Ask your company anything.Get answers with receipts.
The enterprise AI platform for your own data: cited answers, tool-using agents, and visual workflow automation — connect 24+ sources, keep everything behind your firewall, and trace every answer from the exact passage to the permission that allowed it.
Apache-2.0 · runs anywhere, from a laptop to an air-gapped cluster
your sources→hybrid retrieval→cited answer
01Capabilities
Serious retrieval, end to end.
Everything between a raw document and a trustworthy answer — built in, not bolted on.
Hybrid retrieval, engineered from scratch
Lexical BM25 written from first principles, dense semantic vectors, reciprocal-rank fusion and a reranking stage — so the right passage wins whether your people search in keywords or in questions.
keyword
semantic
⇒
fused + reranked
Permissions enforced in the index
Access control is evaluated inside every vector and keyword query — never post-filtered, never left to a prompt. What a user can't read can't be retrieved.
Grounded answers that know when to stop
Every claim carries a citation. Anti-hallucination modes, a faithfulness self-check, and honest abstention when the corpus doesn't contain the answer.
24+ connectors, kept in sync
SharePoint, Confluence, Jira, Slack, GitHub, Google Drive, S3, Azure Blob, GCS, SQL databases and more — on scheduled sync with resumable backfills.
SharePointConfluenceJiraSlackGitHubGoogle DriveS3SQL+15 more
Multimodal by default
PDFs — including scanned ones via OCR — Office files, images, audio, and YouTube videos: paste a link and the transcript lands in the index with timestamps, so answers cite the exact moment in the video.
Bring any model
Claude, any OpenAI-compatible endpoint, vLLM or Ollama. Or skip the setup: paid plans bundle ERAG-hosted models.
Every query, traceable
A per-query trace shows retrieval scores, fusion, reranking and the final prompt — exactly why every answer happened.
Built-in eval harness
Golden questions, LLM-judge scoring and concrete tuning recommendations, so retrieval quality is measured — not assumed.
Governance, out of the box
Retention policies, right-to-be-forgotten, PII redaction, audit export to your SIEM, and SCIM user provisioning.
An architecture documented to 100 TB
Deduplication, vector quantization, sharded indexes and distributed ingestion keep costs flat as the corpus grows.
02The platform
More than search — an AI operating layer for your enterprise.
Turn your governed knowledge into assistants, automations, and insight — all behind your firewall, under your policies.
Agents that actually do things
Configure assistants with a persona and a knowledge scope, then grant them tools — they reason and act: search, run workflows, call external MCP servers, fetch data, send email. Give an agent its own address and your team can just email it.
Build AI automations on a canvas from 35+ typed nodes — triggers, retrieval, models, logic, data, actions and governance. Start them on a schedule, an incoming webhook, an email, or a new document.
Retrieve→Generate→Decide→Act
Metadata engineering
Every document auto-tagged at ingest — entities, roles, departments, dates, type — so a document pile becomes a queryable, permissioned knowledge graph you can filter and reason over.
Chat & analytics
A full conversational surface over any knowledge base, plus a live analytics view of usage, answer quality, cost, and content coverage across your workspace.
Open by protocol (MCP)
Connect agents to external Model Context Protocol servers over HTTP and their tools become available in the reasoning loop — extend the platform without forking it.
Enterprise security, on by default
Single sign-on (OIDC & SAML 2.0), SCIM provisioning, TOTP multi-factor, encryption at rest for documents and secrets, per-document access control enforced inside retrieval, content moderation, session revocation, a complete audit trail, and data-residency controls.