Now in Private Beta

The Trust Platform for the AI Agent Economy

Runtime behavioral safety, compliance, and identity for autonomous AI agents. The SSL/TLS of the agent era.

pip install agenttrust → ⭐ GitHub See the Platform
AgentTrust — Runtime Trust Platform for AI Agents
AgentTrust Dashboard — Real-time Merkle Tree audit logging, trust score monitoring, and threat detection for AI agents
🔍 Click to enlarge
▲ Live demo: Finance Agent Under Attack — Merkle tree audit logging, BSAD threat detection, graduated response

$30B

Agent Safety TAM by 2028

$50M+

Agent Incident Damages in 2025

<5ms

Monitoring Overhead

3 Lines

To Integrate

⚠ The Problem

AI agents are shipping
without a trust layer

Agents are the new software — but there's no SSL, no certificate authority, no security infrastructure. Real incidents are already happening.

✈️

Air Canada Chatbot

Fabricated a bereavement discount policy. Company held legally liable for the AI's promises. Cost: lawsuit + reputational damage.

🚗

Chevrolet Dealer Bot

Agreed to sell a $76,000 Tahoe for $1 after a prompt injection attack. The "binding agreement" went viral.

💰

Enterprise Agent Failures

Fortune 500 companies report agents sending wrong pricing, accessing unauthorized data, and making erroneous financial transactions. Est. $50M+ damages in 2025.

Why existing solutions fail for agents

Built for chatbots, not for autonomous multi-step agent workflows.

Current Approach Why It Fails for Agents
Prompt Guardrails (Lakera) Agents execute multi-step workflows — injection can happen at any step, through any tool
Model Security (Protect AI) The model is fine; the agent's behavior is the risk
Governance Platforms (Credo AI) Static compliance doesn't work for real-time autonomous decisions
Evaluation Tools (Patronus AI) Pre-deployment evals can't catch runtime behavioral drift
🛡️ The Platform

Four layers of
agent-native trust

Comprehensive runtime safety built specifically for autonomous AI agents.

Layer 1

AgentObserve

"Datadog for AI agents"

Full behavioral tracing for every agent action. Integration in 3 lines of code. Async monitoring with near-zero performance impact.

⚡ <5ms overhead
Layer 2

AgentProtect

"Real-time behavioral firewall"

Graduated response system — not binary block/allow. Monitors action sequences for anomalous patterns. Automatically isolates compromised agents.

🔒 <20ms sync latency
Layer 3

AgentComply

"Continuous compliance engine"

Automated EU AI Act, NIST RMF, and ISO 42001 compliance. Continuous monitoring, not point-in-time audits. Board-ready AI risk dashboards.

📋 Real-time audit trail
Layer 4

AgentIdentity

"SSL certificates for AI agents"

Cryptographic agent identities, trust scoring based on behavioral history, cross-agent trust verification. Open protocol with commercial management.

🔐 Metcalfe's Law moat
🏗️ Why This Is a Category

Not a feature.
A platform.

When cloud emerged, people asked "Won't AWS add security?" They did — but CrowdStrike ($80B), Palo Alto ($125B), and Zscaler ($30B) were built because enterprises need specialized, neutral security.

🌐

Cross-Platform

Agents are multi-framework, multi-model, multi-cloud. Enterprises need cross-platform safety.

🎯

Specialized

Generic guardrails can't keep up with agent-specific behavioral threats. Deep expertise wins.

⚖️

Neutral

You can't trust the AI provider to audit their own model's safety. Independent trust is essential.

📈

Data Flywheel

Every monitored agent improves anomaly detection for all customers. CrowdStrike/Datadog dynamics.

📊 Market

A $30B market
forming right now

100,000 enterprises will deploy AI agents by 2028. Every one of them needs trust infrastructure.

$30B

Bottom-up TAM: 100K enterprises × $300K avg safety spend

$1.5B

Addressable today: 15K enterprises × $100K avg spend

42% CAGR

AI safety market growth rate 2024-2028

⏰ Why Now

Four converging forces

The window for building the trust layer is open right now — and closing fast.

🤖 Agentic AI Inflection

Salesforce shipped 2B+ Agentforce transactions. Microsoft Copilot agents are in production. Anthropic's MCP ecosystem is exploding. Agents aren't coming — they're here.

🔗 Protocol Emergence

MCP and A2A are creating agent-to-agent infrastructure — but with zero trust layer. It's HTTP without HTTPS. The SSL moment is now.

⚖️ EU AI Act Deadline

Full enforcement August 2026. Every company deploying AI agents in Europe must prove compliance. This is mandatory, not optional.

💰 M&A Validation

Cisco acquired Robust Intelligence. F5 acquired CalypsoAI. Enterprise security vendors are buying AI safety companies — proving the exit path.

📈 Financial Projections

Path to $400M ARR

Conservative projections based on comparable company trajectories (CrowdStrike, Datadog, Palo Alto Networks early growth).

Year ARR Customers Gross Margin
Year 1 $3M 20 68%
Year 2 $18M 80 74%
Year 3 $65M 300 80%
Year 4 $180M 700 84%
Year 5 $400M 1,500 87%

🏢 Strategic M&A (2028-29)

$500M – $2B

Palo Alto Networks, CrowdStrike, Microsoft, Salesforce

🚀 IPO Path (2030-31)

$5B – $10B

At $400M+ ARR with 87% gross margins

Ready to trust
your agents?

Join the private beta. Ship AI agents with confidence.

pip install agenttrust → ⭐ View on GitHub Contact Us