AI that does real work, not just demos.
We add AI to products and operations where it pays for itself: features your users notice, agents that take repetitive work off your team, and automations that run quietly in the background, with guardrails and a human in the loop wherever mistakes would be costly.
Start from a task worth automating, not from a model.
Answers come from your data, with sources, not guesses.
Hard limits in code, approvals where money or customers are involved.
Evaluations and cost tracking before and after launch.
From a first AI feature to agents in production.
We pick the smallest approach that solves the problem: often a well-designed prompt and good data beats a complex system.
AI features in your product
Assistants, smart search, summaries and drafting built into the app your users already use.
Answers from your own data
Retrieval over documents, tickets and knowledge bases, with citations so people can check the answer.
AI agents with guardrails
Agents that research, draft and act through tools you control, with approval steps for anything irreversible.
Workflow automation
Connect email, CRMs, spreadsheets and internal tools so routine work moves without copy and paste.
Evaluation and safety
Test sets, regression checks and monitoring so quality doesn't silently drift when models change.
Cost and speed tuning
Model choice, caching and batching so AI features stay fast and affordable as usage grows.
AI inside a real-time product.
In Signal Desk, our own market-signals platform, a local model scores every signal, Claude drafts strategies from plain English and explains statistical reports, and an automated studio turns the app's own data into short videos for review. The rules that matter are enforced in code, not left to the model.
Read the Signal Desk case study- Model output is checked and bounded by code before anything happens
- Human approval on decisions with real consequences
- Every AI call logged with its purpose, tokens and outcome
- Works without the AI too: it adds value, it isn't a single point of failure
From idea to an AI feature people trust.
Founder-led from the first call, with a working result every week.
- 01
Find the task
Pick one workflow where AI saves real time or adds clear value, and define what 'good' looks like.
- 02
Prototype
A working prototype on your real data within days, so decisions are based on results, not slides.
- 03
Evaluate
Measure accuracy, cost and failure cases on a test set before anything reaches users.
- 04
Ship and monitor
Integrate, add guardrails and monitoring, then improve with real usage data.
Start small: a one-week, fixed-price sprint
In one week we build a working AI prototype on your own data, for example an assistant over your docs or an automation for one workflow, with a written evaluation of how well it works and what it would cost to run. Fixed scope, fixed price, agreed before we start.
The right tools for the job, not our favourite ones.
Questions we hear most often.
Tell us what's stuck.
Book a call and describe the problem. We'll tell you whether a one-week sprint can fix it, and if it can't, what would.