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AI Engineering

Summarization, classification, intelligent search, and document chat built into your content platform. Features your users keep after the novelty wears off.

We wire AI into the platform itself: enrichment at ingestion, embeddings behind search, assistants inside the UI your users already know. It runs against your real content model and your real permissions, and we measure whether it saves time before we call it done.

Your challenges

What brings teams to us

Search that can't find the document

The content is in there. Twenty years of it. Nobody can surface the right version when it matters.

Metadata nobody fills in

Tagging is manual, so it doesn't happen, so every downstream system starves.

Bolt-on AI that ignores permissions

Generic tools answer from documents the user should never see. That's not a feature, it's an incident.

Our approach

How we work it

Built into the platform

Enrichment, classification, and summarization wired into ingestion and workflow, not a separate tool beside them.

Search that understands

Embeddings and hybrid retrieval tuned to your taxonomy, so people find documents they couldn't before.

Permissions first

Every answer respects the access controls your platform already enforces.

Measured

Time saved and adoption, tracked from the first week.

Weeks

From kickoff to first production feature

2

Enterprises running our AI features in production

100%

Of answers respect existing permissions, by design

Deliverables

What you walk away with

  • AI-powered search with embeddings and hybrid retrieval
  • Document intelligence: classification, summarization, extraction at ingest
  • Assistants and document chat grounded in your repository
  • Evaluation reports showing measured time savings

Need help with AI Engineering?

Tell us what you're struggling with, and we'll tell you how we can help you.

Talk to us