AI Agent Guardrails that block destructive tool calls and enforce rules for AI coding agents.
SigmaShake
AI Agent Guardrails that block destructive tool calls and enforce rules for AI coding agents.
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What it does
SigmaShake provides deterministic guardrails for AI agents, acting as a critical safety layer for your codebase. It actively blocks destructive commands, prevents data loss, and stops secret leaks before an AI agent can execute them, all in under 2 milliseconds. The platform enforces declarative rules and maintains a signed audit trail for every agent action, offering a robust solution for security and compliance in AI-driven development. It's designed to be the "seatbelt, airbags, and dashcam" for your AI agent, ensuring safe and auditable operations.
Who it helps
Developers, engineering teams, and organizations deploying AI coding agents who need to prevent data loss, secret leaks, and ensure secure, auditable agent operations within their development workflows.
Why it's interesting
SigmaShake addresses a critical and growing pain point in the adoption of AI agents: security and reliability. Its benchmarked performance, achieving a 98.2 SHAKEDOWN score, demonstrates superior containment of rogue agents without breaking legitimate work. The deterministic, low-latency evaluation (under 2ms) and the ability to guide rather than just block make it a compelling solution for enterprises seeking to safely integrate AI into their operations.
Card stats
AI-assisted scores estimated from public website information only.
FounderDeck estimate
Medium confidenceThis FounderDeck estimate of $2,000,000 reflects SigmaShake's highly polished product, which solves a critical and timely problem in the rapidly expanding AI agent market. The explicit benchmarked performance (SHAKEDOWN score) provides strong validation and differentiation, indicating a robust, high-value solution for businesses. While early traction (NPM downloads) is visible and the B2B SaaS monetization path is clear, the estimate remains at this level due to the absence of explicit public revenue figures, customer testimonials, or team information that would support a higher valuation.
Valuation date: 2026-06-05. Estimate generated from public signals.
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