Control Plane for AI Agents
From first commit to production deployment — ARIAS gives your team the confidence to ship agentic AI without flying blind.
The Problem Every AI Engineering Team Faces
Agents Ship. Governance Doesn't.
AI agents are being deployed faster than teams can reason about their behavior. A prompt changes, a tool is added, a model is swapped — and suddenly your agent behaves differently in production than it did in staging. There's no diff, no audit trail, and no CI/CD gate standing between a behavioral regression and your users.
ARIAS was built to close this gap. It brings the rigor of software engineering — version control, behavioral fingerprinting, automated certification — to the agentic AI lifecycle.
No Behavioral Visibility
Teams can't track what changed between agent versions or why behavior shifted.
No Deployment Gates
Nothing stops a misconfigured agent from reaching production automatically.
No Compliance Evidence
OWASP, NIST, EU AI Act requirements go unchecked at the code level.
No Inventory of AI Agents
Agents are dynamic, tools, skills, orchestrations change continuously.
The ARIAS platform — including its Agent Behavioral Fingerprint methodology, behavioral drift detection and verdict system, privacy-preserving scanner architecture, and CI/CD governance gate — is patent pending technology, subject of a pending U.S. patent application.
Three Steps from Codebase to Certified
ARIAS integrates directly into your existing development workflow with zero infrastructure overhead. No cloud upload required — everything runs locally in your pipeline.
1. Install the Scanner
One command. Runs locally in your CI/CD pipeline, dev machine, or build server.
2. Scan Your Codebase
Point it at your repo. ARIAS detects agents across 35+ frameworks automatically.
3. Review Your Assessment
Every agent is scored across 6 dimensions with specific, actionable recommendations.
Agent Behavioral Fingerprint (ABF)
Every detected agent receives a unique behavioral fingerprint — a composite hash of the five core dimensions that define how an agent thinks, acts, and fails. The ABF is the foundation of everything ARIAS does: drift detection, certification, and change impact analysis all flow from this single source of truth.
Goal
System prompt, instructions, behavioral boundaries
Tools
Permission signatures, access scope, side effects
Memory
Access patterns, persistence, isolation
Orchestration
Delegation chains, coordination dependencies
Error Posture
Failure handling, fallback mechanisms
Scored Across 6 Dimensions
Every agent in your codebase is evaluated against a structured maturity model. Each dimension produces specific findings with actionable recommendations — not generic warnings, but targeted guidance your team can act on immediately.
Prompt Engineering
Instruction clarity, boundary definition, injection resistance
Agent Design
Architectural patterns, responsibility scoping, composability
Memory Architecture
State management, persistence strategy, isolation controls
Orchestration Soundness
Multi-agent coordination, delegation safety, loop prevention
Observability & Tracing
Logging coverage, trace completeness, debugging surface
Governance Alignment
Regulatory mapping, policy compliance, audit readiness
The Agentic AI Mesh
Risk in an agentic system rarely lives inside a single file — it lives in the relationships between agents, the tools they hold, and the paths they can delegate along. ARIAS reconstructs that graph from your repository and renders it as a navigable map, so the architecture your team believes it built can be checked against the one it actually shipped.
Agents, Tools, Memory, Models
Every node ARIAS detects is placed on one map — per scan and across repositories — so you can see the whole estate rather than one repo at a time.
Delegation Paths Made Visible
Where one agent can reach another agent's capabilities, the path is drawn — including the escalation routes that are invisible when reading either agent's code on its own.
Change the Map, Not Just the Diff
As the estate evolves, the topology evolves with it — new agents, new tools, and new delegation edges appear as changes you can review.
Findings That Read the Architecture, Not Just the File
Once the mesh exists, ARIAS can ask questions no single-file review can answer — whether an agent's access matches the role it is described as having, where authority quietly expands, and whether two agents are pulling in opposite directions.
Permission Fit
Compares the access an agent actually holds against the role its own definition describes — surfacing the gap between "what this agent is for" and "what this agent can do."
Escalation Paths
Identifies where an agent with narrow direct access can reach broader capability by delegating — the reachability question that file-level review structurally cannot see.
Objective Conflicts
Flags agent pairs whose stated goals point toward opposing outcomes on the same concern, so intentional balance can be distinguished from accidental tension.
Permission Drift
Tracks access tier across scans and raises a signal when an agent gains broader capability than it held at its last approved baseline.
Release Comparison
Compares two scans of the same repository and reports what changed at the agent level between releases — not just what changed in the code.
Cost Profile
Estimates the token and cost profile of each agent from its configuration, and flags when that profile shifts materially between scans.
Architectural findings are available on the Enterprise plan.
Drift Detection & Certification
Agents that maintain stable behavioral fingerprints earn active certification. ARIAS continuously compares fingerprints version-to-version — when a tool is added, a prompt is modified, or a model is upgraded, the drift is detected, classified, and acted upon automatically.
Drift classification isn't binary. ARIAS distinguishes between changes that matter and changes that don't, so your team spends review cycles on what's actually risky.
🟢 Cosmetic Drift
Minor changes detected. Certification maintained. No action required.
🟡 Material Drift
Significant behavioral change. Certification suspended. Review required before deploy.
🔴 Critical Drift
Breaking changes detected. Deployment blocked automatically via CI/CD gate.
