Manufacturing // Client Project

From Searching Manuals to
Answers for the Job at Hand.

We built a Generative AI technical knowledge assistant that helps engineers and service teams search manuals, maintenance guides, troubleshooting notes, and service history using everyday questions.

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
Equipment & Field Service Company

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

Partnership
AI Technical Knowledge Development

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

Goal
Faster Technical Knowledge Access

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

What We Built
Technical Documentation AI Assistant

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.

Technicians and support teams worked with product manuals, installation guides, maintenance documentation, service notes, and troubleshooting records. The information existed, but finding the right section during an active job could be slow.

Newer technicians also depended heavily on experienced staff for questions that were already documented somewhere in the company's technical knowledge.

Slow Troubleshooting
Teams spent time navigating long manuals during customer or field work.
Experience Dependence
Newer team members frequently relied on senior technicians for documented information.
Scattered Technical Knowledge
Manuals, service notes, and internal fixes were stored in different places.
The Solution

What We Built.

01
Connect Technical Content
We connected product manuals, maintenance guides, service notes, troubleshooting documents, and approved technical knowledge.
Key details
Sources Manuals Service Notes Guides
Access Permission Aware
Sync Continuously Updated
02
Retrieve Relevant Instructions
The RAG layer finds the sections most closely related to the equipment, symptom, or question being discussed.
Key details
Search Meaning Based
Context Relevant Sources
Answers Grounded AI
03
Explain the Next Step
Generative AI turns the retrieved content into a clearer explanation while keeping the original source available.
Key details
Input Natural Language
Output Clear Answers
References Source Linked
Before and After

How the Workflow Improved.

Area
Before
After
Manual Search

Navigate Documents

Technicians searched table-of-contents pages and PDFs.

Question-Based Search

The assistant retrieves relevant technical sections.

Troubleshooting

Ask Senior Staff

Complexity often led to internal calls for help.

Guided Knowledge

Documented solutions become easier to access.

Learning

Read Full Manuals

New technicians learned through long documents.

Contextual Explanations

AI explains information around the current task.

Key Features

What Made the Solution Useful.

Business SEARCH

Technical Knowledge Search

Teams can ask equipment and service questions in normal language.

Business impact
Faster Information Access
RAG

RAG-Grounded Troubleshooting

The AI retrieves relevant manuals and service notes before explaining a possible next step.

Business impact
More Useful Context
GENERATIVE AI

Technical Summaries

Long procedures can be turned into clearer steps while preserving links to the original source.

Business impact
Easier Field Use
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

Troubleshooting Search

Relevant technical information can be found faster.

BeforeManual Lookup
AfterQuestion Search
OutcomeFaster Field Support
RESULT: PRODUCTIVITY02

Senior Technician Interruptions

Documented answers become easier for newer staff to find independently.

BeforeFrequent Escalation
AfterSelf-Service Knowledge
OutcomeLess Routine Escalation
RESULT: TRUST03

Technical Confidence

Users can check the source manual or note behind an answer.

BeforeMemory Based
AfterSource Grounded
OutcomeMore Verifiable Guidance
ResultsFaster Field Support • Less Routine Escalation
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.

The assistant made our documentation useful in the moment. A technician could ask the question they actually had instead of guessing which manual section to open.

Turn Technical Documentation into On-Demand Knowledge.

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

Technical Document Search

RAG Troubleshooting

Source-Linked Answers