Keep evidence visible.
A recommendation should have a basis that a reviewer can examine.
The platform
Make meaning actionable.
BRECOG is being developed as a cognitive intelligence layer for conversational AI. The goal is to help software teams use context and evidence to inform what happens next.
Where it fits
From conversation
to a considered response.
Your application brings the conversation and relevant context. An evaluation explores whether BRECOG can improve the interpretation and next-step guidance for a defined workflow.
External integration details and supported interfaces are being prepared. Compatibility is a question to establish during scoping.
- 01
Your application
Conversation inputs and relevant background.
- 02
Context and evidence
What is supported, what is uncertain, and which interpretations remain plausible.
- 03
The next response
A candidate recommendation or clarifying question to evaluate.
Design principles
Clarity at every step.
Leave room for uncertainty.
Several interpretations can fit the same words. Further context may change the right response.
Measure the difference.
Compare against the existing approach, including delivery effort and operational cost.
Today and ahead
Build carefully.
Learn deliberately.
Cognitive Intelligence
Our current focus is context and evidence for better decisions in bounded conversational use cases.
Adaptive Intelligence
Our longer-term direction is improvement through evaluated feedback. Availability and performance will be established through development and testing.
Read about readiness