AI consulting services

C-01

We turn a board's AI ambition into a plan that can be funded and built. Leadership sessions and an opportunity map show where the value sits, a feasibility check against your data and systems settles build versus buy, and the work ends in a roadmap with a governance review. The same team writes the business case and the engineering plan, and the gap between those two is where most AI programmes stall.

C-02

Your engineers are already using vendor harnesses such as Codex, Claude Code and Cursor. We put architecture, skills packages, guardrails and CI around them, so the code those tools write reaches production the same way as every other change, and the company is not locked into one vendor's stack.

C-03

We build internal copilots, workflow agents, voice agents and the middleware between them to run against real data every working day. The design work goes into access, permissions, auditability, failure modes and human review, because those decide whether a system survives contact with your operations.

C-04

Our agentic workflows follow one pattern: the agent proposes and a verifier decides. The model does the flexible reasoning, while deterministic rules, schemas, tests and human review decide whether anything is allowed to proceed. The pattern is built for finance, data migration and compliance work, where mostly correct is another way of saying wrong.

C-05

We connect AI to the numbers the business already trusts, through warehouse integrations, semantic-layer work, data contracts, reconciliation and reporting an AI system can read. The test is simple: an answer from the assistant should match the one the finance team would have given, definition for definition.

C-06

We build the middleware, syncs and APIs that put AI inside the tools your teams already use, and we do the unglamorous parts properly. That means idempotent writes, dry-run modes, rollback paths, audit logs, rate-limit handling and daily runs that finish.

C-07

This is a retained senior team for a programme that has the budget and the mandate but nobody to own the technical decisions or build the platform. The team sets the target architecture, makes the vendor and model choices, builds alongside your engineers, runs delivery governance and does the enablement that hands all of it to your own team. It typically runs two to three days a week under one statement of work.

C-08

We place a senior engineer, or a team, inside your programme on a contract from three months, and you direct the work day to day. Every engineer meets the same hiring standard as the rest of 1AYM, and 1AYM holds the cover, so a stream never hangs off one person.

C-09

We make an AI policy enforceable in the system itself. The system checks permissions before it acts, verifier gates sit on the actions that can cause harm, evaluation runs in CI, the gates produce their own audit trail, and data residency is architected in where a region is a requirement. We do this during the platform build, the only point at which it is cheap.