Moving from Opaque Black Boxes to Secure, Transparent, and Trustworthy AI Architectures
Watch how Beddel transforms enterprise AI security
A comprehensive architecture for enterprise AI

Agent code executes in a secure, lightweight environment (like a V8 Isolate) completely separated from the host system, preventing "VM escape" and unauthorized access.

Declarative inputs (like YAML files) are strictly validated against a secure schema at the entry point, blocking injection attacks and resource-exhaustion attempts like "YAML Bombs".

Every agent action is recorded in a tamper-proof log using hash-based chaining, creating a non-repudiable audit trail that is essential for regulatory compliance.

The system performs static analysis and risk scoring on agent definitions before execution, allowing high-risk or non-compliant workflows to be automatically blocked or flagged for human review.

Declarative languages focus on the sequence of steps, creating a transparent, human- and machine-parseable workflow. Schema Validation (e.g., with Zod) ensures reliability and catches errors early.

The architecture has dedicated modules for global regulations like GDPR and LGPD, with built-in helpers for data anonymization. Ensures complete data and process isolation between different clients in a SaaS environment.

Security does not require sacrificing speed. A lightweight, efficient architecture enables auto-scaling and low latency (<10ms), making it suitable for mission-critical, high-traffic applications.
Building for Clarity and Control
Opaque & Hard to Maintain
// 500+ lines of complex code
agent.on('message', async (ctx) => {
const tools = await loadTools();
// Complex nested callbacks...
// Hard to audit & maintain
});Transparent & Auditable
# Clear, auditable YAML
agent:
name: "assistant"
steps:
- validate: input
- process: query
- respond: outputCatches Errors Early
By using strict, type-safe schema validation (e.g., with Zod), a declarative framework can catch configuration errors early, preventing runtime failures and vulnerabilities caused by incorrect inputs.
{
schema: {
type: "string",
data: data
}
}