Security That Runs Inside Your AI Agents

Runtime security, governance, and live threat intelligence for every agent and every action.

"Everyone Sees What Agents Do; We See What They Think"

98.0%

DETECTION ACCURACY

<4ms

RUNTIME LATENCY

5

layer DETECTION engine

8

COMPLIANCE FRAMEWORKS

Security That Runs Inside Your AI Agents

Runtime security, governance, and live threat intelligence for every agent and every action.

"Everyone Sees What Agents Do; We See What They Think"

98.0%

DETECTION ACCURACY

<4ms

RUNTIME LATENCY

5

layer DETECTION engine

8

COMPLIANCE FRAMEWORKS

IN PARTNERSHIP WITH

THE PLATFORM

One platform. Four enforcement points.

Graph

RUNTIME PROTECTION

AI Sentinel

Runtime proxy. Every LLM API call routed through the 5-layer detection cascade. One URL change: no code rewrites. Works with OpenAI, Anthropic, Google, Cohere, Mistral, and any OpenAI-compatible endpoint.

PROTOCOL SECURITY

MCP Shield

Runtime protection for Model Context Protocol servers. Tool call interception, rug pull detection, and least-privilege enforcement. One line in mcp_config.json: every connected agent protected automatically.

Tasks
DelphiGateway event flow

THE ENFORCEMENT POINT

DelphiGateway

Sits in front of agent traffic and decides every call before it executes. Verifies who is really acting, whether that principal is permitted, and whether the request should be allowed, in single digit milliseconds. Covers legacy agents, third party agents and workloads nobody registered, with no code changes. Built on agentgateway, the Rust proxy stewarded by the Linux Foundation. Self-hosted, air-gapped if required.

AGENT GOVERNANCE

xAIDR

Extended AI Detection and Response for multi-agent systems. Every inter-agent message scanned inline before it reaches the LLM. Fleet-level behavioral correlation surfaces coordinated attack chains across agents. Shadow agents discovered automatically. Per-agent trust scores degrade on anomalous behavior. Autonomous quarantine fires when threshold breaks. Microsoft AGT-integrated.

Chart

AGENT-TO-AGENT

The attack every other tool is blind to.

The attack every other tool is blind to.

When one agent hands work to another, the message never touches a network. Your firewall cannot see it. Your gateway cannot see it. Your model guardrails never get a look. It is not that they are worse at catching it, they are structurally incapable of seeing it at all. Delphi runs inside the agents, so we read the delegation itself. An attack split across five agents and nine hops, invisible to everything watching from outside, reads as one event to us.

Watching from the network edge is the wrong place to stand. The only way to catch agent-to-agent attacks is to be inside the agent when they happen. That is where we live.

Watching from the network edge is the wrong place to stand. The only way to catch agent-to-agent attacks is to be inside the agent when they happen. That is where we live.

94.5%

detection accuracy across 500 adversarial agent-to-agent scenarios, and we published the benchmark, the first runtime A2A benchmark put in the open.

NATIVE INTEGRATIONS

Works across your agent stack.

Integration logo 1
Integration logo 2
Integration logo 3
Integration logo 4
Integration logo 5
Integration logo 6
Integration logo 7
Integration logo 8
Integration logo 1
Integration logo 2
Integration logo 3
Integration logo 4
Integration logo 5
Integration logo 6
Integration logo 7
Integration logo 8
Integration logo 1
Integration logo 2
Integration logo 3
Integration logo 4
Integration logo 5
Integration logo 6
Integration logo 7
Integration logo 8
Integration logo 1
Integration logo 2
Integration logo 3
Integration logo 4
Integration logo 5
Integration logo 6
Integration logo 7
Integration logo 8

THE FLEET LAYER

Fleet Intelligence

A single sensor sees one agent. Fleet Intelligence sees all of them at once. Every xAIDR sensor streams its telemetry to one place, where it becomes a live map of your entire agent fleet: who is running, who is talking to whom, which tools are in play, and where trust is degrading. Correlation across agents catches attack chains that no single sensor could see, a probe on one agent and an exfiltration attempt on another, recognised as one coordinated event. This is the difference between watching agents one at a time and governing them as a fleet.

One live view of every registered agent, its connections, and its trust score

Cross-agent correlation that catches attack chains spanning multiple agents

Fleet-wide trust scoring, with automatic quarantine when standing collapses

Shadow agent discovery, surfacing agents nobody registered

Every signal exportable to your SIEM

Fleet intelligence illustration

THE PLATFORM

One platform. Every layer of agent security.

From deep in-process detection to fleet-wide governance, each part solves a specific problem and delivers a specific outcome.

Fleet Intelligence dashboard

Fleet Intelligence

What it is: One live view of every agent across your estate.

The problem: A single sensor sees one agent, so attack chains that span multiple agents go unnoticed.

The outcome: Every agent, connection and trust score on one pane, with cross-agent attack chains surfaced as a single event.

THE PLATFORM

One platform. Every layer of agent security.

From deep in-process detection to fleet-wide governance, each part solves a specific problem and delivers a specific outcome.

Fleet Intelligence dashboard

Fleet Intelligence

What it is: One live view of every agent across your estate.

The problem: A single sensor sees one agent, so attack chains that span multiple agents go unnoticed.

The outcome: Every agent, connection and trust score on one pane, with cross-agent attack chains surfaced as a single event.

Expanding the fleet layer

Behaviour analytics

EARLY ACCESS

Every agent and every principal measured against its own history. Applications behave like metronomes, people are diurnal, scheduled jobs are calendars. Departure from an established pattern is a signal before anything matches a known attack.

