Atomic
Truth.
We don't just store documents; we distill them. WUF.AI extracts unstructured text into a structured graph of canonical facts, each immutably linked to its source evidence.
The Fact Model
From chaos to structure.
Entity Resolution
We identify the core subjects. "Acme Corp," "Acme Inc," and "Acme" are all mapped to a single Canonical Entity ID.
Relation Extraction
We extract the relationship and value. For example: Entity (Enterprise Plan) → Relation (has_price) → Value ($499).
Attribute Normalization
We normalize metadata. "Next Tuesday," "Q3," and "10/12/2023" are converted into standard ISO date ranges for accurate querying.
Extraction Engine
Unstructured to Structured
Temporal Facts
Truth is rarely static. What was true yesterday might not be true today.
WUF.AI's fact model includes native support for temporal validity. Facts can have `valid_from` and `valid_until` attributes, allowing the Knowledge Graph to answer questions about the past, present, and future states of your business.
Irrefutable Provenance
A fact without evidence is just a hallucination. In WUF.AI, every single extracted fact is cryptographically linked to the exact byte range in the source document.
- AuditabilityWhen the engine answers a question or generates a report, it provides exact citations back to the original documents.
- Confidence ScoringEvery extraction is scored. Low-confidence extractions can be flagged for human review before entering the canonical graph.
Conflict Resolution
When two documents disagree, WUF.AI doesn't just guess. It flags the contradiction.
Our conflict engine uses source authority heuristics (e.g., Salesforce > Notion) and timestamps to propose the correct canonical fact, requiring human approval for high-risk changes.
Continuous Ingestion
The Knowledge Graph is never stale. WUF.AI continuously monitors your connected data sources for changes, automatically extracting new facts and deprecating old ones.
- Real-Time SyncConnect via OAuth to Google Drive, Microsoft 365, Slack, and Notion. Changes are detected and processed within minutes.
- Delta ProcessingWe only process what changed. Efficient hashing algorithms ensure we don't waste compute re-analyzing static documents.
The Enterprise Knowledge Graph
Millions of atomic facts, continuously updated, instantly queryable, and cryptographically verified.
Knowledge Graph FAQ
How does WUF.AI handle conflicting information during ingestion?
When conflicting facts are extracted, WUF.AI flags them in the Conflict Resolution queue. It uses source authority heuristics (e.g., a signed contract outranks a Slack message) and timestamps to propose the correct canonical fact, requiring human approval for critical changes.
Can I trace a fact back to its original source?
Yes. Every fact in the Knowledge Graph maintains irrefutable provenance. It is cryptographically linked to the exact byte range in the source document, providing perfect auditability.
How does the Knowledge Graph handle time-sensitive data?
WUF.AI's fact model natively supports temporal validity. Facts include `valid_from` and `valid_until` attributes, allowing the system to understand past, present, and future states, preventing false conflicts between historical and current data.
Establish The Truth.
Turn your scattered documents into a structured, verifiable knowledge graph.