01
Fixed-scope project
A defined outcome, a fixed price and a timeline agreed upfront.
- Price agreed before work starts
- Milestones with clear deliverables
- Ideal for a first collaboration
Best forMVPs, websites, well-defined features
AI is only useful when it changes a number your business cares about. We build agents, assistants and retrieval systems grounded in your own data, and we measure them before and after they go live.
How we deliver
Five phases, each with something concrete you can review before we move on.
We map goals, users and constraints, and agree on the smallest version worth building.
A written scope, an estimate, a plan and the main risks, in plain language.
Architecture, data model and interface prototypes, validated with you before any code.
A clickable prototype and a short technical design document.
Short iterations, a working demo every week, tests and code review on every change.
A weekly demo, a short written update and steady progress you can see.
Production hardening, monitoring, a security review and a calm go-live.
Your product live in production, plus a runbook explaining how to operate it.
We keep improving it with you, or hand it over to your team with full documentation.
A prioritised roadmap, or a handover with documentation, access and a walkthrough.
Ways to work together
Every engagement starts with a free 30-minute call and a written proposal. No commitment before that.
01
A defined outcome, a fixed price and a timeline agreed upfront.
Best forMVPs, websites, well-defined features
02
A dedicated team of our engineers working as an extension of yours, billed monthly and scalable as you grow.
Best forProducts in active development
03
A short, focused review of your architecture, code, cloud costs or AI strategy.
Best forSecond opinions and technical due diligence
Questions
Agents that automate defined tasks, assistants and chat over your documents (RAG), classification and data extraction pipelines, and AI features inside your existing products.
Yes. We design access controls, keep data in your infrastructure or with approved providers, log usage and add human review where the stakes require it. We choose providers and settings that do not use your data to train their models.
We agree on a business metric before we start and build an evaluation suite that tracks quality, cost and latency before and after launch.
Services
Contact
Tell us what you are building. Our team reviews every request and replies within one business day, with questions, not a sales script.