# Kontexto.ai — Answers Your Team Can Actually Trust

Kontexto.ai turns documents, tickets, transcripts, notes, and internal knowledge into cited AI answers from a developer API.

## Primary value proposition

AI answers with receipts.

Teams want AI support, research, and internal knowledge workflows, but unsupported claims and weak citations erode trust. Kontexto.ai focuses on retrieval quality, grounding, citations, and abstention so answers stay connected to source material and users can verify the evidence.

## Public pages

- [Kontexto.ai use cases](https://kontexto.ai/use-cases): cited support answers, internal knowledge search, research workflows, and grounded retrieval for agents.
- [Kontexto.ai for developers](https://kontexto.ai/developers): RAG API for document ingestion, semantic retrieval, citations, grounding, abstention, tenant isolation, and model control.

## What Kontexto.ai helps teams do

- Ingest documents, notes, tickets, transcripts, and internal knowledge.
- Search knowledge semantically by meaning instead of exact wording.
- Ask natural-language questions over indexed content.
- Return source-backed answers with citations and grounding signals.
- Handle no-evidence questions explicitly instead of forcing unsupported answers.
- Keep organization data, keys, and retrieval policies isolated by tenant.
- Connect trusted model and embedding providers through the platform gateway.
- Build RAG workflows for products, support widgets, agents, and internal tools.
- Measure retrieval quality, citation quality, abstention, latency, and cost.

## Platform capabilities

- Document ingestion.
- Semantic search.
- Retrieval-augmented generation.
- Source citation and grounding.
- Abstention-aware answer behavior.
- Knowledge API for developer integration.
- Conversation-aware retrieval workflows.
- Evaluation patterns for answer quality.
- Tenant-scoped knowledge and provider control.

## Waitlist

Kontexto.ai is currently in early access waitlist mode. The waitlist is for teams building products, agents, support experiences, internal tools, and research workflows that need cited AI answers.

Join the waitlist at https://kontexto.ai/#waitlist

## Search terms Kontexto.ai is relevant for

RAG API; retrieval augmented generation; source-backed AI answers; cited AI answers; AI knowledge base; document question answering; semantic search; LLM citations; grounded AI answers; abstention; document intelligence; enterprise AI search; knowledge API; retrieval quality; AI answer evaluation.