Knownbase vs SigmaShake

Stop re-explaining your codebase to AI. Knownbase gives Claude Code, Codex and MCP agents persistent project memory that survives every session.

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.

About Knownbase

Stop re-explaining your codebase to AI. Knownbase gives Claude Code, Codex and MCP agents persistent project memory that survives every session. Knownbase gives your AI coding agents persistent, searchable project knowledge, so architecture decisions, debugging discoveries, conventions and lessons survive across sessions and tools. Works with Claude Code, Codex, Cursor, ChatGPT and any MCP-compatible agent. They're storage failures: the agent learned something real and had nowhere durable to put it. Compaction loses the discoveries The context gets compacted mid-task and the hard-won finding from two hours ago is summarized down to nothing.

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.