How we work

From diagnosis to value in production, in rounds with clear criteria.

It starts with a 2-week Assessment. It ends, in the first round, with a project that extracts value from day zero.

Everything starts with the 2-week Assessment.

What we do

Capability diagnosis

Sessions with the people who live the operation and a technical read of your systems. You get a diagnosis of data, systems and teams, and a map of pain points prioritized by impact.

What you receive

Assessment deliverables

  • Map of capabilities and gaps
  • Pain points prioritized, with a value read
  • Design of the first project, chosen to extract value from day zero, with scope, success criteria and sources
  • A plan of workshops and mentoring for the team’s gaps
What we ask of you

Three commitments

  • Time with the right people, those who live the operation
  • Read access to the essential systems
  • One internal owner for the decision
If the diagnosis shows you do not need Entity yet, the Assessment tells you that too.

You keep the plan of what to fix first. It is yours, whatever you decide next.

Build journey

01/ 05
Diagnosis
Understand
Stage 01 · what happens

We map where knowledge is fragmented and where the layer creates value first. Sessions with the people who live the operation: systems, documents, conversations and the questions no one can answer today.

MilestonePriority use case defined, with success criteria.
Build journey · 01 / 05

Non-negotiable rules.

01

Criteria before the test

Closed scope and success criteria defined before any proof. What counts as success is decided on paper, not midway.

02

Value in every round

Every round delivers measurable value. Never “platform first, value later”.

03

Your team in charge

Workshops and mentoring so your team runs the layer. We build autonomy, not dependency.

04

Everything with a source

Source and auditability in everything the AI states. No exceptions.

The questions your technical team will ask.

Where does the data live?

In your cloud. BYOC by design: the platform is hosted on your cloud infrastructure, and the language models run inside it. We inherit the permissions that already exist in your systems, and they apply to people and to agents on every query. The audit trail is recorded in your account. Your data trains no model of ours or anyone else’s.

Which AI models do you use?

The ones that make sense for your case: models are pluggable via MCP and inference happens inside your perimeter, on a managed service in your account or on dedicated GPUs, depending on scale, budget and requirements. Switching vendors does not reopen the project: the graph, the permissions and the audit trail do not depend on which model answers.

We already have a data lake. Where do we start?

From what you already have. The Assessment diagnoses what to reuse and what is missing. And if you do not have a data lake, you do not need to solve that before calling us: we build it. The data foundation is our service, and it comes in wherever it is missing.

How long until first value?

The Assessment takes 2 weeks. In the weeks that follow, we model and connect the defined slice and run the proof of value with a closed scope and success criteria defined before we start.

What about LGPD?

Governance from day zero: purpose defined at the foundation, role-governed access and an audit trail. Compliance takes part in the design — it does not receive a finished system.

Book the call that starts the Assessment.

Book 30 minutes

with the people who build.

A founder joins the call. You bring a real problem from your operation and leave with an honest read on where AI creates value. If we are not the right fit, we say that too.

The calendar opens right away. You pick the time and get the invite by email.

If you would rather write before booking, the email is contato@entitylabs.com.br.

São Paulo · BrazilBrasília time (GMT-3)

What fits in 30 minutes

  1. You tell us which decision is stuck in your operation today.
  2. We show the layer applied to a case like yours.
  3. We tell you what can be done with the data you already have. And what cannot.
  4. If it makes sense, you leave with a written scope — timeline and success criteria included.