Custom AI development, built for production
Off-the-shelf AI gets you a demo. Custom AI gets you a system that knows your data, fits the way your team works and keeps working after launch. We design, build and run AI features and agents end to end — and we start by finding the place where AI actually changes a decision.
What we deliver
AI strategy & discovery
We map where AI changes an outcome, size the effort honestly and validate the riskiest assumption with a focused proof of concept before anyone commits to a roadmap.
LLM features & copilots
Summarisation, extraction, classification and assistants built into your product, with prompts, evaluations and fallbacks under version control.
AI agents & automation
Agents that call your APIs, follow your business rules and hand off to a human when they should — with guardrails, logging and cost limits.
Machine learning models
Predictive models, recommendations and computer vision trained on your data, when a classic model beats a language model.
Private & self-hosted models
Open-weight models running in your cloud or region when data cannot leave it, including EU and Gulf hosting.
MLOps & monitoring
Evaluation suites, drift monitoring, tracing and retraining pipelines, so quality is measured rather than assumed.
Typical use cases
- Document and email processing that routes work automatically
- Support and sales assistants grounded in your own content
- Forecasting and anomaly detection on operational data
- Image and video analysis for inspection or cataloguing
- Internal copilots for analysts, engineers and operations teams
Technology we use
OpenAI
Ollama
Python
FastAPI
SageMaker
PostgreSQL
How we work
- 01
Discover
We learn the business, the users and the constraints, and agree what success looks like.
- 02
Prove
We test the riskiest assumption first — a prototype or AI proof of concept — before scaling the team.
- 03
Build
Short iterations, working software every two weeks and demos you can click through.
- 04
Run
Launch, monitoring and continued development — or a clean handover to your team.
Related work
Sumus
AI · ESG · Sustainability
An AI product-discovery engine for fashion — scan a garment to reveal its ESG parameters, then compare sustainability across brands. We built the AI tool.
Digital Arrow
Recruiting + HR platform
An HR platform for hiring and processing CVs — timesheets, async video interviews with video requests, time-off, and online signatures. One workspace for the entire hiring lifecycle.
Frequently asked questions
How long does a custom AI project take?
A proof of concept usually takes two to six weeks. Taking it to production — integration, evaluation, security review and monitoring — typically adds one to three months, depending on your systems and data.
Do we need a lot of data to start?
Often not. Many LLM features work with your existing documents and a well-built evaluation set. Where a trained model is needed, we assess data quality in discovery and tell you plainly whether it is enough.
Which models do you use?
Whatever fits the job and your constraints: hosted models from OpenAI, Anthropic or Google, open-weight models such as Llama or Mistral, or classic machine learning. We design so the model can be swapped later.
Can the AI run inside our own cloud?
Yes. We deploy on AWS, Azure or Google Cloud in the region you need, including EU and Middle East regions, and can use self-hosted models when data must stay in your environment.
Further reading
Custom AI Development vs Off-the-Shelf AI Tools
Off-the-shelf AI tools solve common problems well. Custom AI earns its cost when the value sits in your data, your workflow or your product. Here is how to tell the difference.
5 min read
LLM Agents in Production: Tools, Guardrails and Evaluation
Agents that call tools and take actions are powerful and fragile. The engineering practices that keep them safe, measurable and affordable in production.
5 min read
What an AI Consultancy Should Actually Deliver
An AI consultancy is worth hiring when it leaves you with working software and a team that understands it. What to expect at each stage, and what to be wary of.
5 min read
Let's talk about your project
Send us a short description and we will come back with questions, a rough plan and a team.
Email us