Media & Consumer VC
AI-Powered Deal Sourcing for a Media & Consumer VC
A VC firm was sourcing deals the old-fashioned way — spreadsheets, manual research, and a lot of copy-pasting between tabs. I built two internal tools (a Sourcing Platform and an Intel Hub) that use AI-powered enrichment and multi-source web scraping to surface, score, and track deals in real time. The team went from spending 10-20 hours/week on manual sourcing to having a live pipeline that updates itself.
Scope
Sourcing Platform — investment sourcing platform
Intel Hub — retail intelligence hub
AI enrichment pipeline design
Real-time collaborative data infrastructure
Tech Stack
The Challenge
The client is a startup VC firm focused on media and consumer — music, entertainment, film, digital media, beauty, hospitality, and more. As a lean team without enterprise tooling, researching potential investments meant hours of manual Googling, scattered notes, and no structured way to enrich, grade, or track companies at scale.
The Approach
Started with the core problem: the team was spending hours manually researching every company. Built a Sourcing Platform to let them enter a name and website, then let AI do the rest
Designed the enrichment pipeline in phases — domain discovery, web scraping, AI analysis, social data extraction, and follower counts — each validating against multiple sources so nothing relies on a single data point
Added the tools the team needed around it: theme-based organization with drag-and-drop, a grading system, bulk CSV imports, and a real-time dashboard tracking ROI and pipeline health
Built an Intel Hub as a second tool for retail intelligence — analysts photograph store shelves, Gemini AI identifies every brand and SKU on sight, then enriches each with manufacturer data and maps it all geographically
Key Features
Multi-phase AI enrichment: domain discovery → web scraping → AI analysis → social data → consensus scoring
Four concurrent background processing queues for parallel enrichment
Hierarchical theme/folder management with drag-and-drop organization
Interactive dashboard with ROI tracking and sourcing grade distribution
Brand extractor for bulk CSV imports with automated domain discovery
Store walk photo analysis — Gemini AI detects every brand and SKU on retail shelves
Two-pass retail enrichment with Google Search grounding for manufacturer data
Interactive Google Maps view with intelligent markers per store location
A/B/C/D company grading system with pipeline tracking
Real-time Firestore listeners — all users see data updates instantly
The Results
~0
Companies / Week
0+
Hours Saved / Week
0
Days Saved / Year
$0
Cost / 1K Companies
~1,000 companies enriched per week at $10–15 in API costs — work that would take a full team 250+ hours done automatically
13,000+ hours of manual research eliminated per year — the equivalent of six full-time analysts
8,851 companies sourced, enriched, and graded in the system to date
Deal pipeline went from scattered notes and spreadsheets to a structured, searchable platform the whole team uses daily
Investment team now sees enriched company data in real time — research that used to take hours is ready in seconds
This project combined
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