Bound the agent.Free the enterprise.
G8R inspects every AI agent’s actions, evaluating intent against corporate policies, and brokers just-in-time credentials.
Multi-Agent Management for the agentic enterprise.
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The execution gap
The defining enterprise AI challenge isn’t maximizing agent autonomy. It’s reliably bounding its execution.
Enterprises are wiring probabilistic models into deterministic infrastructure. Today’s security stack was never built to govern what an autonomous agent decides to do.
Standing credentials
Agents inherit broad, long-lived privileges. One prompt injection turns that standing access into catastrophic lateral movement.
The contextual blindspot
WAFs and IAM evaluate IPs, headers, and roles, never the declared action. They cannot tell a safe read from a destructive delete on the same endpoint.
The approval bottleneck
Routing high-velocity agent actions through change-approval boards creates alert fatigue and erases the efficiency automation promised.
The checkpoint
3 steps between intent & execution.
Intercept
G8R sits natively in your VPC between the agent and your infrastructure. It intercepts each MCP tool call and inference request before anything executes.
→ agent.invoketool: kubernetesaction: "delete namespace prod"
Evaluate intent
The declared action and execution context are evaluated against deterministic, GitOps-managed YAML policy. G8R reasons about what the agent is actually trying to do.
policy: prod-guardrails.yamlmatch: action == deleteverdict: DENY (blast radius)
Broker JIT credentials
Approved calls are exchanged for a tightly scoped, just-in-time credential. Valid for seconds, never standing, it is then forwarded. Everything is logged, tamper-evident.
mint: sts:AssumeRolescope: read-only · ns=prodttl: 60s · audit: signed
Multi-Agent Management
MDM tamed fleets of phones.
G8R manages fleets of agents.
As enterprises move inference onto their own hardware (mini AI PCs, on-prem GPUs, air-gapped nodes), every agent becomes an endpoint to govern. G8R is the control plane for that fleet: Multi-Agent Management. One controller, every node, wherever the model runs.
One controller, many nodes
A single corporate control plane governs a fleet of agent and mini-AI-PC nodes over a private tailnet. Enroll, entitle, and bound each like a managed device.
Local-first inference
Sensitive work is routed to air-gapped local models like Ollama, vLLM, and Nemotron, and never leaves your trust boundary. It isn't even scanned, because nothing egresses.
Per-identity entitlements
The effective skill set for any identity is default ∪ groups ∪ allow − deny. Govern what every agent across the fleet is permitted to do.
Budgets, heartbeat & shadows
Cloud spend is capped per identity and fails closed without a controller heartbeat, while local inference stays unlimited. EDR telemetry surfaces shadow agents.
The defensible layer
Identity platforms issue the passport.
G8R is the border checkpoint inspecting the payload.
G8R secures what AI agents do, not just who they are.
The platform
One governance layer for the agentic enterprise.
Execution context evaluation
Parse the declared action, request context, and policy metadata of every tool call, then authorize against deterministic YAML.
Skill provenance validation
Cryptographically verify that the skill an agent runs was signed and vetted by your AppSec team. Shut down the supply-chain vector.
JIT credential brokering
Exchange an approved action for a scope-attenuated, ephemeral token valid for seconds, never standing privilege.
Shadow-mode policy generation
Observe agent behavior in non-production to auto-generate least-privilege policy. Ship guardrails without hand-writing every rule.
Tamper-evident audit
Emit cryptographically hashed logs of every invocation, intent, and outcome to your SIEM. Non-repudiable forensics by default.
Built in Rust. Deployed in your VPC. Fail-closed by design.
Stateless, sub-100ms credential brokering on a stack engineered for the control path.
Put a checkpoint on every agent.
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