The problem Inflynce Protocol solves

Inflynce introduces a real-time, reputation-based coordination system on Base by leveraging the Farcaster graph - solving one of the most urgent and overlooked problems in Web3: DISTRIBUTION

Today, launching is easy. Anyone can ship a mini app in hours or publish content on Farcaster or Base App in seconds. But the real challenge comes next: How do you reach your first 100 real users? How do you get your first meaningful engagement? This is core problem: Web3 lacks a native, trust-based way to coordinate attention and unlock reliable distribution.

Inflynce solves this by transforming onchain engagement into a measurable, merit-based asset: Mindshare. Every user on Farcaster receives a real-time, percentile-based Mindshare Score, calculated from their social activity over the last 24 hours (recasts, likes, replies, velocity). This score reflects authentic behavior and becomes the coordination signal for distributing attention, rewards and visibility across the ecosystem.

To make this practical today, Inflynce Hub (live now) puts Mindshare into action. Hub is the public advertising surface of the protocol, where anyone can run or join onchain campaigns:

• Grow: Launch a Boosting Campaign by selecting a cast, adding a USDC budget and letting the system reward amplifiers based on their Mindshare.
• Earn: Recast eligible boosted posts and get paid in USDC - the higher your Mindshare, the more you earn.
• Result: Creators monetize their reach and projects gain trusted contributors.

Inflynce creates an Onchain Attention Marketplace, turning distribution into a reputation-aligned flywheel. Signal is rewarded. Value flows where it should: to those who truly move the graph.

TL;DR: If you’re building on Base or Farcaster, shipping is easy. Getting seen is the hard part. Inflynce solves distribution through programmable trust - a new onchain advertising system. 🟧

Challenges I ran into

One of the biggest challenges we faced was building a real-time, reputation-based coordination engine on top of the Farcaster graph - without any existing infrastructure for stream processing or behavioral reputation.

Key hurdles we ran into:

• No off-the-shelf scoring framework: We couldn’t rely on follower count or raw engagement metrics. We needed a custom algorithm (Mindshare) that could process likes, recasts and replies and factor in velocity - all in real time.
• Handling real-time data at scale: Farcaster generates thousands of events per minute. We had to design a streaming architecture (Redis + InfluxDB + PostgreSQL) that could handle ingestion, processing and scoring without latency or data loss.
• Sybil and bot mitigation: We had to build our own heuristics and filtering layers to prevent manipulation of Mindshare scores and reward distribution for Hub.

We designed a custom pipeline where events are ingested via Neynar, normalized and stored in InfluxDB (for time-based scoring) and PostgreSQL (for relational queries). The scoring logic was written in TypeScript with percentile-based ranking and signal-to-noise filters. To prevent compute overload during spikes, we batched and streamed events into Redis queues before computation.

This architecture is now live and powering Inflynce - an onchain attention marketplace where distribution is fully reputation-based.

Smart Contract Address(es)

Contract for Inflynce Hub payments distribution:
0xd15F681381b493b8f32090A01AAC835C89b19Fc6