The AI engineering team your startup hasn’t hired yet.
We build agent harnesses, evaluation pipelines and cost-efficient inference for newly funded startups: the infrastructure that keeps AI features reliable in production and affordable as usage grows.
NDA on request · Written proposal within 48 hours · Code in your repository from day onehallucination rate after adding evals and tracing
cost per request after moving to self-hosted inference
documents in a retrieval system where every answer cites its source
median latency on an AI service with 50K monthly users
Infrastructure for AI that has to work in production.
Most AI prototypes work in a demo. The hard part is making them reliable, observable and cheap enough to run for every customer. That is the work we focus on.
Agent harnesses
The runtime around your agents: tool and MCP integrations, context and memory management, sandboxed execution, retries, human approval steps and full tracing. Agents that finish long tasks and can be audited afterwards.
Token & inference cost optimisation
Cost per task tracked by feature and customer, then reduced with prompt caching, model routing, context compression and semantic caching.
Evals & regression testing
Golden datasets from your real traffic, automated scoring and a CI gate, so every prompt or model change is measured before release.
Cloud & GPU efficiency
Right-sized inference: quantised models on vLLM, autoscaling and spot capacity, so your credits and runway last longer.
Context engineering & RAG
Hybrid search, reranking and layout-aware parsing, with answers that cite the exact passage they came from.
Guardrails & AI security
Prompt-injection and jailbreak defence, PII redaction and policy guardrails, informed by our own published research.
Fine-tuning & small models
Move high-volume tasks to smaller models you own with LoRA, QLoRA, distillation and speculative decoding.
AI observability
Traces, cost and latency dashboards and drift alerts for every model call: what the model saw, did and cost.
Built for the months after a raise.
Each engagement has a fixed scope and a written proposal within 48 hours. Start with the one closest to your problem; most teams combine two.
AI cost audit
We trace your LLM and cloud spend, find where it goes, and implement the fixes you approve.
Eval & reliability sprint
A measurable definition of "good" for your AI features, enforced on every change.
Agent harness build
From prototype to a production agent your team can extend and trust.
Embedded AI team
Our engineers work as your AI team until you hire one, then hand over.
You’ll always know where your build stands.
Founders in the US, UK, Dubai and Australia.
One engineering team, with a few hours of overlap every day in each time zone. Select a location to read what the client said.
Add this client’s quote here: two or three sentences on what you built together and what changed for them.
What founders ask us first.
The engineering around the model: harnesses, evals, guardrails, observability and cost controls. Most of the reliability and cost of an AI feature is decided by that layer rather than by the choice of model.
It depends on your traffic and architecture, so we measure before we promise. The cost audit gives you a per-feature breakdown and a list of changes with expected savings, and we implement the ones you approve.
You do. We work in your repositories and cloud accounts from the first commit, and IP assignment is written into the contract.
Yes. We work in your repositories, follow your review process and document everything, so your team can own it after handover.
We work with clients in the US, UK, Dubai and Australia, keep a few hours of overlap each day for calls, and reply in a shared channel.
You get a written proposal within 48 hours of the scoping call. Once it’s approved, work usually starts the following week.
Yes, when your AI needs a product around it. Our work page shows the web, mobile and CRM projects we have shipped.
Tell us what your AI needs to do next.
A 30-minute call with the engineers who would build it. You’ll leave with a clear read on scope, cost and timeline, whether or not we work together.
Book a call