Maetra
Maetra is an AI governance and compliance control plane for teams operating tool-using AI agents. Discover inventories agents and capabilities; Comply maps systems to applicable frameworks and keeps reusable evidence current; Govern evaluates consequential actions against versioned policies and routes human approval when required. Secure scans prompts, messages, model outputs, and tool calls for prompt injection, data exposure, unsafe actions, and policy violations. Task Guard detects task drift, scope changes, and mismatched effects. Interaction Guard protects supported browser-AI prompts and files, while Audit preserves linked decision, approval, runtime, and change evidence. Teams can adopt modules separately or together through the web app, REST APIs, SDKs, and MCP. A 14-day no-card trial is available, with paid plans from $20/month.
Learn more
JetStream Security
JetStream Security is a security-first AI governance platform designed to give enterprises full visibility, control, and accountability over their AI systems by turning them from opaque, fragmented tools into managed, traceable infrastructure. It acts as a centralized control plane that connects identity, runtime governance, observability, and financial oversight into a single system, allowing organizations to “see every AI action, tie actions to accountable owners, [and] keep workflows inside approved boundaries” while enforcing policy at runtime. It introduces agentic identity, binding human, agentic, and non-human identities to specific actions and access permissions, ensuring every invocation, tool call, or workflow can be traced and governed through least-privilege access principles. Through continuous runtime governance, JetStream compares live AI behavior against approved blueprints, using immutable logging and real-time observability to detect drift.
Learn more
Bevel
Bevel is a vendor-agnostic, Git-backed control plane for enterprise AI agents, where an organization’s agents, context, skills, tools, permissions, and identities are defined as files the company owns in its own infrastructure and served to any agent runtime over MCP. Context is stored as typed knowledge nodes with provenance for every fact, including where it came from, who last changed it, and when it was verified, then compiled into a graph that can be traversed, updated, and used for dashboards. Skills are written as plain Markdown procedures that process owners can read, review in diffs, and port across runtimes. Tool manifests define available capabilities, while secrets stay in a vault and access rules determine which agents may read specific files or call endpoints. Each agent has its own identity, credentials, and scope so actions remain attributable.
Learn more
Aditya Protocol
Aditya Protocol is a reviewed-operations control plane for teams using AI agents, scripts, CI/CD, internal tools, and automation near production.
It helps technical teams request, review, approve, run, and record important operational actions with human oversight. The product includes reviewed command flows, rationale prompts, approval states, run history, artifacts, access-token guidance, node-token guidance, settings controls, and evidence-oriented workflows.
Aditya Protocol is currently open for a small supervised pilot with trusted technical reviewers and service-provider partners. It is not positioned as a broad public launch, certification product, legal-advice product, or replacement for human operational judgment.
Learn more
