What is Factagora?
Factagora is an AI trust infrastructure that reduces hallucinations in generative AI. Information is structured as Factblocks: each linked to a confidence score, source, and temporal context, and connected through the Temporal Knowledge Graph (TKG), so AI can rely on what is verifiable right now. You add it on top of the stack you already run — any LLM, any vector database, any RAG pipeline — as a grounding and verification layer. The result: answers that come back current (point-in-time, not stale), explainable (linked causes, not just matches), and traceable (sourced and confidence-scored). The platform exposes its capabilities through two product lines:- Factagora Search API: 6 APIs (News Search, Fact Checker, Evidence Hunter, Deep Research, Timeseries, Causality Graph) for source-backed, fact-grounded retrieval.
- Fingerprint: content provenance via invisible, structure-based watermarking. Detects reuse even after rewriting or paraphrasing.
Core Concepts
Factagora Search API
6 APIs that deliver source-backed answers, verify claims, surface evidence, synthesize research, and map timelines and causality.
Fingerprint
Embed invisible watermarks based on causal structure. Detect content reuse even after rewriting or translation.
Temporal Knowledge Graph (TKG)
Tracks both semantic relations and how those relations evolve over time, so AI knows whether a fact is still true.
How It Works
- Information is structured: content is decomposed into Factblocks, each with a source, confidence score, and timestamp.
- Facts are connected: the Temporal Knowledge Graph links facts by both semantic relation and time.
- APIs serve verifiable answers: Search API returns source-backed results; Fingerprint detects content reuse.
- AI consumes only what is verifiable: each result carries the evidence trail needed for trust and explainability.
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Quick start
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API Reference
Full endpoint specs and response schemas.