EgisAI is a runtime control plane designed for governance and oversight of AI agents operating in production environments. Its core function is to act as an intermediary between AI agents and the external world, enabling organizations to block destructive tool calls, mask personally identifiable information (PII), and maintain a comprehensive audit of every agent action. The platform addresses the risks associated with unauthorized agent behavior, data leakage, and compliance requirements by providing real-time policy enforcement and observability.
The tool integrates with a broad range of AI frameworks and libraries, including OpenAI, Anthropic, Gemini, Bedrock, LangChain, CrewAI, AutoGen, and more, requiring only a single line of code to initialize. Once active, EgisAI automatically detects and fingerprints every agent in a codebase based on their system prompts, eliminating the need for manual registration or agent IDs. It generates behavioral fingerprints for each agent and end-user, capturing cadence, model affinity, tool-call signatures, and prompt-shape histograms. Anomaly detection is performed using Z-score drift analysis across multiple dimensions, which helps identify model degradation, prompt-injection campaigns, and runaway loops, with severity grading and plain English narration.
EgisAI assigns a trust score to each agent, derived from factors such as provenance, cadence, anomaly density, and policy alignment, allowing teams to quickly identify risky or rogue agents. The platform also features behavioral twin detection, which uses cross-agent similarity scoring to flag new agents exhibiting suspiciously similar behaviors, such as those created after SDK key leaks. Its two-phase policy engine applies local deterministic rules first—covering PII, regex patterns, model allow-lists, and prompt sizes—before invoking LLM-based semantic guards if necessary, ensuring that sensitive data never leaves the local process. Policy updates are delivered in real time via server-sent events, and the system is designed to fail open on availability but fail closed on PII-related issues.
Pre-dispatch enforcement is supported for various operations, including tool calls, shell commands, database queries, and financial actions, physically blocking them before execution if they violate policy. EgisAI maintains an append-only audit trail with run-level identity stamping and rule-based verdicts, supporting the generation of evidence packets for compliance standards such as SOC 2, ISO 27001, and HIPAA. The platform is positioned as a solution for teams deploying AI features who require robust runtime governance, policy enforcement, and auditability across diverse AI agent frameworks.
In the LLM eval & observability space, EgisAI takes a focused approach. It focuses on ensuring safe, compliant, and auditable operation of AI agents in production environments. EgisAI is a B2B product aimed at AI operations teams and compliance officers. Pricing is paid. EgisAI is available on the web, the command line, and API.
It is developed by EgisAI, and the product first shipped in 2026. The project is developed in the open on GitHub with 40 commits in the last 90 days. Across PulseGate's embedding index, EgisAI has few near neighbours, marking it as relatively distinct. Among its 5 catalogued features are policy enforcement, PII masking, and audit trails. It exposes integrations via a public API.
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