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Dedicated teams

AI engineers who have had to operate the model.

Add a senior engineer to an existing product team for a defined period. The work can include AI evaluation, monitoring, cost controls, permissions, and human-review workflows.

What you get.

  • A named engineer who has shipped AI with evaluation attached
  • Help writing down what the model is allowed to decide
  • Review on prompts, tools, and the paths that spend money
  • A handoff your team can keep running

How it works.

01

Name the decision the model would make

If that cannot be written in a page, we are not ready to embed anyone.

02

Sit in your repo

Evaluation, logging, and approval gates get added where they are missing. Demo-quality chat is not the deliverable.

03

Leave the measurements behind

Your team should be able to see quality and cost after we go, without asking us to read the graphs.

Fit.

These criteria help determine whether the engagement model matches your requirements.

This is a fit when

  • A feature that demos well and nobody trusts
  • A team that can keep the product running and needs help on the model path
  • Work where being wrong is expensive

A poor fit when

  • Projects where AI is the requirement and the problem comes later
  • A request to fine-tune a foundation model from scratch
  • A bench of prompt engineers billed by the hour

Products we run.

LobeStack drafts with a model and waits for a person. Averil reads a career against a market and refuses to mass-apply. Those are the habits an embedded AI engineer would bring.

LobeStack

Live

Models draft, a person approves, rejected posts change the next batch. Live.

Write-up

Averil

Live

A market read in plain language, no vanity score. Live.

Write-up

Questions.

You build with AI. Is the code safe?

We use AI-assisted development tools where they are useful, but code remains subject to engineering review and testing. Access control, data separation, dependencies, and database changes are reviewed according to the risks of the system.

Do you only build AI products?

No. We also build web and mobile products, integrations, internal tools, and platform modernization work. AI is recommended only when it is suitable for the use case and operating requirements.

Can you just add engineers to our team?

Yes, for focused requirements where senior engineers can join an existing product team. We are not structured for large-volume staffing or an interchangeable contractor bench.

Open

Add engineering capacity.

We aim to reply within two working days. Email info@techsity.comif you would rather provide project details directly.

Add engineering capacity