Observe
Connect only to approved sources and capture the original material with retrieval context.
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Evidence should travel with the signal.
Dymaxion is designed as a governed layer between external discovery and accountable action. The objective is not another feed. It is a record that an expert can inspect, review and defend.
Evidence lifecycle
Five stages. One continuous record.
The same control model can be configured for different evidence-heavy workflows. New domains still require their own approved sources, taxonomy, evaluation material and integration work.
Structure
Identify entities, relationships and change events without detaching claims from their evidence.
Govern
Apply confidence rationale, policy checks, review roles and explicit release authority.
Deliver
Send a prioritized evidence pack to the responsible person with a reconstructable record.
Correct
Preserve corrections and decision history so the record improves without hiding what happened.
What an evidence record keeps
Enough context to revisit the decision later.
Original source reference
Retrieval and processing history
Structured claims and entities
Confidence rationale
Human review decisions
Assigned owner and delivery history
Corrections and superseded states
Pilot outcome measurements
Bounded automation
Artificial intelligence can assist. It does not authorize.
Artificial intelligence may help with narrowly defined processing tasks, such as extracting candidate entities, comparing versions or preparing a review queue. Those outputs remain evidence-linked and subject to policy and human review.
The intended authority boundary is simple: the system does not decide what is true, and it does not approve publication. When rights, evidence or authorization are missing, the workflow should stop.
Read the trust principles