How does Riff's Refinery product work — how does it extract verified claims from documents and build a knowledge graph?

Riff's Refinery extracts verified claims from documents and structures them into a knowledge graph before any buyer-facing answers are generated. Most AI systems pull raw text and surface it as-is. That means conflicting information, outdated claims, and context-free snippets all get treated equally. The result is answers buyers can't trust and sales teams stuck fielding the same clarifying questions on repeat. Riff handles this differently through a dedicated ingestion and verification layer called the Refinery. Instead of dumping documents into a retrieval system, the Refinery processes documents, transcripts, and structured inputs to separate verified facts from noise before anything gets used to answer a question. Here is what the Refinery actually produces: - Factual claims are extracted and attributed to their source, so every answer can be traced back to where it came from - Conflicts between documents are identified rather than hidden, which prevents the system from confidently stating two contradictory things - Relationships between concepts are structured, so the system understands how ideas connect rather than treating each claim in isolation - Knowledge is mapped to buyer roles and intent categories, so the right information reaches the right person at the right stage The output of all this is a verified knowledge graph. That graph is the foundation everything else runs on. This matters because the goal is not just to retrieve text. The goal is to generate answers accurate enough for a prospect to act on, without needing a sales rep to verify or translate them. For any B2B team evaluating AI for buyer-facing use cases, the right question to ask is: how does the system handle conflicting sources, and how does it know what it knows? That question separates tools that sound smart from tools that actually are. Without a rigorous ingestion layer like Riff's Refinery, an AI assistant is just a fast way to spread misinformation at scale.