SaaS // Client Project

From Scattered Sales Content to
Smarter Deal Preparation.

We built a Generative AI sales assistant that helps teams search case studies, service information, product documentation, pricing guidance, and approved proposal content, then turns the right knowledge into faster, more relevant sales material.

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 B2B Technology Company

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

Partnership
AI Sales Enablement Development

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

Goal
Faster Sales Preparation

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

What We Built
Generative AI Sales Knowledge 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.

The company had strong case studies, service documents, pitch decks, proposal content, product notes, and pricing guidance, but finding the most relevant material for a specific prospect took too much time.

Salespeople often reused old content because it was easier to find. The business wanted a smarter way to use existing knowledge while keeping messaging aligned with approved company information.

Slow Deal Preparation
Sales reps spent time searching for matching examples and reusable content.
Outdated Content Reuse
Easy-to-find material was sometimes used even when newer or more relevant information existed.
Inconsistent Messaging
Different reps described services and capabilities in different ways.
The Solution

What We Built.

01
Connect Sales Knowledge
We connected case studies, service content, product information, proposal libraries, pricing guidance, and approved sales materials.
Key details
Sources Case Studies Proposals Docs
Access Permission Aware
Sync Continuously Updated
02
Find Deal-Relevant Content
The RAG layer retrieves information based on the prospect's industry, problem, service interest, or sales question.
Key details
Search Meaning Based
Context Relevant Sources
Answers Grounded AI
03
Generate a Useful Draft
Generative AI turns selected knowledge into call briefs, proposal starting points, email ideas, or relevant case-study summaries.
Key details
Input Natural Language
Output Clear Answers
References Source Linked
Before and After

How the Workflow Improved.

Area
Before
After
Finding Proof

Search Manually

Reps browsed folders and decks for relevant case studies.

Ask by Deal Context

The assistant finds matching proof based on the prospect.

Proposal Preparation

Start From Old Files

Teams copied previous proposal content and edited it manually.

Grounded Drafting

AI creates a starting point from approved knowledge.

Messaging

Rep Dependent

Positioning varied between team members.

Shared Knowledge Base

Teams work from the same current information.

Key Features

What Made the Solution Useful.

Business SEARCH

Context-Aware Sales Search

Reps can ask for examples relevant to a prospect's industry, challenge, or requested service.

Business impact
Faster Deal Research
RAG

RAG-Based Case Study Matching

The assistant retrieves matching proof before suggesting what content is relevant.

Business impact
More Relevant Sales Proof
GENERATIVE AI

AI Draft Generation

Approved business knowledge can be transformed into call notes, summaries, and proposal starting points.

Business impact
Less Blank-Page Work
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

Sales Research

Relevant proof and service information becomes easier to find.

BeforeFolder Search
AfterContext Search
OutcomeFaster Deal Preparation
RESULT: PRODUCTIVITY02

Proposal Starting Point

Teams can begin from grounded company knowledge instead of old copied files.

BeforeOld Templates
AfterAI-Assisted Draft
OutcomeLess Manual Preparation
RESULT: TRUST03

Messaging Consistency

Sales teams use the same approved source material.

BeforeRep Dependent
AfterShared Knowledge
OutcomeMore Consistent Positioning
ResultsFaster Deal Preparation • Less Manual Preparation
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.

Instead of searching through old decks before every call, the team could ask for the most relevant examples for that specific prospect .

Turn Sales Content into Deal-Ready Knowledge.

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

Sales Knowledge Search

Case Study Matching

Grounded Content Generation