CI/CD Gate — Stop Bad Agents Before They Ship
Integrate ARIAS into your deployment pipeline and enforce a hard gate on agent certification. The gate runs automatically on every deploy, checks the certification status of all agents in scope, and either allows the deployment to proceed or blocks it with specific, actionable findings — not a generic failure message.
All Agents Certified
Fingerprints stable. Certification active. Deploy proceeds automatically with a full audit record.
Material or Critical Drift Detected
Deploy is blocked. ARIAS surfaces the exact findings — which agent, which behavioral dimension, what changed — so your team knows precisely what to fix.
1,500+ Curated Rules. Zero Guesswork.
ARIAS ships with a comprehensive, continuously updated knowledge base covering the most critical standards and frameworks for AI governance. Every finding is backed by a specific rule, evidence, and recommended resolution.
OWASP LLM Top 10
Full coverage — prompt injection, insecure output handling, excessive agency, and more.
EU AI Act Requirements
Rules mapped to EU AI Act obligations for high-risk AI systems, transparency, and conformity assessment.
NIST AI RMF Controls
Alignment with the NIST AI Risk Management Framework across govern, map, measure, and manage functions.
Custom Organizational Rules
Business and Enterprise plans support custom rule sets tailored to your organization's internal policies.
Your Agents, Read Through the Auditor's Lens
Engineering and risk teams describe the same agents in different languages. Compliance Posture projects the findings ARIAS already maintains through the control framework your auditors actually use — so the evidence arrives without a translation round.
For every control in every framework, the dashboard shows whether the agents in scope are aligned, partially aligned, or have a gap — and which specific findings produced that status. Alignment is tracked scan over scan, so a control that regresses surfaces as a change rather than a discovery during audit preparation.
Evidence exports in OSCAL format and posts webhook events on status change, so it lands in the GRC platform your risk team already runs rather than in a spreadsheet someone rebuilds each quarter.
EU AI Act
NIST AI RMF
ISO/IEC 42001
SOC 2
GDPR
OWASP LLM Top 10
OWASP Agentic Top 10
MAESTRO
Included with Enterprise; available as an add-on on Business plans. See pricing.
Change Impact Analysis — Test What Actually Changed
Stop Testing Everything. Start Testing What Matters.
When an agent changes, your QA team faces an impossible choice: test everything (slow, expensive) or test nothing (risky). ARIAS eliminates this dilemma with Change Impact Analysis — available on the Enterprise plan.
When an agent's behavioral fingerprint drifts, ARIAS identifies exactly which component changed — Goal, Tools, Memory, Orchestration, or Error Posture — and generates a targeted test scope based on that specific drift. No more guessing, no more regression anxiety.
Drift Detected
ARIAS identifies a behavioral fingerprint change in your agent between commits.
Component Classified
The specific behavioral dimension (e.g., Tools permission scope) is isolated.
Test Scope Generated
ARIAS surfaces the exact test cases relevant to the changed component.
Confidence Restored
Your team ships with a precise, traceable validation record — not a gut feeling.
Supported Agentic AI Frameworks
ARIAS detects and analyzes agents built on 35+ frameworks — covering the full spectrum of the modern agentic AI ecosystem. If your team is building with it, ARIAS can scan it.
Agent Orchestration
LangChain, LangGraph, AutoGen, CrewAI, DSPy, Haystack, LlamaIndex, Pydantic AI, MetaGPT, CAMEL-AI, Smolagents, LangChain4j
Model Providers & SDKs
OpenAI, Anthropic, Semantic Kernel, NVIDIA NeMo, NVIDIA NIM, Guidance
Cloud & Enterprise Platforms
AWS Bedrock, Azure AI, Google Vertex AI, Databricks, Snowflake Cortex, Salesforce, ServiceNow
Agent Protocols
Model Context Protocol (MCP) and Agent-to-Agent (A2A) — detected as first-class integration surfaces, including the delegation paths they open between agents.
Low-Code & Emerging
Cloudflare Agents, Agno, AutoGPT, BabyAGI, TaskWeaver, n8n, Flowise, Dify
Spec-Driven Development
GitHub Spec Kit (.specify/ projects). Plus universal spec ↔ agent traceability across Claude Code subagents, Anthropic Skills, CrewAI YAML, and any future spec format.
Don't see your framework? ARIAS's detection engine is continuously expanding. Contact the team for custom framework support on Business and Enterprise plans.
Built for Engineering Teams Who Ship Fast
ARIAS doesn't slow down your deployment velocity — it protects it. By automating behavioral analysis and certification at the CI/CD layer, ARIAS removes the manual review burden from engineers and gives leadership the audit trail they need for compliance.
Frameworks Supported
Comprehensive detection across the agentic AI ecosystem
Maturity Dimensions
Every agent scored across a structured behavioral model
Curated Rules
Mapped to OWASP, NIST, EU AI Act, and custom policies
Command to Install
Zero infrastructure overhead, runs entirely local or in CI/CD
Ship Your Agents With Confidence
Every day agents reach production without a behavioral baseline is a day your team is shipping without a safety net. ARIAS gives you the visibility, certification, and CI/CD enforcement to build agentic AI with confidence — starting with a single command.
Install in 60 Seconds
One curl command. No cloud account required. Start scanning your first agent immediately.
curl -sL https://app.tryarias.com/install | shRequest a Demo
See ARIAS scan a real agent codebase live — including ABF generation, drift detection, and CI/CD gate configuration.
Enterprise Evaluation
Working at scale with multiple agent systems? Talk to the team about Enterprise plans with Change Impact Analysis and custom rules.