Business Services // Client Project

From Scattered Knowledge to
One Company-Wide AI Search.

We built a company-wide AI search platform for a growing organization so employees could search approved information across departments, ask follow-up questions, and get source-grounded answers from one place.

Key Results RESULTS
1
Connected Knowledge Hub
Across Business Content
Seconds
Answer Time
Search + Generate
Source
Grounded Answers
With References

Trusted by teams building ambitious products

What We Set Out to Improve.

Business
Growing Multi-Department Company

A growing organization with useful information spread across documents, systems, shared folders, and team knowledge.

Partnership
Business AI Search & RAG Development

Coretus worked on product discovery, AI experience design, search logic, RAG workflows, integrations, testing, and deployment.

Goal
Company-Wide Knowledge Discovery

Help teams find the right information faster and turn business knowledge into useful, conversational answers.

What We Built
Company-Wide AI Search Platform

A secure AI search and RAG experience that finds relevant company information first, then uses Generative AI to explain it in simple language.

What Was Getting in the Way.

Sales, operations, HR, delivery, finance, and support each had useful documents and systems, but employees often did not know where to search first. The same question could require checking several tools or asking multiple people.

The company wanted one search experience without forcing every department to move all of its content into a brand-new system.

Too Many Places to Search
Employees jumped between shared drives, wikis, project tools, and internal systems.
Cross-Team Learning gaps
People often did not know which department owned the answer.
Repeated Questions
Routine questions moved through Slack, email, and meetings because knowledge was difficult to discover.
The Solution

What We Built.

01
Connect Existing Sources
We connected approved documents, knowledge bases, internal tools, and department content without requiring one large migration.
Key details
Sources Docs Wikis Internal Systems
Access Permission Aware
Sync Continuously Updated
02
Search Across Departments
The RAG layer retrieves relevant information across connected sources while respecting user access permissions.
Key details
Search Meaning Based
Context Relevant Sources
Answers Grounded AI
03
Generate One Clear Answer
Generative AI combines the retrieved context into a useful response with links back to the supporting sources.
Key details
Input Natural Language
Output Clear Answers
References Source Linked
Before and After

How the Workflow Improved.

Area
Before
After
Search Experience

Tool by Tool

Employees searched each system separately.

One Search Layer

A single question can search across approved sources.

Cross-Team Questions

Ask Around

People contacted several departments to locate information.

Knowledge Discovery

Relevant answers can surface regardless of which team created the content.

Access

Broad Sharing

Knowledge was sometimes duplicated just to make it easier to find.

Permission-Aware

The search layer respects existing access rules.

Key Features

What Made the Solution Useful.

Business SEARCH

Unified Business Search

Employees can search across connected company knowledge from one conversational interface.

Business impact
Fewer Tool Switches
RAG

Permission-Aware RAG

The retrieval layer uses only sources the current user is allowed to access.

Business impact
Safer Knowledge Access
GENERATIVE AI

Cross-Source Answers

Generative AI can summarize information from several approved sources into one clear response.

Business impact
Faster Cross-Team Understanding
Faster Delivery

How We Reduced Build Time.

Tested foundations helped the team spend less time on setup and more time on the parts that made this product useful.

What accelerated the work

4 reusable building blocks
01

Secure Knowledge Access

A tested starting point for secure knowledge access reduced repeated setup work.

02

RAG Search Layer

Reusable work for rag search layer let the team focus more time on the client’s specific needs.

03

Content Sync

This made it easier to add content sync without rebuilding common foundations.

04

Answer Quality Monitoring

A tested starting point for answer quality monitoring reduced repeated setup work.

Results

The Business Difference.

A straightforward before-and-after view of what changed for the team and their customers.

RESULT: SPEED01

Knowledge Discovery

Employees can search multiple approved sources at once.

BeforeSeparate Tools
AfterUnified Search
OutcomeLess Time Finding Information
RESULT: PRODUCTIVITY02

Cross-Team Questions

People can find knowledge outside their immediate department more easily.

BeforeAsk Around
AfterAI Discovery
OutcomeFewer Internal Hand-Offs
RESULT: TRUST03

Access Confidence

Search results remain aligned with existing content permissions.

BeforeDuplicate Sharing
AfterPermission Aware
OutcomeBetter Knowledge Control
ResultsLess Time Finding Information • Fewer Internal Hand-Offs
Trust and Control

How We Kept It Safe and Reliable.

01
Permission-Aware Search
The AI respects existing access rules so users only receive information they are allowed to see.
ACCESS CONTROLLED
02
Source-Grounded Answers
The system retrieves relevant business content before generating an answer, reducing unsupported responses.
RAG GROUNDED
03
Source References
Answers can include the supporting documents or knowledge sources so users can verify important information.
TRACEABLE
04
Knowledge Updates
Content can be refreshed as policies, documents, products, and processes change.
UPDATE READY
Client Testimonial

In their own words.

We did not need another place to store information. We needed a better way to find what already existed across the company.

Connect Company Knowledge with One AI Search Layer.

Have a similar challenge? We can help you plan and build a practical Business Services solution around your goals, budget, and existing systems.

Company-Wide AI Search

Permission-Aware RAG

Cross-Source Answers