SigmaShake vs Wattfare

Generative AI agent guardrails mapped to MITRE ATLAS AML.M0020: deterministic ALLOW, DENY, ASK, FORCE at the tool-call boundary. Honest-agent. Not a sandbox.

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you.

About SigmaShake

Generative AI agent guardrails mapped to MITRE ATLAS AML.M0020: deterministic ALLOW, DENY, ASK, FORCE at the tool-call boundary. Honest-agent. Not a sandbox. SigmaShake (ssg) checks every AI agent tool call against your rules before it runs, so risky actions can be blocked or rewritten in milliseconds, without a sandbox. AI agents run shell commands, edit files, and call external APIs. That means they can cause real damage before you realise what happened. It was completing a task "helpfully." The replies came in fast.

About Wattfare

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you. OpenAI-compatible Works with the Vercel AI SDK ~5-min integration. One button connects a user's inference budget to your app, metered, capped, and revocable. The problem AI costs are the one line item you can't predict. Every AI app makes the same uncomfortable bet: price high enough to survive your power users, ration usage so nobody hurts you, or quietly lose money on the heavy ones.