APERION
APERION provides an on-premises runtime governance platform called Smartflow that sits between enterprise applications and AI models, enforcing policy on every prompt, response, and MCP tool call. The platform attributes each agent action to a verified human through enterprise identity providers, escalates high-risk actions for approval, and maintains a hash-chained audit trail for regulatory compliance. Smartflow deploys as a Kubernetes-native appliance with a compiled Rust enforcement path, requiring zero code changes.
- Regulatory & Compliance Technology
- Cybersecurity
- Artificial Intelligence
- Enterprise Software
- AI Agents
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Enterprises deploying AI agents face a critical accountability gap: they cannot attribute model calls to verified humans or prove which person authorized high-risk actions like wire transfers. The existing identity stack was built for people, not autonomous agents, leaving most model calls unattended and exposing organizations to unauthorized actions and compliance failures with regulators like FINRA, SEC, and HIPAA.
Solution
Smartflow is a runtime governance layer that sits inline between enterprise applications and AI providers, enforcing policy at every prompt, response, and MCP tool call before execution. The platform attributes each agent action to a named, verified human through integration with existing identity providers like Okta and Entra, then escalates high-risk actions to that accountable person with assurance levels scaling from push notifications to live face checks. The system blocks, redacts, warns, allows, or holds actions based on policy, and records every decision in a hash-chained, examiner-ready audit trail. Deployed entirely on-premises in a Kubernetes container, Smartflow requires zero code changes and provides a unified control point for both security and finance governance.
Target Audience
Primary customers are regulated enterprises in financial services, healthcare, and government sectors running AI agents in production that require human-in-the-loop approval, compliance-ready audit trails, and strict data residency controls.
Features
- Compiled Rust-based enforcement path for infrastructure-grade performance, not a Python library in the request path
- Four-phase BERT semantic caching that measures hit rates on customer traffic during scoped proof-of-concept trials
- On-premises deployment in customer data centers or private cloud with no cloud dependency, no PyPI supply chain risk, and no third-party data exposure
- Identity-aware governance authenticating every AI interaction against enterprise IdP over OIDC, composing with Entra ID, Okta, SAML, and Kerberos single sign-on
- MCP tool-call policy enforcement that blocks destructive calls before they reach databases, repositories, or filesystems
- Unified gateway routing with vendor independence, automatic failover, split-traffic comparisons, and consolidation of 50+ API keys into a single enterprise key
- Active-active configuration with 256-bit encryption and complete audit trail with rollback capabilities