AgentInfra Radar
Use cases

Built for teams selling, advising, or investing across the AI infrastructure stack

AgentInfra Radar helps teams find public projects that may be relevant for account research, market mapping, partnership review, or founder-led outreach.

AI security companies
Find projects adopting agents, MCP servers, tool use, and LLM apps before security posture is mature.
  • Prioritize teams likely to need prompt injection, data leakage, access control, or runtime review
  • Track MCP and agent ecosystems where new security surfaces appear
  • Use contactAngle to start with context rather than fear-based outreach
LLM gateway companies
Spot teams building multi-model applications, gateway layers, routing controls, or model governance.
  • Identify projects likely to need routing, fallback, spend controls, rate limits, or policy enforcement
  • Monitor MCP and agent stacks that may become production workflows
  • Segment outreach by category and possibleNeed
AI observability tools
Track teams moving from prototype to production where traces, evals, and monitoring become urgent.
  • Find LLM apps, agent workflows, RAG systems, and tool-calling stacks
  • Use growthSignal to prioritize active projects
  • Map competitors, integrations, and ecosystem shifts
AI consulting agencies
Discover organizations building around agents, MCP, and LLM infrastructure that may need implementation help.
  • Source consulting conversations around architecture, deployment, evals, and workflow automation
  • Build vertical market maps from public project activity
  • Use possibleNeed to tailor discovery calls
AI infrastructure investors
Use the radar as a lightweight market map for emerging categories and early ecosystem signals.
  • Track new tools before they are broadly covered
  • Compare categories such as MCP servers, gateways, evals, observability, and security
  • Use source and verificationStatus to support further diligence

What it should not be used for

AgentInfra Radar is not a guaranteed customer list, a private email database, or an automated outbound engine.

  • Do not treat a leadScore as a promise of buyer intent
  • Do not skip manual review before outreach
  • Do not use the data to spam broad, unpersonalized campaigns