Claude Code and Cowork use your software like any other tool. We have shipped one to production, in the case study below.

Contract and policy intelligence
Long-context review that holds a whole agreement at once instead of sliding a window over it. Flags the clauses that differ from your standard position, explains how, and quotes the paragraph. Useful exactly where a summary is not.
The Engagement
Start with a consult. Own everything after.
You start with a free 30-minute call. If it's a fit, the consult is a focused, paid engagement that ends with a plan you can act on and working artifacts you keep. Building it is a separate step, and we can do that too.
We design the system
An AI Systems Audit, architecture design, GTM strategy, and local agent and Claude Code consulting. You leave with working artifacts you keep, whether or not you build with us.
We build it, you own it
Optional, and scoped separately. We build the product, APIs, MCP servers and agents inside your own repos and accounts, ship them to production with monitoring, then hand you the keys.
Yours to keep
Everything we produce lives in your accounts and tools. No platform to stay subscribed to, and nothing locked away from your team.
What you walk away with
Satisfaction.
A product that ships, works, and is yours. Concretely, that means:
A production-grade build of your product, API or agent, live and handling real users
Your AI workload re-engineered for cost: the right model per task, caching and tighter prompts
Hard before-and-after numbers on token spend and reliability, not vibes
An MCP server and API docs, so your product plugs into Claude Code and Cowork
Monitoring, alerts and fallbacks, plus everything documented and owned by you, with your team trained to run it
Proof
Products we've designed, built and shipped
More than a vendor
If we believe in it, we don't just build it. We back it.
Most teams ship your MVP and send an invoice. When we love where you're headed, we go further: we invest our own time to help you scale, and we're open to equity or revenue-share when the vision is right. We win when you win.
Questions
The things teams ask before we start
Can you really ship a real product in about a month?+
How is this cheaper than hiring a team?+
What does "you'd invest" actually mean?+
What if we just need part of it, like an API or an MCP server?+
Do you work in our own codebase and accounts?+
Can you act as our fractional AI CTO and train our team?+
Do we own everything you build?+
Book a free 30-minute call. We'll scope what we'd ship first and how fast. If we love where you're headed, we'll tell you how we'd back it too. No deck, no pressure.
Tell us what you're building
30 minutes, no slides. The product, the AI behind it, and where it's stuck or bleeding cost.
We scope the build
The architecture, what we'd ship first, and what it costs to build and run. Live, on the call.
You decide, no pressure
You leave with a clear plan either way. Start the consult, take it in-house, or just keep the map.

