How does AegisMesh handle Human-in-the-Loop (HITL)?

AegisMesh intercepts mutating actions taken by AI agents and parks them in an Infinispan-backed cache. The execution is suspended until a verified human explicitly approves the action.

How does AegisMesh reduce LLM API costs?

AegisMesh utilizes Semantic Prompt Caching. It understands the context of a prompt using vector embeddings and instantly serves cached answers for conceptually similar questions.

AI Governance & LLM Edge Proxy

Integrating Multi-Agent Frameworks can lead to high API costs, FinOps unpredictability, and severe security risks. AegisMesh acts as an intelligent AI Platform Gateway, bringing strict oversight to autonomous agent behavior.

Human-in-the-Loop (HITL) Execution

Allowing autonomous agents to freely execute state-changing actions presents a catastrophic risk. AegisMesh natively intercepts sensitive Model Context Protocol (MCP) tool calls (like wire transfers or database mutations) and safely parks the payloads in a clustered Infinispan cache. The AI's task is suspended until a verified human operator explicitly approves the payload via the control plane, ensuring ultimate safety.

FinOps Chargebacks & Token Budgets

Uncontrolled multi-agent scaling leads to billing surprises. Using native OpenTelemetry GenAI semantics, AegisMesh tracks and aggregates precise Token-Per-Minute (TPM) consumption cross-referenced by OIDC Agent Identity and Tenant boundaries. It actively enforces budget limits dynamically to prevent runaway cloud provider costs and alerts on unauthorized LLM Shadow IT.

Instant Semantic Prompt Caching

Standard exact-match caching fails for AI because agents ask the same questions using different phrasing. AegisMesh understands the actual semantic meaning behind a prompt. It instantly serves cached answers for conceptually similar questions, drastically reducing external OpenAI/Anthropic API costs and eliminating inference latency.

Prompt Injection Defense & Data Isolation

AegisMesh acts as an AI Firewall. Natively executing external process (ExtProc) ML analysis, it identifies and intercepts malicious Indirect Prompt Injections before they reach your internal Agentic Frameworks. Furthermore, all retrieved RAG context is strictly isolated by Tenant ID and GitOps RBAC roles, guaranteeing that sensitive information retrieved by an executive never leaks to a guest user.