AI & Automation Builds

Nuno leads the build. Today he runs the AI operating system inside a real 8-figure consumer-goods business: 15-plus tools unified, 40-plus custom skills in production, executive briefings written daily and weekly by automations that read across the business. Everything we build externally is informed by what survives in production internally.

Most useful automation is not a single model call. It is a chain: a trigger that recognises the right moment, a knowledge layer that knows what context to pull, a skill that performs the work, and a write-back that updates the system of record. Agentic patterns earn their keep when those steps can be reliably stitched together, audited and changed without breaking.

We build custom AI skills (not just prompts) when the off-the-shelf path is wrong. Sometimes a third-party SaaS is the right answer: cheaper, faster, well supported. Sometimes the workflow is too specific, the data too sensitive, or the integration too brittle, and a custom build is the only thing that actually pays back. We are honest about which is which.

Builds ship in tight increments. The first useful output usually lands within two weeks, with the team able to use it. We test against real cases and edge cases before go-live, and we ship the documentation and training the team needs to actually adopt it. Adoption is a deliverable, not a hope.