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Knowledge Chat

Internal knowledge assistant with source citations.

A source-backed assistant for teams that need answers from policies, runbooks, product notes, and internal documentation.

[ Client review ]

Knowledge Assistant made the workflow easier to explain: the inputs, AI review, human handoff, and business action are all visible in one place.

Product team
Internal knowledge assistant answering a question with cited company documents.
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CS / 21Knowledge AssistantInternal documents · Cited answers
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Client

Knowledge Assistant

Internal documents · Cited answers

Engagement

Product narrative

Positioning · workflow story · product proof

Role

AI builder

Knowledge Chat workflow

Year

2026

Project positioning

Buyer caseknowledge chat outcomes
Chat
Answer surface

Questions answered in context

Cite
Source cards

Evidence remains visible

Filter
Search scope

Teams narrow by source

Trust
Reviewability

Snippets support the answer

Company answers are scattered across docs, runbooks, and policy pages.

Employees need quick answers, but they also need to know which document supported the response.

The workflow needed a visual and operational story that buyers can scan quickly: what comes in, what the AI does, what a human reviews, and where the result lands.

Answers need source dates, versions, and confidence around outdated material.

The assistant must respect document access rules.

Employees should see snippets before relying on a response.

The system should say when no reliable source exists.

We made citations the center of the assistant experience.

The assistant interface pairs the chat answer with source cards, document snippets, and filters so users can verify before acting.

The project is framed around the business workflow itself: the source inputs, AI review, approval points, and final handoff are all visible in one story.

  • Chat answer written from internal documents.
  • Source cards and document snippets.
  • Search filters for teams, date, and collection.
  • Fallback when the assistant cannot find evidence.

Citation-first UI

Source cards are placed beside the answer.

Filter controls

Users can scope searches to relevant collections.

Snippet preview

Evidence is visible without opening every document.

Feedback loop

Users can flag weak answers for content updates.

Week 1

Workflow audit

Mapped source inputs, users, review points, and the final business action.

Week 2

AI task design

Defined classification, extraction, drafting, prediction, or detection responsibilities.

Week 3

Human review path

Added approval, exception, and escalation points where judgment matters.

Week 4

Product narrative

Turned the workflow into a clear buyer story for sales conversations, reviews, and handoff.

Answer speedTeams find internal guidance faster.
86
Source trustCitations make answers inspectable.
90
Search controlFilters keep answers in the right knowledge area.
80
Support loadRepeated internal questions require fewer handoffs.
76
[ 01 ] Sources
Knowledge sources
  • Docs
  • Runbooks
  • Policies
  • Tickets
[ 02 ] Prepare
Retrieval prep
  • Chunking
  • Permissions
  • Metadata
  • Filters
[ 03 ] Decide
Assistant answer
  • Grounded response
  • Source cards
  • Snippets
  • Gaps
[ 04 ] Deliver
Team delivery
  • Chat UI
  • Saved answers
  • Escalation
  • Feedback

Knowledge assistants should answer only when they can show the user where the answer came from.

Clearer product surface: Knowledge Assistant now communicates the workflow through the actual review states, handoffs, and outcomes buyers care about.

Faster buyer clarity: the problem, workflow, proof points, and next action are easy to understand without a technical walkthrough.

"

Knowledge Assistant made the workflow easier to explain: the inputs, AI review, human handoff, and business action are all visible in one place.

P
Product team
Sources
  • Docs
  • Runbooks
  • Policies
  • Tickets
Processing
  • Chunking
  • Permissions
  • Metadata
  • Filters
Answer layer
  • Grounded response
  • Source cards
  • Snippets
  • Gaps
Delivery
  • Chat UI
  • Saved answers
  • Escalation
  • Feedback
Governance
  • Human review
  • Audit trail
  • Quality checks
  • Fallback rules
Book a call

Got a problem AI might solve? Let's find out.

30 minutes. Free. No NDA needed. You leave with a clear yes-or-no on whether to build — and a one-pager you can forward to your team the same day.

[ Response ]

Within 24 hours

[ Timezone ]

GMT+5 · flexible

[ Discovery ]

Free · no NDA needed

[ Engagement ]

$1,000 / week sprint