Flocker Pitch: Building a Self-Maintaining Customer Data Platform for AI Agents

This is a TechCrunch Disrupt stage pitch by Flocker, a startup building a customer data platform that maintains itself so AI agents can answer business questions reliably. The founder explains why fragmented, outdated business data causes agents to hallucinate, then demos Flocker alongside Claude using the same model to show the difference clean data makes. The session closes with a judge Q&A covering go-to-market, moats, open sourcing, onboarding, and pricing.

■ The Problem
- Business data is always changing: people change jobs, companies shut down, teams get laid off
- Agents connected to unclean, unconnected sources still hallucinate
- HubSpot CEO and Salesforce president have raised the same issue at recent conferences
- Manual CRM/CDP maintenance is an estimated $50B opportunity

■ Product Demo
- Same model (Claude) on both sides: one agent with raw sources fails, Flocker succeeds
- Query asked: customers who signed up but were not contacted this year

■ Core Value Propositions
- Acts as a data router procuring 80+ data vendors
- Agent harness that builds and maintains data pipelines without data engineering effort
- Builds and maintains a customer ontology that models new objects automatically

■ Traction & Team
- Customers include AI and fintech companies such as Perplexity and Wise
- Reported 14% month-over-month compound revenue growth; starting ACVs around $10K with most revenue from expansion
- Team of eight based in Toronto, including former customers and founders

■ Judge Q&A
- Alternatives considered, economic buyer, product surface area expansion
- Enterprise onboarding and data confidentiality, outcome-based pricing, open-source strategy

This is useful viewing for founders, engineering leaders, and go-to-market teams evaluating how AI agents depend on data quality. Viewers can expect to understand the current market framing of agent-ready customer data, what a platform in this category claims to automate, and the commercial and technical questions investors ask about it.