Consulting since 2009
Most AI projects are data projects in a better suit.
We help teams find where AI genuinely helps, build the systems that deliver it, and keep the data underneath in good order. We started with the last part, in 2009.
- day 01gjh.discoveryshadow 3 workflows · interview 6 practitioners✓
- day 04gjh.dataprofile source systems · row counts, freshness, null rates✓
- day 09gjh.analysisscore 11 candidates → 2 build · 3 defer · 6 decline✓
- day 14gjh.deliveryrecommendation memo + reference architecture✓
- day 15clientdecide: proceed, defer, or stop — no obligation
What we do
Four practices, one team
Senior people do the work. You will not be handed to a team you have not met.
- 01
Advisory
Where AI is worth the effort, and where it isn't.
Read more → - 02
Building
Assistants, automations, and internal tools that hold up in production.
Read more → - 03
Data foundations
Warehouses, pipelines, and models — the part everyone skips.
Read more → - 04
Staying with it
Monitoring, tuning, and support after launch.
Read more →
How we work
Three commitments we put in writing
- Start small and paid
- A short assessment of one workflow, so you can judge the work before committing to more. Most engagements begin under a month.
- Senior people do the work
- The person in the first meeting is the person writing the code. No handoff to a bench you have not met.
- You own everything
- Code, infrastructure, and documentation, in your accounts. No dependency on us by design.
Industries
Where the constraints do the talking
GJH works across 15 industries. Named case studies are pending client approval.
Partnerships
Platforms we build on
Five partnerships, each earning its place. What matters is what we do with them.
Models
Anthropic
Claude is the default model in our assistant and document work. Partner status gives us early access to capability and safety guidance we pass through to clients.
Lakehouse
Databricks
Our primary platform for lakehouse architecture, pipeline orchestration, and putting governed data next to model workloads.
Warehouse
Snowflake
Where we build warehouse and semantic layers for organisations already standardised on it.
Infrastructure
AWS
Most systems we build run in the client's own AWS account, under their controls and their billing.
Cloud & workspace
Google
Cloud infrastructure and workspace integration for teams whose day runs inside Google.
Insights
Notes from the work
Aug 5, 2026 · 2 min
What the first two weeks of an engagement actually look like
No deck, no workshop, no 'alignment'. Five days of shadowing, a data profile, and a written recommendation you can decline — that is the shape of it.
Jul 30, 2026 · 2 min
An answer is only as good as the lineage behind it
Before you wire a language model to your data, ask whether a number on your dashboard can be traced to the row that produced it. If it cannot, neither can your citations.
Jul 22, 2026 · 2 min
Most failed AI pilots are data failures with better branding
Six pilots that stalled, and what was actually wrong in each. In five of them the model was fine.
Tell us what you're trying to do.
A paragraph is plenty. We will tell you whether it is a job for AI, a job for a pipeline, or not a job at all.