Knowledge agents, grounded

Answers from your documents,
with sources.

Knowledge buried in SharePoint, Google Drive, Notion, Confluence, Zendesk, ServiceNow, and Sitecore — surfaced by purpose-built RAG agents that cite every answer. Users trust what they see because they can click through to the underlying doc. Hallucination is the default failure mode of generic chatbots. Citations are the default behaviour here.

14 days free — no credit card required

A Nexil knowledge agent answering with inline citations

Five stages between question and answer

Generic chatbots paste your question into an LLM and hope. Nexil’s knowledge agents rewrite the query, search hybrid (vector + keyword), let an LLM rerank, then ground the final answer in the top results — with citations.

1. Query rewriting

An LLM step expands vague questions ("what did we decide about X?") into a precise, search-optimised query. Acronyms get expanded. Pronouns get resolved.

2. Hybrid search

Vector similarity for semantic match, BM25 keyword search for exact terms. Results merged via reciprocal rank fusion — you get the best of both.

3. LLM reranking

A reranker LLM scores the top N hits for relevance to the actual question. The five best chunks survive, the rest fall away.

4. Grounded generation

The answer LLM gets the surviving chunks as context and a strict instruction: cite every claim, refuse to invent. Strict, prefer-sources, or open grounding modes per agent.

5. Inline citations

Every fact in the response carries a citation marker. Click through to the source document at the exact page or section. Verifiable, not vibes.

Seven connectors, native to your stack

Each connector handles auth, incremental sync (only changed files reprocessed), and chunk-level metadata so citations point to the right place — not just the right document.

SharePoint

Sites, libraries, pages, attachments

Google Drive

Docs, Sheets, Slides, PDFs, shared drives

Notion

Workspace pages, databases, blocks

Confluence

Spaces, pages, attachments, comments

Zendesk

Help center articles, ticket KB

ServiceNow

Knowledge articles, runbooks

Sitecore

Marketing CMS content, public site copy

Direct upload

PDF, DOCX, Markdown, plain text drop-in

Tenant-level connections, agent-level scoping. The SharePoint connection sits at the tenant level; each agent picks which sites or folders it sees. No cross-agent leakage.

Each agent sees only what it should

One agent shouldn’t see everything. The Legal RFC agent only reads the legal SharePoint site. The Engineering RFI agent only reads the project specs library. The HR Policy agent only reads the handbook — not the salary band spreadsheet next to it. Scope is configured per agent, enforced at retrieval time, audited per query.

  • Two-tier data architecture — tenant-level connections, agent-level filters
  • Per-agent source allow-lists — site, folder, label, or path scoping
  • Group-based access — only the audience scoped to the agent can query it (IDP groups enforce this)
  • Grounding modesstrict means "if the source doesn’t cover it, say so", with a custom fallback message you write
  • Citations are mandatory in strict mode — the agent can’t answer without one
  • Incremental sync — only changed files are reprocessed; new docs appear in answers within minutes
The Nexil agent configuration editor with source scoping

What teams actually ask

Knowledge agents earn their keep when the answer would otherwise take 20 minutes of clicking through SharePoint. These are the patterns we see most.

Engineering RFI triage

"Has this BIM clash been resolved before?" — agent searches project SharePoint + Autodesk APS BIM models, returns the prior decision with the doc link.

Legal contract lookup

"What termination clause did we use in the Acme deal?" — agent searches the contracts library, returns the exact clause with page-level citation.

HR policy Q&A

"How much PTO do I accrue in year three?" — agent searches the employee handbook, returns the policy paragraph and links to the source PDF.

IT runbook Q&A

"How do we rotate the staging cert?" — agent searches Confluence + ServiceNow runbooks, returns the step-by-step with a ticket template.

Customer support

"Does this product support SSO?" — agent searches help center articles, returns the answer with the article link the agent can paste back.

Vendor research

"What did we decide about the Vendor X renewal?" — agent searches meeting notes + procurement SharePoint, returns the decision and who signed off.

Why users actually use it

Most enterprise AI fails the trust test — users get an answer, they can’t verify it, they stop using the bot. We invert the default.

Inline citations

Every claim shows the source. Click through to the doc, the page, the section. Verification is one click.

"I don’t know" is allowed

Strict grounding mode means the agent refuses when the source doesn’t cover it — with a custom fallback you wrote. No invented answers.

Feedback loop

Thumbs-up / thumbs-down on every response feeds back into analytics. You see which agents work and which need a better prompt or better sources.

Audit trail

Every query and response is logged per tenant. Compliance teams can reconstruct what an agent told a user, when, and from which source.

Drop in a PDF. Get a Q&A agent in seconds.

The fastest way to feel the difference is the Quickstart: upload a single PDF, DOCX, or Markdown file at signup. We chunk it, embed it, and spin up a knowledge agent ready to chat. 14-day free trial — no credit card required.

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