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Fiescrow

AI Engineering

We build AI into products that already do something useful. Support assistants that read your own knowledge base. Agents that draft replies for a human to approve. Retrieval that returns the right record and shows you where it came from. We have shipped all three in our own products, so we know where they break.

  • Python
  • Vercel AI SDK
  • OpenAI
  • Anthropic
  • pgvector

What this covers

The parts we actually do

Support assistants

Grounded in your documentation and your data, with a handoff to a person when it should not answer.

Agents with review steps

Drafting replies and actions that a human confirms before anything is sent.

Retrieval

Search over your own content that returns sources, so answers can be checked.

Evaluation

Test sets and scoring, so you find out a change made things worse before your users do.

What you get

Deliverables

Named up front so there is no argument about scope at the end.

  • Working AI feature inside your product
  • Evaluation suite and baseline scores
  • Cost and latency budget
  • Fallback behaviour when the model is wrong or unavailable

Proof

Where we have done this

Our own products, running in production. Open them and judge for yourself.

Business operations

Bustera

Live

One platform for selling products, booking services, running events and taking payments, in whichever currency your customers use.

Business types
5
Starter plan
₦5,000/mo
Currencies
Multi
Learning

Selah

Live

A daily learning app across five subjects, with streaks, leagues and quests doing the work that willpower usually has to.

Academies
5
Bible versions
6
Free daily energy
25

Need ai engineering?

Tell us what the problem looks like from your side. We will tell you what it would take to fix it.

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