Client Challenge
Where they were stuck
- Institutional knowledge is trapped in PDFs and stale wikis.
- Employees ask the same questions to overworked seniors.
- Naive AI search leaks confidential information.
Case Studies
Enterprise / KnowledgeAI AutomationDemo Project
AI Document & Knowledge Base Assistant
Turn thousands of internal documents into a single, always-answering colleague.
Industry
Enterprise / Knowledge
Category
AI Automation
Timeline
4 weeks (demo build)
Services
4 disciplines
Project Overview
The engagement
A retrieval-augmented assistant that ingests PDFs, wikis, SharePoint and Google Drive into a single searchable, citeable knowledge layer — with permissions that match the source systems.
Our Solution
What we built
- Connectors for common document and wiki sources.
- Grounded answers with clickable citations.
- Permission-aware retrieval mirroring source ACLs.
- Feedback loop to improve retrieval over time.
Development Process
How the work unfolded
01
Discovery
Framed the problem, mapped the workflow and defined success from day one.
02
Blueprint
Sketched the architecture, data model and user journeys end to end.
03
Build
Shipped in weekly increments with production-quality code from the first commit.
04
Launch
Migrated data, trained the team and cut over with a safety net in place.
05
Optimise
Measured, tuned and hardened until the system felt effortless to run.
Technology Stack
OpenAILangChainPineconeNext.jsSupabase
Services Provided
RAGKnowledge BaseSearchAccess Control
Key Features
What shipped
- Slack and Teams surfaces
- Per-document access control
- Freshness signals and stale-content alerts
- Analytics on what teams actually ask
- Audit log of every answer served
Before vs After
The shift
Before
Answers buried in PDFs
After
One click, one cited answer
Before
Ambiguous permissions
After
AI respects source ACLs
Before
Static wikis
After
Living, measured knowledge layer
Results
The outcome they feel every day
Faster onboarding
New hires ramp faster with a colleague that never sleeps.
Senior time reclaimed
Experts stop being human FAQ engines.
Content quality loop
Analytics show exactly which docs to rewrite next.
"This is what a modern intranet should feel like — an assistant, not an archive."
INTILEQ AI Lab
Demo build
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