AI & Data Advisory
Build to run. Not just to demo.
Methodly implements practical AI workflows and builds the trusted data foundations underneath them. The test of the work is whether it still holds up on an ordinary Tuesday, months after the engagement ends.
What we do
The four practices
The data and AI work a Chief Data and AI Officer is accountable for, delivered as four separate practices. Which one applies depends on where the problem actually sits.
Agentic AI and Workflow Automation
Business processes rebuilt as AI-enabled workflows on the systems already in place, with evaluation, oversight and exception handling designed in.
Data Governance and Modeling
Models that represent how the business actually works, so data is structured around real needs. Ownership, definitions, quality and lineage, so every data asset can be trusted and used.
Data Architecture and Platforms
The technical foundation, from ingestion, pipelines and platforms to networking and access, through to how the data gets consumed.
AI Risk and Controls
Managing and preventing the potentially adverse effects of AI, through a control-by-control review of the AI already running and the AI about to.
Who we work with
Smaller and mid-size businesses come mostly for AI automation, and larger organizations for the data and control work that regulated environments depend on.
What we believe
Production over demos. Business outcomes over technology for its own sake. Human judgment kept where it matters. Control built in rather than added once something goes wrong.
Where to begin
Most work here begins with something small and specific that has been getting pushed to next quarter for a while. That is enough to open with.