Launching June 2026 · Seeking 5 Design Partners · Designed for Regulated Industries

Runtime Assurance for Agentic AI

Deploy AI-powered automation with controls, evidence, and accountability built in. Every decision traced. Every workflow verified. Every outcome auditable.

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100%
Continuous monitoring
Every Decision
Verified — input, reasoning, output
Audit Ready
Evidence on demand
Arbis Verification Event Log
14:22PASSLoan underwriting agent — decision logged, all conclusions grounded in source
14:23PASSAdvisor prep agent — response approved, no PII exposure
14:23FAILResearch agent — information barrier breach in reasoning trace. Escalated for review.
14:26WARNINGEquity analysis agent — overconfidence detected

Works with LangChain · CrewAI · AutoGen · OpenAI Agents · custom agents · any enterprise AI platform

The Problem

Your AI is making decisions. Is anyone watching?

Point-in-time audits

Compliance checks happen monthly or quarterly. Between audits, an AI agent can make thousands of decisions — and thousands of violations. By the time an auditor notices, the exposure is already systemic.

Black box decisions

AI agents make consequential decisions — credit, trading, underwriting, advisory — with no audit trail you can trust. Regulators are asking questions you can't answer.

Stack of compliance tools

Governance framework, observability platform, guardrails toolkit — every vendor covers one slice. No one verifies the full reasoning. No one produces proof.

AI decisions are happening continuously. Controls and evidence need to be continuous too.

Platform — Runtime Verification

Every decision monitored, verified, and auditable

Not a dashboard. Not a report. A verification engine that analyzes every AI agent decision — input, reasoning, and output — flags violations, and produces a tamper-evident proof.

Decision Visibility

Every AI decision — input, reasoning trace, and output — captured with full context. Not sampled. Not aggregated. Every single one. We see the reasoning, not just the result.

Real-Time Violation Detection

Policy rules run against every decision in real time. When a rule breaks — bias threshold, data scope, output constraint — you know within seconds, not days.

Controlled Enforcement

When a violation is detected, Arbis flags it, assigns severity, escalates to the right owner, and holds deployment until resolved. Human oversight at every critical decision point.

Audit-Ready Reports

One-click regulatory reports for the EU AI Act and COSO ICIF. Full decision history, policy coverage, and a tamper-evident verification log — formatted for the exact framework your auditors expect.

Executable Policies

Define compliance rules once — they run continuously against every decision. Version-controlled, auditable, deployed like software. Your legal team and your engineers speak the same language.

Multi-Agent Orchestration

Arbis traces the full call chain when AI agents hand off to other agents — cross-system lineage with verification at every boundary, not just single-agent snapshots.

How It Works

From connect to verified in three steps

01

Connect your AI stack

Plug Arbis into any AI agent via SDK or API. Supports LangChain, AutoGen, CrewAI, custom LLM flows, and enterprise AI platforms. Non-invasive. No re-architecture required.

02

Define your policies

Set compliance rules, data access boundaries, output constraints, and regulatory requirements. Import from existing frameworks or start fresh. Every policy is versioned and auditable.

03

Arbis verifies continuously

From day one, Arbis monitors every decision, flags violations in real time, and escalates to human reviewers. Continuous evidence generation — and a full audit log whenever you need it.

AI assurance is not a dashboard problem. It's a runtime verification problem.

Arbis is built for enterprises deploying AI agents in high-stakes domains: banking, insurance, telecom, healthcare, government. If your AI makes decisions that matter, you need controls, evidence, and accountability built in from day one.

Get Started

Two ways to begin

Enterprise

Design Partner Program

For enterprises deploying or planning AI agents in regulated environments. Shape the product. Early access. Direct engineering support.

  • On-prem or VPC deployment
  • Custom compliance rule packs
  • Financial Services Compliance Pack
  • Reference workflows or custom workflow development
  • Cryptographic proof per decision
  • Dedicated onboarding
Teams

Arbis Starter

For teams building AI agents that need production-grade controls. SaaS deployment. Guided onboarding. Start verifying fast.

  • SaaS deployment
  • Continuous evidence generation
  • SDK integration
  • Low-touch guided onboarding
Why Arbis

The team behind Arbis

Built by

Radhika Venkatraman, CEO — Fmr CTO Verizon · CIO/CDO Credit Suisse · Sr. MD Cerberus Capital

Prof. Sriram Vishwanath, Head of Research — Byers Chair Professor Georgia Tech · MITRE Tech Fellow · Fmr Professor UT Austin · PhD Stanford

Dr. Yanni Georghiades, Head of Engineering — AI & Blockchain Expert · PhD UT Austin

Mapped to
EU AI Act · NIST AI RMF · ISO 42001
Plus OWASP LLM, OWASP Agentic, MITRE ATLAS, MITRE LILAC, COSO ICIF
Insights

From our team

Financial Times
Why enterprises need a new approach to AI governance
Radhika Venkatraman on the gap between AI governance policies and the production controls enterprises actually need.