Office
© 2026 MangoCoders. All rights reserved.
© 2026 MangoCoders. All rights reserved.
BD Automation is a complete AI Business Developer system built to replace months of manual onboarding with a single knowledge-powered agent. It centralizes company profile, portfolio, and team data, then uses that knowledge to scan bidding platforms, score opportunities, and generate proposals that read like they were written by a senior BD.
From platform scanning and confidence scoring to AI-drafted proposals, developer matching, follow-up tracking, and a trainee bidding gate, the platform gives agencies a single command center to run their entire business development pipeline without losing institutional knowledge when staff turns over.
The Issue At Hand
The client's business development process lived entirely in the heads of a few senior hires. Every new BD had to be manually walked through the company's services, past projects, and developer roster before they could write a credible proposal, and pricing, tone, and quality varied wildly from person to person.
Meanwhile, opportunities were scattered across five different platforms with no way to tell which ones were worth a proposal versus a pass, and follow-ups regularly slipped through the cracks because there was no central system tracking client touchpoints.
No centralized company knowledge base, so new BD hires took weeks to ramp up on services, portfolio, and team.
No way to score incoming platform posts, leading to wasted proposals on poor-fit opportunities.
Proposals were written from scratch each time with inconsistent quality, tone, and referenced experience.
No system for matching the right developers to the right project before a proposal went out.
Follow-ups were tracked in scattered notes, causing overdue client touchpoints and lost deals.
No safe environment for training new BD hires without risking live bids on unvetted proposals.
Our Collaboration
Phase 1
Discover
Phase 2
Design
Phase 3
Build
Phase 4
Launch
Phase 1 — Discover
We shadowed the existing BD team to understand exactly how proposals were written, how opportunities were evaluated, and where knowledge was getting lost between hires.
Key Activities
BD Process Shadowing
Observed senior BDs writing live proposals to capture the unwritten rules behind a winning pitch.
Knowledge Gap Mapping
Catalogued every piece of company knowledge, services, portfolio, team, pricing, that lived only in people's heads.
Platform Scoring Criteria
Defined the scoring factors, expertise fit, developer availability, portfolio relevance, that would drive the AI's confidence score.
Trainee Onboarding Analysis
Reviewed how long new hires took to ramp up and where their early proposals typically fell short.
Delivered
Confidence Scoring
Every platform post is scored against company expertise, developer availability, and portfolio relevance to surface the best-fit opportunities first.
AI Proposal Generation
Generates full proposals from company profile and matched portfolio experience, typed out section by section like a real BD.
Central Knowledge Base
A single source of truth for services, tech stack, industries, and differentiators that every AI feature draws from.
Developer Auto-Matching
Automatically matches and names the right available developers for each project based on skills and specialties.
Trainee Bidding Gate
New BD hires practice here, with proposals auto-approved to go live only once they score 9.0 or higher.
Lead Pipeline & Follow-ups
A full Kanban pipeline paired with a color-coded follow-up tracker and AI-suggested client messages.
Gallery
Built with:
“
This is the closest thing to cloning our best BD. New hires used to take weeks to write a proposal we'd actually send, now the trainee gate gets them there in days, and the confidence scoring means we stopped wasting time on bids we were never going to win.
— BD automation Manager
This project is part of our ai automation work. See what we can build for you.
