Nia indexes code, documents, PDFs, and datasets into a unified retrieval API, enabling AI agents to search with graph traversal, reasoning, and source citations.
Nia is an index and search layer designed specifically for AI agents, providing a unified retrieval interface across diverse data sources. It allows teams to index codebases, documentation, PDFs, datasets, and other unstructured content, then expose that knowledge to any agent through a single, consistent API. The primary purpose of Nia is to make AI systems more reliable and context-aware by grounding their outputs in searchable, navigable, and verifiable information.
At its core, Nia offers advanced retrieval with traversal, reasoning, and citation capabilities. Agents can not only fetch relevant chunks of information, but also follow links and structure within data (such as code dependencies, document hierarchies, or relational references) to build richer context. Nia’s reasoning layer helps agents interpret and connect retrieved pieces, improving multi-step workflows and complex question answering. Citation support ensures that every answer can be traced back to specific sources, enabling auditing, debugging, and human review.
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