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SOT Labs

CUSTOM AI ENGINEERING

Your company's brain, finally searchable

Internal assistants over your docs, SOPs, policies and tribal knowledge — answers with citations, not folklore.

from ₹1L + ₹8K/mo

20%

of the average knowledge worker's week goes to looking for information that already exists somewhere internally.

WHAT IT DOES

Outcomes, not features.

  • One place to ask anything: policies, SOPs, product specs, past proposals
  • Every answer cites its source document — trust through verifiability
  • New staff onboard themselves; veterans stop being human search engines
  • Permission-aware: people only get answers from documents they can access
  • Lives where your team does — Slack, WhatsApp or a web app

HOW IT CONNECTS

Wired into the tools you already run.

An agent that can't write to your systems is a toy. Integration is the product.

Google Drive / SharePointNotion / ConfluenceSlack / WhatsAppYour file server

DELIVERY

Dates we commit to in writing.

  1. week 1

    Corpus & permissions

    Document sources connected with access control mapped.

  2. weeks 2–3

    Build & evaluate

    Retrieval tuned and measured on a test set of real team questions.

  3. week 4

    Rollout

    Team launch with usage analytics and a feedback loop.

STRAIGHT ANSWERS

What buyers ask about this.

Our documents are a mess. Will this still work?

Messy is normal — retrieval handles redundancy and the citation model exposes contradictions so you can fix the source. Don't run a cleanup project first; the assistant will show you what's actually worth cleaning.

Does our data train anyone's model?

No. Retrieval-augmented generation reads your documents at question time; nothing is trained on them. Data stays in your tenancy.

How accurate is it?

We build a test set from your team's real questions and publish the retrieval accuracy before launch. If we can't hit the bar on your corpus, we tell you.

More questions? See pricing or talk to us.

DON'T TAKE OUR WORD FOR IT

Test it on your own docs

Send us three documents and five hard questions — we'll demo retrieval on your material, not a canned dataset.