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 the suggested angle 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 the reason each account may matter

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 public activity signals 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 the buyer-fit note 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 links and source-check status 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 fit score as proof that an account is ready to buy
Do not skip manual review before outreach
Do not use the data to spam broad, unpersonalized campaigns