01 / capability
Multi-source conversation ingestion
Exposed as a scoped capability with its own evidence trail, not a hidden setting.
Knowledge & context · Concept
Make the knowledge answerable.
A conversation intelligence and evidence platform that transforms human and AI interactions into structured, searchable organizational knowledge.
01
What it is
Chatlogs is built for AI teams, enterprises, developers, researchers, compliance and knowledge managers.
The problem
Chatlogs replaces scattered chat histories, disconnected transcripts and manual conversation archiving.
The approach
A conversation intelligence and evidence platform that transforms human and AI interactions into structured, searchable organizational knowledge.
The boundary
Work stays inside an explicit scope: named sources, defined permissions, bounded execution, retained evidence.
02
Capabilities
Five contracts the product is specified around. Each one is a boundary as much as a feature.
02 / capability
Message and trace normalization
Exposed as a scoped capability with its own evidence trail, not a hidden setting.
03 / capability
Entity and relationship extraction
Exposed as a scoped capability with its own evidence trail, not a hidden setting.
04 / capability
Provenance and evidence retention
Defined as an explicit contract so operators can review it before it runs.
05 / capability
Knowledge graph, API and MCP access
Defined as an explicit contract so operators can review it before it runs.
03
How it works
The same three steps apply whether a person or an agent is driving.
01
Define the scope
Start from the boundary Chatlogs is allowed to act inside: the workspace, the sources, the budget, the authority.
02
Connect the surfaces
Expose the same capability through the interface a human uses and the interface an agent calls, with one permission model.
03
Act with evidence
Every action leaves a record that can be inspected, replayed and challenged before the next one runs.
Read the specification before you believe the category.
Chatlogs is documented as a concept: requirements, interfaces and evidence expectations. It is not presented as a live service.