012 weeks
AI Value Discovery
- Two weeks on site with your team
- We map the priority workflows and price each opportunity
- A prioritized list and a value case, before anything is built
Reimagine the future of work
We find where AI can create real value in your business, build the solution and stay until it works in production.
Today your best people lose hours copying documents, retyping data and checking spreadsheets. It doesn't have to be this way.
Our goal is to recover the talent that companies lose to manual work.
Built by people who have worked at these companies
How we work: from the first week on site with your team to an agent running every day.
Extract: We spend the first weeks on site with your team.
- Work on site, with your team
- Map the priority workflows
- Find what holds it back
Trace: We put a number on each opportunity.
- Put a yearly dollar value on each opportunity
- Prioritize by impact and ease
- A quantified value case
Build: We ship it into production.
- Agents, automations, internal tools
- Plugged into your CRM, WhatsApp and Teams
- Runs in your environment
Scale: Your team runs it, tunes it and finds the next one.
- Train your team
- Guardrails and policies for every team
- Measure what changed, in dollars and hours
09:00
10:00
11:00
12:00
13:00
Total
35 min
ERP
15 min
50 min
Excel
55 min
30 min
01 Observed work
One specialist, one morning, five systems. Almost all of it is manual work. The darker blocks are one document.
Request arrives
Find past ones
Excel
Retype the data
Ask a colleague
Send to sign
× thousands a year
02 The repetition, priced
built first →
$1milliona year
in opportunities, found and priced in a two-week discovery
Every opportunity we found, ranked by value. The top one is this document.
01 Triggers
A new request, by e-mail or WhatsApp, wakes the agent.
02 Agent
The team's own rules, written down as instructions.
03 Knowledge
Several thousand of the client's past documents. Every answer cites its source.
04 Model gateway
Every model call is metered, behind a kill switch.
05 Approval
A specialist reviews the draft and signs. Nothing goes out alone.
06 Tools
Files the signed document where the team already works.
Durable run
Every step is logged, so a restart picks up where it left off.
Your cloud ·
Security & compliance
Everything runs inside your own cloud or tenant. Your data doesn't leave it.
Inside AgentLayer
DOC 0418 Signed
DOC 0419 Signed
DOC 0420 In review
DOC 0421 Signed
DOC 0422 Drafting
Documents · today
Review · 1 waiting
DOC 0420 has 2 exclusions flagged. The specialist decides.
Run log
This first automation
$14k/yr
Saves each person about an hour a day
1h · Mon–Fri
05 Running
One specialist, one morning, five systems. Almost all of it is manual work.
Every opportunity we found, ranked by value. The top one was a document the team still wrote by hand.
Inside AgentLayer: a request comes in, the agent drafts from thousands of past documents and a specialist reviews and signs, all inside your own cloud.
This first automation saves each person about an hour a day, worth $14k a year.
A Brazilian healthcare company, from kickoff to running in daily work.
2 weeks
from kickoff to a working proof of concept, not a slide about one
$14k/yr
from the first automation, now live and saving each person about an hour a day
$1M/yr
of opportunity found and priced, most of it in documents still made by hand
Four questions: where to start, how to build, how to scale, how to get the team ready.
02Build to production
AI Delivery
- Agents, automations and internal tools that solve the problem
- Integrated with your data and systems
- Done only when it runs in production and we have measured what changed
03Continuous
Agentic Transformation
- Guardrails, policies, training and a knowledge base
- AI becomes part of how the company runs, not a pile of pilots
- A continuous engagement, not a project
04For every team
AI Literacy
- Hands-on sessions for leadership and frontline teams, on real work
- What AI does well, where it fails and how to use it safely
- Your team leaves using AI every day, not just knowing about it
Common questions: what people ask us before we start.
hello@extrace.aiWhat does an applied AI company actually do?
We find where AI creates measurable economic value in how a company operates today, put a number on each opportunity, build the solution (agents, automations, internal tools) into the systems the company runs on and stay until it works in production. The capability stays with the client's team when we leave. The difference from a traditional consultancy is that we build; the difference from a software agency is that we start from the business case, not from a specification.
What kind of company is a good fit for Extrace?
Mid-sized and large Brazilian companies, typically owner-led and often backed by a private equity fund, where AI has reached the executive layer but not the front line: leadership uses ChatGPT, the teams still run on spreadsheets and WhatsApp, and anything built internally does not scale for lack of security, integration and access control. We are not a fit for a company that wants a slide deck with no build, or for pure staff augmentation.
Which systems do you integrate AI with?
The ones the company uses today: the CRM and ERP, WhatsApp and Teams, email, spreadsheets, documents and internal databases. We do not ask a client to replace its stack; we build into it, with proper access control, so what we ship can run in production and be maintained by the client's team.
How do you handle our data and security?
We sign an NDA before the discovery starts. What we build runs in your own cloud or tenant, so your data does not leave it, and we use the models through APIs under enterprise terms that rule out training on your data. Access is set by role, every step the agent takes is logged, and a person approves before anything goes out. We work within the LGPD, sign a DPA when you ask for one and delete your data from our environments when the engagement ends.
How do we start?
Write to hello@extrace.ai or use the form on our contact page. After a first conversation, we'll come back with where we'd start and what a discovery would cover.
Tell us where the hours go. We'll come back with a first step.
The first conversation is about your business, not about AI.