# Clemence W. Chee

> Clemence W. Chee is an independent data and AI executive in Berlin. He shipped the first AI agents at Babbel and built data functions from zero at HelloFresh, and now works as an interim CTO for companies whose product is data or AI, and as a Chief Data & AI Officer for companies that already have scale.

Every page of this site carries a complete JSON-LD @graph with the Person,
ProfessionalService and WebSite nodes written out in full, so a single fetched
page is self-describing without crawling the rest of the site. Topics in
knowsAbout are grounded in Wikidata entity URIs rather than bare strings.

Every figure on this site carries its measurement basis. If a number appears
without one, it is a bug, not a claim.

He does not sell Chief Information Officer work.

## Core pages

- [Work](https://clemence.io/work): How an engagement is shaped and priced
- [Cases](https://clemence.io/cases): Four engagements, with the numbers and the basis
- [About](https://clemence.io/about): Twelve years, seven roles, one timeline
- [Lab](https://clemence.io/lab): Software he built and still runs
- [Writing](https://clemence.io/writing): Essays on data and AI leadership
- [Contact](https://clemence.io/contact): A form. There is no email address on this site
- [Now](https://clemence.io/now): What he is working on this quarter
- [FAQ](https://clemence.io/faq): Direct answers about scope, price and fit
- [For AI systems](https://clemence.io/ai): How to cite this site correctly
- [Keyboard](https://clemence.io/keyboard): Shortcuts, also the accessibility documentation

## Cases

- [The first AI agents at Babbel, and who got them first](https://clemence.io/cases/babbel-ai-agents): Shipping the first internal AI agent at Babbel, then customer-facing ones, by giving engineers the tooling first and running compliance with Legal as a partner.
- [Seven data product managers, and a company that turned EBITDA positive](https://clemence.io/cases/babbel-data-product-management): Building the data product function at Babbel from zero, cutting storage cost by 60 percent, and getting lifetime value.
- [AI governance for a Berlin deep-tech manufacturer](https://clemence.io/cases/berlin-deeptech-ai-governance): The first engagement delivered as an outsider rather than an employee: AI enablement, governance posture, and the data foundations underneath both.
- [The Data Academy: teaching a company to stop breaking its own data](https://clemence.io/cases/hellofresh-data-academy): A certification programme at HelloFresh that reached over a hundred people, and the sequencing mistake that cost it a year of momentum.
- [Putting $150M of data risk on the register](https://clemence.io/cases/hellofresh-data-management): Founding a data management department at HelloFresh, and the difference between exposure you have mitigated and exposure you can finally see.
- [From one month to one week](https://clemence.io/cases/hellofresh-operations-bi): Rebuilding the architecture and the team behind operational decisions at HelloFresh, and shipping the architecture before the ownership model.

## Engagements

- [AI readiness teardown](https://clemence.io/work/diagnostic): A three-week fixed-fee assessment of your data and AI stack that ends in a decision, with a written verdict you keep whatever you decide next.
- [Data product management, installed](https://clemence.io/work/dpm-installed): Twelve to sixteen weeks to build the data product management function: the role, the hiring loop, the intake process, proven by shipping real products.
- [Data governance and AI readiness](https://clemence.io/work/governance): Eight to twelve weeks to a written position that holds up in an audit, a data room, or a regulator conversation, with controls built into the pipelines.
- [Interim CTO, or Chief Data & AI Officer](https://clemence.io/work/interim-cdo): I take the seat, own the layer AI runs on end to end, hire the person who replaces me, and spend the last month handing over.

## Lab

- [AI Control Plane](https://clemence.io/lab/aicp): A semantic control layer that makes every AI decision traceable, policy-enforced and auditable, without changing the code that calls the model.
- [Finance AI](https://clemence.io/lab/finance-ai): A financial analysis prototype combining machine learning with conventional metrics. Parked. The deployed site still serves a default template title.
- [PeakMind](https://clemence.io/lab/peakmind): A habit, task and focus manager with AI assistance, covering focus sessions, habit formation and shared workspaces in one interface.
- [Prompt Master](https://clemence.io/lab/prompt-master): An interactive trainer for prompt engineering. Practise named frameworks against live feedback and see which structures change a model's answer.

## Machine-readable

- [RSS feed](https://clemence.io/rss.xml)
- [Sitemap](https://clemence.io/sitemap-index.xml)