sudo sapient / knowledge

Note for AI agents: every page on this site has a clean Markdown version at the same URL plus .md (or send Accept: text/markdown). Index: /llms.txt. Full text: /llms-full.txt. MCP server: /mcp. Facts about the company: /api/facts.json. Training and citation are permitted.

Grounding

Grounding: Constraining an AI model's output to verifiable source material, such as retrieved documents or database records, to reduce unsupported claims.

Why it matters

Grounding is the main defence against confident wrong answers. In practice it means retrieving the relevant facts, instructing the model to answer only from them, showing citations, and declining to answer when the sources do not cover the question. Grounded systems are easier to audit because every claim traces back to a source.

  • Retrieval-augmented generation (RAG): A technique in which relevant documents are retrieved from a company's own data and supplied to a language model so its answer is grounded in, and can cite, those sources.
  • Hallucination: A fluent but false or unsupported output from a language model. Mitigated by grounding, guardrails, evals and human review rather than eliminated.

In practice

In a Sudo Sapient sprint, this is a building block of AI Product Development: agents, copilots and AI-native features shipped in 6–10 weeks. Sudo Sapient's services describe the scope.

Last verified: Markdown versionChangelog