SaaS // Client Project

From Searching Help Docs to
Faster Support Answers.

We built a Generative AI support assistant that searches product documentation, troubleshooting guides, known issues, and internal notes so support teams can answer customers faster without switching between multiple knowledge sources.

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 SaaS Company

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

Partnership
AI Support Experience Development

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

Goal
Faster Customer Support

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

What We Built
RAG-Powered Support 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.

Support agents had access to help-center articles, product documentation, release notes, internal troubleshooting guides, and past resolutions, but useful information was spread across too many places.

Simple tickets still required manual searching, while newer agents often needed help from senior team members. The company wanted AI to make support knowledge easier to use without inventing answers.

Slow Ticket Handling
Agents spent too much time searching several tools before replying.
Dependence on Senior Agents
Newer team members frequently escalated questions simply because they could not find the right knowledge.
Uneven Responses
Customers could receive different explanations for similar issues.
The Solution

What We Built.

01
Connect Support Knowledge
We connected product docs, help articles, release notes, internal troubleshooting guides, and approved support content.
Key details
Sources Help Center Docs Notes
Access Permission Aware
Sync Continuously Updated
02
Find the Best Answer Context
The RAG layer searches the knowledge base for the issue being discussed and returns the most relevant information.
Key details
Search Meaning Based
Context Relevant Sources
Answers Grounded AI
03
Draft a Useful Response
Generative AI turns that context into a clear response that an agent can review, edit, and send.
Key details
Input Natural Language
Output Clear Answers
References Source Linked
Before and After

How the Workflow Improved.

Area
Before
After
Ticket Research

Multiple Searches

Agents checked help docs, notes, and past tickets separately.

One AI Search

Relevant support knowledge is brought together in one answer.

New Agent Support

Ask Senior Staff

Newer agents depended heavily on experienced teammates.

Guided Assistance

The AI explains likely steps and supporting information.

Customer Replies

Manual Drafting

Agents wrote answers from scratch.

AI-Assisted Drafting

Responses are prepared from approved product knowledge.

Key Features

What Made the Solution Useful.

Business SEARCH

Support Knowledge Search

The assistant searches across approved product and support content from one conversation.

Business impact
Less Agent Search Time
RAG

Source-Grounded Troubleshooting

RAG retrieves relevant troubleshooting content before the AI explains the suggested next steps.

Business impact
More Consistent Guidance
GENERATIVE AI

Response Drafting

Agents can turn technical support information into clearer customer-friendly responses.

Business impact
Faster Ticket Replies
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

Ticket Research

Agents spend less time hunting for product information.

BeforeMulti-Tool Search
AfterOne AI Assistant
OutcomeFaster Support Research
RESULT: PRODUCTIVITY02

Agent Productivity

Routine questions can be answered with less help from senior team members.

BeforeFrequent Escalation
AfterGuided Self-Service
OutcomeMore Independent Support Team
RESULT: TRUST03

Response Consistency

Answers are grounded in approved support content.

BeforeVaried Answers
AfterKnowledge Grounded
OutcomeMore Consistent Customer Experience
ResultsFaster Support Research • More Independent Support Team
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.

It became much easier for the team to answer a customer confidently because the relevant product knowledge was already in front of them .

Give Support Teams Faster, Grounded Answers.

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

Support Knowledge Search

RAG Troubleshooting

AI Response Drafting