Skip to content
Dipolo AIDipolo AI

Your AI has data.It lacks context.

AI initiatives stall. Copilots give wrong answers. Critical knowledge still lives in people. Dipolo turns what your company knows into AI you can trust.

Services

What we deliver

AI reliability diagnosis

We investigate why AI fails on company data: ambiguous definitions, conflicting sources, and critical context that never made it out of people's heads.

Data context structuring

We turn business rules, entity relationships, operational exceptions, and institutional knowledge into a foundation AI can query and use consistently.

Embedded implementation

We apply the fix in the critical workflow, validate behavior in production, and leave behind a living context that keeps up with the business.

Approach

How we work

We work where the business feels the failure, capturing the context that is currently scattered across people, systems, and operational exceptions.

01

Start with the decision that cannot afford to fail

We enter the workflow where delays, errors, or rework already carry a clear business cost.

02

Capture the context that is not in the data

Definitions, exceptions, and trusted sources are rarely modeled end to end. We make them explicit so AI does not have to guess.

03

Keep context alive

New products, rules, and systems cause data meaning to drift. We build a foundation that can be updated as the business changes.

About

Who solves it

I'm Raphael Ballet. For over 8 years, I've built data and AI systems at Meta, Expedia Group, Loggi, Elo7, and Pipo. In every one of them, the biggest blocker wasn't the model. It was the context the model didn't have.

I built recommendations at Instagram (Meta), drove $10M+ in business value at Expedia Group, and built data platforms at high-growth startups. The same pattern repeated everywhere: companies had data, had models, but the AI had no way to understand what the company's data actually meant.

I founded Dipolo to solve exactly that problem: building the context layer that transforms raw enterprise data into something AI systems can understand and trust.

LinkedIn

Contact

Let's talk

Have an AI initiative that isn't reaching production? An AI tool that can't make sense of the company's own data? That's the right problem for us to talk about.

Send email

or write directly to raphael@dipolo.ai

São Paulo, Brazil