Neta Bridge. Turning a broker's 1,000+ contacts into an intelligent deal pipeline.
Brokers and traders in global commerce have always known the problem: thousands of contacts, dozens of live deals, and no efficient way to connect the right person to the right opportunity. Neta Bridge is being built to solve that — starting with contact ingestion and deal tracking.
MVP
Stage
Live & acquiring customers
5
Team Size
Engineering + Business
1000s
Contacts
Per broker, untracked
2026
Active Since
Ongoing development
01 — The Origin
A broker with 7,000 contacts and no way to search them
Our co-founder had spent years in international trade. He'd spoken to enough brokers to know their shared frustration: thousands of WhatsApp contacts, hundreds of active deals, and no system to surface “who do I know that can supply X, right now?”
The problem wasn't the quantity of relationships. Brokers are deeply networked. The problem was that their network was locked in unstructured devices — phones, spreadsheets, memory — with no searchable, trackable layer on top.
The answer: a contact ingestion pipeline paired with a deal-tracking interface. Not a marketplace to meet strangers — a system to unlock the value of relationships they already have.
The untracked broker reality
02 — The Product
Contact ingestion. Deal tracking. Network intelligence.
The MVP is a two-part system: ingest a broker's contacts automatically (no manual entry), and overlay a deal-tracking pipeline on top. Phase two makes that network intelligent — searchable, filterable, connectable.
Contact Ingestion
Import contacts from existing sources without manual data entry. The platform organizes them into searchable, filterable profiles — supplier, buyer, product type, geography.
Deal Pipeline
A Kanban-style deal tracker that attaches contacts to active opportunities. Track status, parties, products, and timelines across every deal simultaneously.
Network Intelligence
Surface warm introductions, identify who in your network can supply a given product, and map relationship strength — like Affinity CRM, but for trade operators.
Marketplace Layer
Once the network has real users and real data, a marketplace layer allows verified members to discover vetted opportunities beyond their existing circle.
03 — Build Process
From broker interviews to live MVP
01
Problem Discovery
Our co-founder spoke to dozens of brokers and traders. One recurring pain point emerged: they had thousands of contacts and hundreds of active deals — all living in WhatsApp threads and spreadsheets with no way to surface the right person at the right time.
02
Contact Ingestion Pipeline
The first thing we built was a way for users to import their existing contacts. Not manually — automatically. Like LinkedIn's 2004 address book import, we knew the product had to be valuable to ONE person with zero other users on the platform.
03
Deal Tracking Interface
We designed a pipeline view where brokers can track their active deals, assign contacts to opportunities, and see the status of every trade at a glance. CRM meets trade ops.
04
MVP Launch
The MVP is live. We are in active customer acquisition mode, turning early user feedback into product priorities. The network intelligence layer comes next.
04 — How They Built It
Companies that combined network intelligence with marketplaces
Our co-founder studied four defining companies — LinkedIn, Affinity, Faire, and Alibaba — to understand the order of operations. The pattern was clear: the network layer always precedes the marketplace. The one approach that has never worked at any scale is launching a generic, empty marketplace for “anyone who wants to trade.”
est. 2003
Launched with profiles only. No marketplace for 2 years. The marketplace worked because millions of real profiles existed first.
Affinity CRM
est. 2014
Proved that 'search your own network' is a massive standalone business worth $120M+ raised — with no public marketplace, ever.
Faire
est. 2017
Started impossibly narrow (indie retailers + artisan brands) and seeded the marketplace with existing relationships, not strangers.
Alibaba
est. 1999
Manually recruited suppliers for years before the marketplace worked. An empty marketplace for 'everyone' has never worked at any scale.
The order that worked
| Company | Started With | Marketplace Added | Key Insight |
|---|---|---|---|
| Profiles + address book import | 2 years after launch | Real profiles first, marketplace second | |
| Affinity | Email/calendar sync (auto CRM) | Never — network tool only | Search your own network = $120M+ business |
| Faire | Net-60 terms for indie retailers | Day 1, seeded by existing relationships | Viral because real relationships migrated |
| Alibaba | Manual factory recruitment | After years of supply-side building | Empty marketplace for 'everyone' never works |
What this means for Neta Bridge: We are building the network tool first. Contact ingestion → deal tracking → network intelligence. The marketplace layer grows naturally from a foundation of real users with real data — exactly like LinkedIn, exactly like Affinity. That's the playbook.
05 — Skills Applied
My contribution to the build
06 — Tech Stack
Built for real-time trade intelligence
Framework
Next.js
Framework
React
Backend
Node.js
Database
PostgreSQL
Database
Prisma ORM
Design
Figma
Language
TypeScript
Styling
TailwindCSS
Neta Network
netabridge.com