Governance for AI agents.
Because AI agents don't have an undo button.
Every agentic AI action gets approved, flagged, or stopped cold — in milliseconds, with a permanent record.
Works with Python, TypeScript, and Java. Framework plugins for LangChain, AutoGen, and CrewAI.
Five stages between intent and action.
What we believe about governance.
Your agents are acting. Who's governing?
Autonomous AI agents are sending emails, executing transactions, accessing records, posting content, and controlling physical systems. Right now, the governance model for most of these agents is: hope the prompt was good enough.
GaaS provides the institutional checks that every hospital, bank, and trading floor requires of human employees — but for AI agents. Cognitive offloading that's structured, fast, transparent, and auditable.
Simulated feed. Actual decisions include full audit records with hash-chain verification.
Three lines of code. Full governance.
from gaas import GaaSClient client = GaaSClient(api_key="gaas_live_org_...") # Every agent action goes through governance decision = client.declare_intent( action="send_email", target="customer@example.com", risk_level="low", context={"authenticated": True, "template": "welcome_series"} ) if decision.approved: send_email(decision.modified_parameters or original_params)
Rules applied to reality, not just claims
Context Connectors are pluggable data sources that enrich AI agent intent declarations with real-world context during Stage 2 of the governance pipeline.
They transform governance from "rules applied to agent claims" to "rules applied to reality."
Govern what your agents do. Govern what agents do to you.
Organizations that govern their outbound agents earn trust tokens recognized across the GaaS network.
Governance earns trust. Trust unlocks access.
12 frameworks. 60+ policies. Built in.
Every governance decision is evaluated against the regulatory frameworks that apply to your industry, jurisdiction, and action type.
Patent Pending — Provisional patent filed March 2026 covering the GaaS governance pipeline architecture.
Frequently Asked Questions
Every time an agent declares an intent and GaaS evaluates it through the full five-stage pipeline — intent declaration, context enrichment, policy evaluation, deliberation if needed, and verdict plus audit — returning a verdict in under 100ms, that is one governance decision. The free launch pool covers all of that at no cost.
Every block includes a complete reasoning chain: which policy triggered, which condition failed, and what the agent would need to change to make the action compliant. Nothing is blocked silently. Your team can review every blocked action in the dashboard.
Shadow Mode requires a short SDK integration (Python, TypeScript, or Java) that routes your agent's actions through the GaaS pipeline. It typically takes an afternoon for a developer using LangChain, AutoGen, or CrewAI. Shadow Mode does not enforce decisions, so there is zero operational risk while you evaluate. Switching to live enforcement is a single flag change.
Guardrails live inside your agent's context window and cost 23,000–65,000 tokens per governance cycle. They have no access to real-world context and produce no auditable record. GaaS is an external governance layer: 200–500 tokens per cycle, enriches decisions with context your agent doesn't have, and produces an immutable audit trail for every decision.
GaaS evaluates every governance decision against 12 regulatory frameworks and 60+ policies — including EU AI Act, GDPR, HIPAA, PCI DSS, SOC 2, NIST 800-53, FedRAMP, CMMC, NIST CSF, NIST AI RMF, FERPA, and COPPA. Coverage is automatic based on the action type, jurisdiction, and industry. Compliance status is queryable via API and exportable for auditor review.
Every intent declaration is scanned against 17 prompt injection signatures at Stage 1 — before any context enrichment or policy evaluation occurs. Flagged payloads are rejected immediately. At Stage 3, enriched context is re-scanned for injection patterns that only emerge after enrichment. Behavioral anomaly detection identifies agents deviating from established patterns. All security controls are Tier 1 — non-disableable. SIEM integration (CEF format) is available for enterprise security operations.