AI Knowledge Base Agent

AI Knowledge Base Agent
Instant Answers from Your Company Docs

Your team wastes hours searching through docs, wikis, Slack threads, and emails to find answers that already exist somewhere in the company. An AI knowledge base agent indexes all your internal documents, understands context and relationships, and answers any question instantly with citations pointing to the source. It stays current as documents change and learns which answers are most useful.

14 day delivery
Permission aware
Full source code
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What This Agent Does

Indexes your company docs, answers questions instantly with citations, and stays current as documents change.

Natural language search across all company documents, wikis, Slack, email archives, and databases
Context aware answers that understand follow up questions and remember conversation history
Source citations with every answer linking directly to the document, page, and paragraph
Multi format ingestion: PDFs, Word docs, Google Docs, Confluence, Notion, Slack, and email
Automatic re indexing when documents change so answers always reflect current information
Permission aware responses that only show information the asking user is authorized to see
Slack and Teams integration for asking questions directly in the tools your team already uses
Data privacy with on premise deployment options and no external API calls for sensitive content
Usage analytics showing most asked questions, knowledge gaps, and content that needs updating
Onboarding acceleration with guided Q&A for new hires learning company processes and policies
Knowledge gap detection that identifies topics frequently asked about but poorly documented
Configurable confidence thresholds with fallback to human experts for low confidence answers

Measured ROI

30 seconds

Answer Time

Instant answers instead of 15+ minutes searching through documents

95%

Search Success

Questions answered accurately from existing company documentation

5 hrs/person/week

Time Saved

Every employee saves time on information retrieval

50% faster

Onboarding Speed

New hires find answers independently instead of asking colleagues

Tech Stack

LangChain
Agent framework
OpenAI / Claude
Question answering
Pinecone
Vector search (RAG)
PostgreSQL
Metadata store
Redis
Response cache
Resend
Digest delivery
Hono
API server
Railway
Hosting

14 Day Build Timeline

Day 1 to 2

Content Audit

Catalog document sources, assess content quality, map access permissions, define ingestion priorities.

Day 3 to 5

Ingestion Pipeline

Document parsers, chunking strategy, embedding generation, vector store setup, metadata extraction.

Day 6 to 8

Q&A Engine

Retrieval pipeline, answer generation, citation linking, confidence scoring, conversation memory.

Day 9 to 10

Integration

Slack bot, web widget, Teams connector, permission sync, auto re indexing.

Day 11 to 12

Testing

Answer accuracy on 200+ questions, permission validation, latency benchmarks, gap analysis.

Day 13 to 14

Launch

Production deployment, full document ingestion, team onboarding, analytics dashboard.

AI Knowledge Base Agent

$4,000

14 day delivery • RAG powered • 30 day support

Basic Q&A bots from $1,500 • Enterprise from $10,000

Build Your Knowledge Agent

See a RAG Application We Built

A knowledge base system that indexed 15,000 documents and achieved 96% answer accuracy for a professional services firm's internal team.

Read the Case Study

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50+ products shipped$10M+ funding raised2-week delivery

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