Leadpoet
SN71AI sales agents that find and qualify your next customers automatically
Decentralized sales intelligence. Miners source, enrich, and submit prospective customer leads matching ideal customer profiles. Validators independently verify every lead through multi-stage checks: email deliverability, LinkedIn validation, domain verification, and reputation scoring. Only consensus-approved leads enter the curated pool.
// Sales leads, verified by consensus.
Leadpoet is a subnet that generates verified sales leads. Miners use automated pipelines to find potential customers matching specific business profiles, and validators independently verify that each lead is real, reachable, and relevant before it enters the pool.
The simple version: Imagine hiring 218 research assistants to find potential customers for your business. Each assistant finds prospects, but before you contact anyone, an independent team verifies every email works, every LinkedIn profile is real, and every company actually exists. Leadpoet automates this entire pipeline.
Centralized equivalent: Think ZoomInfo, Apollo.io, or Clearbit, but the data sourcing and verification are decentralized across competing miners and consensus-driven validators.
How it works:
- Miners continuously source prospects with automated pipelines, structure lead data (company, contact info, role, intent signals), and submit batches for validation. Rewards scale with consistency and quality of approved leads over time.
- Validators independently validate each lead through multi-stage checks: email format and deliverability, company and role verification, reputation scoring. They run commit/reveal consensus to approve leads and set on-chain weights.
- The problem it solves: Traditional lead generation is expensive, slow, and produces low-quality prospects. Sales teams waste time chasing dead emails and wrong numbers.
- The opportunity: The global lead generation market exceeds $10 billion annually. Every B2B company needs qualified prospects, and the willingness to pay for verified leads is high.
- The Bittensor advantage: 218 active miners competing to source leads means broader coverage than any single data provider. Multi-validator consensus verification produces higher quality than centralized systems where one company's algorithm decides what's "verified."
- Traction signals: 1,386 commits across 35 contributors (second-highest contributor count in our coverage). 218 active miners. Recent commits raising champion score thresholds (quality bar increasing). Dev activity score: 8.0/10.
Category: Data Analytics and Prediction | Centralized Competitor: ZoomInfo, Apollo.io, Clearbit, Lusha, Hunter.io
Leadpoet targets one of the most commercially straightforward markets in Bittensor. Unlike subnets that need to convince the world that decentralized AI matters, Leadpoet produces something every sales team already buys: verified contact data.
Mechanism:
The commit/reveal consensus for lead validation is well-designed. Validators independently assess each lead and submit encrypted verdicts before revealing them, preventing copying. This mirrors academic peer review: multiple independent evaluators assess the same work, and consensus determines quality.
Recent development is focused on raising quality bars. The latest commits increase champion score thresholds from 10 to 25 to 30, and add automatic cleanup of stale work files. This trajectory (tightening standards over time) is a sign of a maturing marketplace.
The codebase is substantial: 1,386 commits across 35 contributors with 6-37 commits per week in recent months. This is one of the most actively developed subnets by contributor diversity.
Market metrics are solid. At 34,001 TAO market cap with 2,043 holders, Leadpoet is mid-tier. Gini of 0.580 (low, well-distributed). The 30-day is flat at +0.5%, while the 90-day shows -29%. Net 7-day outflow of -242 TAO suggests some repositioning.
- 90-day decline: -29% indicates the market hasn't found a catalyst despite active development.
- Data quality arms race: As miners get better at gaming verification, validators must constantly evolve checks. This is an ongoing cost.
- Regulatory risk: Automated lead scraping operates in a gray area under GDPR and similar privacy regulations.
- Competitive saturation: Lead generation tools are abundant. Differentiation must come from quality, not just price.