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LLM

AI solutions

A language model is useful when it answers from your data instead of guessing. We build assistants grounded in your documents and procedures, with a source link on every answer and a clear line where the assistant must say it does not know.

Stack

  • Claude API
  • OpenAI API
  • pgvector
  • LangChain
  • Python

What you get

  • Sourced answers

    Every answer points at the document it came from.

  • Assistant boundaries

    Defined topics beyond which the assistant refers to a person.

  • Cost control

    Limits and usage tracking so the bill holds no surprises.

  • Quality checks

    A test set of questions we check every change against.

How it runs

  1. 01

    Data

    We collect the documents and clean them into something usable.

    1 week
  2. 02

    Prototype

    We run a narrow version and check how accurate the answers are.

    1–2 weeks
  3. 03

    Rollout

    We connect the assistant to the channel your people already use.

    2–3 weeks
  4. 04

    Oversight

    We review conversations and fix the places where answers are weak.

    ongoing

Tell us what you want to build

Write a few sentences about the project. We reply within one business day, and if we are not the right people for it we will say so and point you somewhere better.