Every answer can be traced, checked, or refused, because Bast grounds AI in your approved knowledge and source material.
Selected outcomes
DVC case study
Lead feature on DVC's blog
Every answer traces back to its context, source page, version, and pipeline. One of the sexiest use cases and best uses of AI, deliver the next step in the procedure the medic is trained on to reduce cognitive load and provide an audit trail for the medic back at the FOB.
Read the DVC feature →Maryville University
$1.2M saved in the first semester
Social learning companions kept students engaged — a scalable, explainable path to support.
Compute control
70–85% fewer tokens vs. standard RAG
Bast controls exactly what reaches the model, so it's deterministic and you own every input — then delivers each answer the way people need it: 8th-grade English, Vietnamese, or an analogy.
The shift
Bast sits between your knowledge and the model's output. Before any answer ships, it checks scope, pulls only approved sources, and refuses when nothing supports a reply.
Proof before output
Supported question
The model sees only what passed the checks. Answers are written for the person asking, grounded in your own sources.
Unsupported question
If nothing supports an answer, Bast refuses before the model guesses.
Institutional trace
See the sources, scores, and path behind every answer. Users get clarity; you get accountability.
What you deploy
Modular infrastructure. Run the whole stack or just the layers you need — hosted, private cloud, or on premises.
AI infrastructure
Kubernetes microservices that fit your operating and compliance needs.
Data management
Versioned storage and ontology-aware language understanding, built in.
Orchestration
Route each request to the right behavior and keep improving from approved knowledge.
Application
Interfaces that put governed answers in front of the people who need them.
How it's built
Data pipeline
Turn raw source material into a knowledge base the system can reason over.
Natural-language understanding
Language is read against your own terms, not a generic guess.
Knowledge graphs
Answers follow explicit relationships, so the route stays inspectable.
Model Context Protocol
Built on MCP, so the right context reaches the model and nothing else does.
Hybrid intelligence
Model fluency plus symbolic control, for answers that hold up.
Explainable UI layer
Responses people can read, check, and act on with confidence.
Watch the control layer work
See Bast from the admin console, knowledge manager, and end-user view: approved knowledge sets the boundary, and unsupported questions stop before a guess can ship.
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Lucid Therapeutics
From admin setup to end-user experience: governed knowledge, CAT building, and production analytics.
Health and medicine
A healthcare walkthrough of assistant configuration, source visibility, reasoning traces, and expert refinement.
Healthcare ontology
The same patient knowledge, shaped for patients, caregivers, and providers.
Built for places where answers matter
Source, ontology, and routing stay tied to the response.
The trust layer meets your operating constraints.
Relevant knowledge is picked before generation, cutting tokens and noise.
Bast records every blocked, missing, or out-of-scope answer.
Your control
Talk to a human
Ask us anything. A real person texts back, usually same day.
On a computer? Text +1 303-717-6099.
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Follow the build
We build in the open. Follow along for demos, case studies, and what we're learning about explainable AI.