  • Learned baselines per principal type
  • Deviation scoring on cadence, reach, tools and delegation depth
  • Feeds the existing trust score rather than blocking on its own
  • Drift classification: identity, data access, tool misuse, model behaviour

WHY DELPHI

Security that works at machine speed.

Inline. Not proxied.

The sensor runs inside each agent process. Threats are caught before the LLM call is made, not after the response arrives.

Zero infrastructure changes.

One URL change or one npm install. No new servers, no firewall rules, no changes to your existing LLM provider.

Fleet-aware governance.

Sentinel Brain correlates behavior across every agent simultaneously. A coordinated attack across three agents becomes one alert, not three separate noise events.

Cryptographic agent identity.

Every agent carries an Ed25519 cryptographic identity via Microsoft AGT integration. Unregistered agents cannot impersonate trusted ones.

Compliance evidence, automated.

Every detection event maps to specific controls across 8 frameworks. OWASP, NIST, EU AI Act, ISO 42001. Evidence generated from runtime. No manual questionnaires.

Governance policies, per agent.

Define tool whitelists, access scopes, and behavioral guardrails per agent. Policies enforced locally by each sensor. Custom content policies block hate speech, violence, and regulated advice categories.

Identity you already own

Delphi consumes identity rather than issuing it. Point the gateway at your existing provider and every token is validated offline against its published keys. No callback into your identity plane, no new dependency in the authentication path, no directory to synchronise.

Data sovereignty by design

Delphi runs entirely inside your perimeter. Self-hosted, air-gapped if you need it, with no backend and no callout in the scan path. Telemetry carries a hash and a length, not your content. Your data, and your sovereignty over it, stay yours.

THE DIFFERENCE

Not a guardrail. Not a policy engine.

Traditional tools watch for known patterns. Delphi understands intent, correlates behavior across agents, and responds autonomously. Runtime security built for systems that operate without humans in the loop.

Traditional AI security tools

Single-agent, input-only scanning

Static rules and policy configs

No visibility into agent-to-agent traffic

Compliance reports built manually

Cannot say which person an agent acted for

Revocation waits for the token to expire

Delphi Security

Fleet-level inline scanning across all agents

Intent decomposition and behavioral correlation

Full A2A message inspection and trust scoring

Runtime evidence mapped to 8 frameworks

Verified principal and full delegation chain on every call

Denied on the next request, across every agent

THE DETECTION ENGINE

Five layers. One verdict. Under 100ms.

DETECT

ANALYZE

GOVERN

L0 + L1

Pattern recognition. Intent decomposition.

Policy and DLP rules fire first: 15 PII classifiers, custom guardrails, keyword and semantic matching. Then 230+ detection rules across 9 threat families run instantly. Intent decomposition analyzes 11 ACTION+TARGET patterns including 4 built specifically for agent-to-agent scenarios. Known attack signatures caught in under 5ms.

DETECT

ANALYZE

GOVERN

L0 + L1

Pattern recognition. Intent decomposition.

Policy and DLP rules fire first: 15 PII classifiers, custom guardrails, keyword and semantic matching. Then 230+ detection rules across 9 threat families run instantly. Intent decomposition analyzes 11 ACTION+TARGET patterns including 4 built specifically for agent-to-agent scenarios. Known attack signatures caught in under 5ms.

PRICING

Runtime security for every stage.

Start free. Scale when you need to.

Developer

AI runtime security, observability, and governance for your LLM traffic. A drop-in proxy you connect by changing one base URL.

Five-layer detection cascade: regex, behavioral heuristics, ML, and LLM arbitration

Prompt injection, jailbreak, and multi-turn conversational drift detection

Bidirectional DLP: PII, secrets, and credentials redacted before they leave your system

MCP tool-call interception with OWASP LLM and NIST evidence reports

Usage and cost monitoring with a plain-language AI activity overview: every request, threat, and metric in one live dashboard

Drop-in proxy or SDK, provider-agnostic. Monitor mode by default, safe in production from day one. 100,000 API calls per month.

Enterprise

Advanced runtime security with governance, compliance, and full customization for enterprise AI deployments at scale.

Custom

Everything in Developer, across your entire agent fleet

xAIDR in-process detection: every inter-agent message scanned inline in under 20ms

Fleet-wide correlation: coordinated multi-agent attack chains surfaced as one alert

Shadow agent discovery with trust-based autonomous quarantine

Compliance evidence across 8 frameworks: OWASP, NIST, EU AI Act, and ISO 42001

Intent-based governance, cryptographic agent identity (Ed25519 and DID), per-agent tool whitelisting. Self-hosted deployment, dedicated CSM, 4hr SLA.

RESEARCH

From the lab.

Technical research, benchmarks, and product updates from the Delphi Security team.

WHITEPAPER

xAIDR: Extended AI Detection and Response for Multi-Agent Runtime Security

Whitepaper introducing xAIDR, a new category of AI security. 94.5% accuracy with 98.4% precision on a 500-prompt agent-to-agent test suite.

BENCHMARK

94.5% Accuracy on 500 Adversarial Agentic AI Attacks

How Delphi AI Sentinel achieved 94.5% accuracy and 98.4% precision on a 500-prompt adversarial test suite targeting agentic AI tool calls, MCP poisoning, and cross-agent attacks.

THE PYTHIA CHALLENGE

Can you jailbreak Delphi?

10 levels. Escalating difficulty. Our proprietary adversarial challenge lets you test the limits of the detection cascade directly. Beat all 10 levels and we will have a conversation.