Problems we fix

AI????

AI where it actually removes work.

Most AI projects fail because they start from the technology. We start from the tasks eating your week, pick the two or three where a model genuinely helps, and wire them in with guardrails so the output can be trusted.

Sounds familiar?

  • You bought AI features nobody on the team uses.
  • Someone is pasting company data into a chatbot.
  • An automation confidently produces wrong answers.
  • You suspect there's a use case but can't tell which.

How we fix it.

Every step runs through the Ticket Portal — status, owner, logs, no mystery.

  1. 01

    Find the repetitive work.

    We audit where time goes and score tasks on how well a model can actually handle them.

  2. 02

    Pick two or three.

    Narrow, high-volume, checkable tasks first. No company-wide assistant nobody asked for.

  3. 03

    Wire it with guardrails.

    Grounded on your own data, with review steps, logging, and limits on what it can do alone.

  4. 04

    Keep it honest.

    We check outputs over time so quality drift gets caught before a client does.

What you end up with

A couple of boring, expensive tasks quietly handled — with a record of what the system did and why.

Smithers

Got something
long and annoying?

Send it over. We scope it, ticket it, and get it off your desk.

Erico Di Teodoro
Lead Strategist