Fact-checking where
conversations happen.
A source-backed AI agent that can receive a claim in context, assemble relevant evidence, and return a reviewable record without presenting automation as final authority.
Meet the claim where it appears.
The agent reduces the distance between a questionable claim and the evidence needed to examine it. It is designed for conversation surfaces and monitored workflows, including X, where a mention can become a structured fact-checking request.
Live demo: experience the agent on X via @0xProvenance. X is one live implementation; the agent can also operate across other platforms and defined organizational workflows.
Fast enough for the conversation. Traceable enough for review.
The agent identifies the checkable question, searches for relevant sources, and produces a linked record that keeps evidence and reasoning available beyond the original exchange.
It supports human judgment rather than replacing it. Developing events, limited sources, conflicting accounts, and uncertainty remain visible instead of being compressed into false confidence.
Request in context
Bring a claim from the conversation rather than forcing people into a separate research workflow before they can ask whether it holds up.
Evidence-based results
The response is built around relevant sources and a review record, not an unsupported answer detached from where its evidence came from.
Human and AI validation
Automation can accelerate collection and synthesis. Human review, domain expertise, and accountable policies remain essential where the stakes require them.
Enterprise-ready workflows
The same agent pattern can support defined streams, dashboards, APIs, and review queues for organizations monitoring high-volume information.
Start with where claims reach your team.
Tell us about the conversation surface, review policy, and evidence requirements that matter to your organization.
Discuss the AI Agent