Most AI projects that fail do not fail in the code. They fail because nobody agreed on what the system was supposed to change. So every project we take on moves through the same five stages, in the same order.
1. Discovery
One to two weeks. We sit with the people who do the work today and learn the business, the goals and the problems. The output is a short list of places where AI would make a real difference, and an honest note on where it would not.
2. Strategy and design
One to two weeks. We design the architecture, choose the technology and agree a roadmap. This is where we decide what an agent should do on its own, and what must always go to a person.
3. Development
Four to eight weeks. We build in short cycles with regular demos, so the product never drifts away from what was agreed. You see working software early, not a big reveal at the end.
4. Deployment
One to two weeks. Testing, documentation, and hands-on training for the team who will use it. A system nobody knows how to run is not finished.
5. Support and scale
Ongoing. Monitoring, support and steady improvement, so the system keeps earning its place after launch.
If you have a problem you think fits this path, tell us about it. Start with the problem, not the solution.
