FreshByDesign Case Study Hero Background

How FreshByDesign Slashed Sales Proposal Turnaround from Days to Minutes with Generative AI

LocationAustralia

SolutionGenerative AI Sales Proposal & Equipment List Generator

Minutes

Drafting Time (Down from 3–5 Days)

250–300

Monthly Quote Requests Automated

10 Years

Historical Proposals Leveraged as RAG Base

At-a-Glance

FreshByDesign — premier Australian distributor and engineering provider of advanced aquaculture and water filtration technologies.

Case Study

CHALLENGE:

The sales engineering team handled 250–300 highly technical quote requests monthly. Each proposal required analyzing design files, drafting custom equipment lists, and cross-referencing vendor cost sheets—taking 3 to 5 business days per proposal.

SOLUTION:

Intelegain architected an end-to-end multi-agent proposal generator leveraging Claude 3.5 Sonnet, OpenAI, n8n workflow orchestration, and an interactive Retool proposal studio backed by 10 years of vectorized engineering documents.

RESULTS:

Proposal drafting shifted from days down to minutes, pricing accuracy reached 100%, and sales engineers increased high-margin project proposal volume without adding administrative staff.

The Challenge: Complex Technical Proposals Bottlenecking Growth

FreshByDesign is renowned across Australia and the Asia-Pacific region for engineering state-of-the-art commercial aquaculture, hatchery, and water treatment solutions. Delivering these systems requires detailed, technically rigorous proposals featuring specialized pump schematics, filtration components, monitoring telemetry, and precision plumbing.

With demand growing rapidly, the sales engineering team was flooded with 250 to 300 proposal requests every month. Each quote required engineers to read client project briefs, extract design requirements, manually search manufacturer price sheets across dozens of vendors, and write 15-to-30 page custom proposal documents.

This manual workflow created massive bottlenecks. Drafting a single proposal consumed up to 8 hours of senior engineering time, causing turnaround delays of 3 to 5 business days. In a competitive commercial bidding environment, these delays hindered client deal velocity and limited revenue expansion.

High monthly quote volume (250–300 requests) overwhelming senior sales engineering capacity.

Lengthy turnaround times (3–5 days) causing competitive friction and delayed customer buying decisions.

Manual line-item extraction from fragmented vendor price sheets and PDF catalogs risking pricing errors.

Valuable tribal knowledge locked inside 10 years of archived proposal files, inaccessible during active quoting.

Why Intelegain Was Chosen

FreshByDesign selected Intelegain because of our ability to architect hybrid multi-model AI workflows combined with practical human-in-the-loop interfaces.

Multi-Model Architecture:

Combining Anthropic Claude 3.5 Sonnet for deep technical synthesis with OpenAI GPT-4o for rapid structured tabular extraction.

10-Year Historical Knowledge Base:

Ingesting and vectorizing a decade of past successful proposals, pricing models, and component configurations into an intelligent RAG knowledge base.

Human-in-the-Loop Workflow:

Designing an intuitive Retool interface that enables engineers to inspect, fine-tune margins, and approve generated proposals before export.

Low-Code Agility with n8n & Firebase:

Delivering lightning-fast document generation pipelines without heavy, brittle monolithic development.

Implementation: The Intelegain Approach

The project was delivered across three high-impact engineering phases over 14 weeks:

Phase 1: Knowledge Vectorization & Cost-Sheet Pipeline

Intelegain ingested ten years of historical proposal documents, engineering specifications, and dynamic vendor pricing sheets into Firebase Vector Store, creating a unified semantic search architecture across 15,000+ technical components.

Phase 2: Multi-Model Generation Core with n8n

We built automated n8n workflows. When a project brief is uploaded, OpenAI parses equipment specs and vendor line items, while Claude synthesizes the engineering narrative, executive summary, and project methodology tailored to the client brief.

Phase 3: Retool Proposal Studio & Export Engine

We built a sleek Retool dashboard for sales engineers. Engineers can view the AI-generated equipment bill of materials, adjust discount margins, review narrative text, and export publication-ready branded PDF proposals in one click.

Anthropic Claude 3.5 SonnetOpenAI GPT-4on8n AutomationRetoolFirebase Vector StoreNode.jsPDF Generation Engine

Measurable Results & Business Impact

Minutes

Proposal drafting turnaround (collapsed from 3–5 business days)

300/mo

Quote capacity managed effortlessly without increasing engineering headcount

100%

Consistency with real-time vendor equipment catalog pricing

4.5x

Faster time-to-client response, accelerating deal close rates

The deployment transformed FreshByDesign’s commercial velocity. Sales engineers now simply upload customer specifications, and within two minutes, the AI proposal studio generates a complete, mathematically accurate proposal draft with customized engineering rationale and exact line-item costs. Engineers maintain full control, reviewing and personalizing drafts in minutes rather than spending entire workdays writing documents from scratch.