No. Alterion deploys lightweight, runtime-level sensors across your infrastructure—monitoring network flows, container behavior, endpoint activity, and application logs—to build a continuously updated map of every agent and their behaviors. There are no code changes, no SDK integrations, and no modifications to how your agents are built or deployed.

Real-time token and agent spend by team, agent and use case, on the same pane as governance.

A live, explainable risk score per agent from behaviour, identity, permissions and blast radius, so the alert stream becomes a ranked list.

Behaviour that diverges from intent across a session, the failure mode you cannot write a rule for in advance.

No. Alterion interoperates as the central plane, pulling your gateways, SWG, EDR and DLP into one policy and one view, and filling the gaps between them.

Yes. Author policy once in Draco and enforce through Aquila, Zscaler, your EDR or your DLP. It is not a rip-and-replace.

Sensors across endpoints, SaaS and cloud observe activity at the runtime, so shadow and third-party agents surface next to the ones you instrumented. Discovery does not depend on an agent being declared.

Route each task to the best-value model automatically, and cap or kill runaway agents before spend runs away.

Evidence is generated from runtime activity and mapped to SOC 2, ISO 42001, NIST AI RMF, HIPAA and the EU AI Act. It is produced from the runtime, not assembled for the audit.

Three layers, one record: heuristic, semantic that reads intent, and behavioural that tracks drift over time, judged in-path by purpose-built small language models.

Runtime enforcement covers the seams siloed tools leave, and discovery surfaces the shadow agents none of them can see.

Aquila checks browser AI and personal ChatGPT on the device, above encryption, before data leaves the browser, with no TLS termination.

No. Discovery and enforcement both work from the runtime, with no agent code changes and no SDKs.

Yes. Alterion monitors prompts flowing through your agents in real time and flags injection patterns—including attempts to override system instructions or escalate permissions through text, files or images. When detected, we trigger remediation automatically.

Traditional policy tools enforce rules based on access permissions (what an agent can do.) Alterion's contextual boundaries enforce rules based on intent (what an agent should be doing given its purpose, team, and environment). A finance agent can't talk to the customer support database not because of a hardcoded rule, but because the system understands the agent's purpose and baseline behaviour, and prevents actions outside their intended scope.

Yes. Spend is attributable by team, agent and use case, so cost becomes a governed, provable line rather than an estimate.

Runtime governance acts on it, tightening boundaries and blocking off-policy actions as risk climbs.

Yes. The MCP and function-calling step nothing else controls is judged across prompt, response, tool call and payload.

Yes. Set policy once and apply it across every agent and environment.

Every prompt, tool call and commit is checked pre-execution on the device, so secrets and non-compliant code are stopped before they run.

Those map cloud posture and known assets. Alterion discovers agents by what they do at runtime, attributes each to an owner, and enforces in the path, including the shadow agents those tools do not see.

Identity tools know who an agent is. Alterion knows what it's doing. Agents aren't users; they don't have job titles, org charts, or intent you can read from a permission set. Alterion was built from first principles for non-deterministic, autonomous systems. That's a fundamentally different architecture than retrofitting an IAM tool.

We believe that detecting every agent in the enterprise, especially unsanctioned or shadow agents, requires detection at the runtime (malicious actors will not use your SDK!). Additionally, we believe engineering and business teams should focus on launching agents and driving business value quickly, not being slowed down by SDK integrations and dev time assessments. Enabling governance at the runtime enables your business to move fast and stay competitive, while providing governance at the only time that matters - when the agent is running autonomously with production data and systems.

No agent code changes or SDKs.

Alterion is air-gapped and runs in your stack, so residency is answered by the deployment itself.

97.5% classification accuracy across six small language models, with a verdict in under 100 milliseconds.

In your VPC, models included, with no egress.

None, and no SDKs.

Nowhere. Alterion runs entirely in your environment, in your VPC or on-prem, models included. Nothing leaves your walls.

We believe agents are a new class of technology that require a different paradigm to managing, securing and governing, that does not fit in the existing enterprise IT stack. This is why we built Alterion, the intelligent runtime control plane for agents, providing comprehensive observability, security, governance and optimization for enterprises.

Alterion's policy engine lets you define rules once and enforce them everywhere. Import your existing compliance policies in plain language or CSV format—Alterion's Small Language Models translates them into actionable rules and applies them to the right agents and boundaries across every cloud, automatically.

Yes, entirely in your stack, with cost on the same pane as governance.

No. Audit packs come from the runtime, without building an army of a team.

None, and no SDKs. It runs entirely in your stack.

None.

No. Alterion runs entirely in your stack.

A single read-only scan in your VPC produces the inventory. Deployment is days, not months.

Alterion supports agents deployed on any cloud including AWS, Azure and GCP. We are agent agnostic and support agents built through any agent development framework including Langchain, CrewAI etc.