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KEMSafe
Private pilot access

The action firewall for autonomous AI agents.

KEMSafe verifies identity, permissions, intent, and risk before AI agents touch real business systems.

API keys prove who connected. KEMSafe verifies what the agent is about to do and why.

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AI Agent
autonomous caller
KEMSafe Gateway
verifying
Identity
Capability
Intent
Risk
ApprovedHuman reviewBlocked
Business API
downstream system
identity · capability · intent · riskverified before execution

Designed for agents operating across the tools businesses already depend on.

Problem

Autonomous software is crossing the boundary from chat to action.

AI agents are beginning to send emails, update CRMs, export customer data, trigger payments, and operate internal tools. But most systems still treat a valid API key as proof that an action is safe. That assumption breaks when the decision-maker is an AI agent reading untrusted inputs.

Valid credentials, wrong action

A manipulated agent can use legitimate access to perform harmful actions. Authentication proves the caller is known. It does not prove the action is safe.

Prompt injection reaches tools

Invoices, tickets, emails, documents, and web pages can carry hidden instructions that influence an agent before it calls a real system.

No audit of intent

Most systems log what happened after execution. They do not verify why the agent acted before execution.

Product

Verify every high-risk agent action before it executes.

KEMSafe sits between autonomous agents and business APIs. It checks whether an action should be allowed, reviewed, blocked, or quarantined before the downstream system is touched.

Agent identity

Give every agent a cryptographic identity with short-lived sessions, revocation, and clear ownership.

Capability boundaries

Define exactly what each agent is allowed to do. Attempts outside the approved scope are blocked before execution.

Proof-of-Intent

Require risky actions to carry structured evidence: the intended action, reasoning, confidence, input hash, timestamp, and context.

Behaviour checks

Compare each action against expected patterns. Unusual amounts, frequencies, targets, or workflows can trigger review.

Human approval

Route sensitive or uncertain actions to a human decision queue instead of letting the agent act blindly.

Audit trail

Log every decision with the agent, action, policy result, risk signals, reason, and timestamp.

How it works

A control plane between agents and business systems.

  1. Agent requests an action
  2. KEMSafe verifies identity and capability
  3. Risky actions include Proof-of-Intent
  4. Policy returns approve, review, block, or quarantine
  5. Decision evidence is logged for audit
kemsafe-gateway.tsnode
// verify a high-risk action before it executes
await kemsafe.verify({
  agent: "invoice-agent",
  action: "payment.request",
  amount: 48000,
  reason: "Invoice matched contract VC-2024-089",
  inputHash: "sha256:..."
});
approved— policy matchreview— amount above thresholdblocked— prompt-injection signal

Approved actions continue. Suspicious actions stop before they reach the downstream API.

Use cases

Built for the first wave of agentic business workflows.

Invoice and payment agents

Block prompt-injected invoices, unusual payment amounts, spoofed agents, and actions outside the approved payment policy.

Customer support agents

Review refunds, account changes, sensitive replies, and customer data access before an agent takes irreversible action.

Sales and CRM agents

Control lead updates, bulk exports, customer record edits, and outbound messages from autonomous sales workflows.

Data export agents

Prevent unsafe exports of customer, financial, or operational data when an agent is influenced by untrusted context.

DevOps and code agents

Add an approval and audit layer before agents modify production systems, secrets, repositories, or deployment workflows.

Internal automation agents

Give teams a safety boundary for agents that operate across Slack, email, spreadsheets, CRMs, and internal tools.

Security architecture

Deterministic first. AI-assisted only when useful.

KEMSafe should not put an LLM in the default critical path. Routine actions should be checked with deterministic controls such as identity, capability, policy, revocation, and trust state. High-risk actions can trigger deeper Proof-of-Intent analysis, anomaly checks, and human review.

Fast path

Routine actions

  • Agent identity
  • Capability policy
  • Revocation
  • Trust gate
  • Audit event

Designed for low-latency verification.

Risk path

High-risk actions

  • Proof-of-Intent
  • Prompt-injection signals
  • Behaviour anomaly
  • Human review
  • Quarantine decision

Used when the action can create business, financial, operational, or compliance risk.

Demo

See the failure before it becomes damage.

A payment agent reads an invoice. The invoice contains a hidden instruction telling the agent to ignore policy and transfer funds urgently. The API key is valid. The payment endpoint would accept the call. KEMSafe catches the mismatch between the input, reasoning, and requested action — then blocks or routes it to review.

Clean invoice

Approved

The agent identity is valid, the amount matches the contract, and the action stays within policy.

Spoofed agent

Blocked

The request fails identity verification before reaching the downstream API.

Prompt-injected invoice

Quarantined

The agent attempts a risky payment based on suspicious instructions inside the input document.

Thesis

The trust layer for autonomous software

AI agents are becoming operators. They need more than API keys. They need identity, permission boundaries, intent verification, and runtime control.

Read the thesis
“

API keys prove access. They do not prove judgment.

Building agents that can act?

Talk to us before they touch real systems.

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