We pay for Claude or ChatGPT.
It became a chat box for writing text or code, with no automation and no link to the systems. The gain shows up in no result at all.
OFFER > AN ENGINEER INSIDE YOUR TEAM
FORWARD DEPLOYED ENGINEER.
Make AI deliver value: a TDIA engineer joins your team with a defined goal and puts AI into production in your systems.
THE PROBLEM
THE IDEA WORKED. PRODUCTION DID NOT.
It worked in the demo.
With real data it does not: high cost, slow answers, errors.
Someone built it on Lovable or Replit.
It served the first users. Today it is hard to maintain or scale.
While nobody solves it, the licenses and the stalled project keep costing.
WHERE IT APPLIES
support and documents spreadsheets and rework data analysis delivery pipeline SEE THE PIPELINE >HOW IT WORKS
ONE GOAL THROUGH TO DELIVERY.
TDIA engineer
assesses, builds and integrates
proposes new paths and solutions in your repository, in your accounts
your team
prioritizes, validates and approves
plan before code, independent review and release only with your sign off
EXPERIENCE FROM OUR OWN PROJECT
monitore.ai
monitore.ai is built and maintained the same way an engineer would work inside your company.
millions of CNPJs
cross referenced every day, from multiple sources
hours, not weeks
for a new database to reach monitore.ai
FOR COMPANIES
START WITH WHAT IS STUCK TODAY.
Tell us what was already tried, bought or built, and which result was not reached.
Prefer to write? Send it to contato@tdia.com.br. Still at the start? Take the initial assessment. Want to understand the role? What is a Forward Deployed Engineer.
QUESTIONS
BEFORE YOU BOOK.
Is this developer staffing?
No. The engineer comes in with an agreed goal and owns it.
We already pay for Claude or ChatGPT. Does that keep being used?
Yes. The work connects what you already pay for to the real systems.
We already tried something and it never took off. Can that be a starting point?
Yes. The engineer assesses what to keep and what to rebuild.
Do our code and our data leave the company?
No. Nothing leaves the company, including the AI services, agreed with your team before the start.
How do we measure the result?
The goal becomes an agreed metric, set in the first conversation and tracked every cycle.
What is left at the end?
Support and further work are agreed separately.