Runlayer claims discovery of unmanaged agents, MCPs, skills, plugins, and client configurations with visibility into agent sessions.
Surface Shadow AI from unmanaged agents, MCPs, skills, plugins, and client configs
Public-source research
Vendor evidence
Review what vendors say publicly, the exact quoted source text, the security requirement each statement may support, and what still needs verification.
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Evidence records1280
Source checked863
Needs verification0
Source captured0
No supporting claim found411
Excluded from evidence6
Showing 1–17 of 17 evidence records
Clear all filtersRunlayer materials reviewed did not provide a public claim for embedded AI discovery across the business-application environment.
No quoted source text is recorded for this claim.
Runlayer claims centralized monitoring of AI usage, adoption, agent activity, and team-level value.
Monitor AI usage, cost, adoption, and agent activity in one place
Runlayer claims policy over what users and agents may access under identity, budget, OAuth grant, and runtime conditions.
Set what users and agents can access, under which identity, budget, OAuth grant, and runtime conditions.
Runlayer claims pre-action runtime scanning of tool calls, outputs, intent, and sensitive data.
scan tool calls, outputs, intent, and sensitive data before risky actions reach company systems
Runlayer materials reviewed did not provide a public claim for browser or software as a service (SaaS)-session controls for employee AI use.
No quoted source text is recorded for this claim.
Runlayer claims runtime security inspection before agent actions reach enterprise systems.
Secure runtime execution
Runlayer materials reviewed did not provide a public claim for enterprise AI governance, risk, approval, and compliance workflows.
No quoted source text is recorded for this claim.
Runlayer materials reviewed did not provide a public claim for adversarial testing or release assurance for AI systems.
No quoted source text is recorded for this claim.
Runlayer materials reviewed did not provide a public claim for model and AI component supply-chain inspection.
No quoted source text is recorded for this claim.
Runlayer claims an approved Model Context Protocol (MCP) catalog and governed Model Context Protocol (MCP) gateway across major AI clients.
serve them through a governed MCP gateway across every major AI client
Runlayer claims visibility, policy, and audit across agent sessions, MCPs, skills, plugins, memory, triggers, and scoped permissions.
full visibility into every agent session
Runlayer materials reviewed did not provide a public claim for trust or policy enforcement between agents.
No quoted source text is recorded for this claim.
Runlayer materials reviewed did not provide a public claim for non-human identity, service-account, secret, or workload credential lifecycle controls.
No quoted source text is recorded for this claim.
Runlayer claims identity-aware access policy and scoped permissions for users and agents.
under which identity, budget, OAuth grant, and runtime conditions
Runlayer claims centralized controls for employees using Claude, Cursor, ChatGPT, Codex, internal agents, Model Context Protocol (MCP) servers, and existing AI clients.
employees are adopting Claude, Cursor, ChatGPT, Codex, and internal agents
Runlayer claims centralized AI cost monitoring, spend attribution to teams and workflows, and budget-conditioned access for users and agents.
Monitor AI usage, cost, adoption, and agent activity in one place, then tie spend back to the teams and workflows getting real value.