Traditional API gateways break when AI agents talk via MCP or A2A. Agentic Edge Proxy sits transparently on the wire to govern FinOps, cache redundant tools, and redact PII—without blocking your multi-agent workflows.
Enterprise AI adoption is stalled by two massive blind spots: spiraling un-attributable inference costs and the "Shadow AI" data egress hazard.
Global LLM API spending is surging. Agents stuck in loops burn hundreds of dollars an hour. Our 4-Layer Token Attribution explicitly separates context, tools, and memory, applying a per-tenant Runtime Kill Switch.
Why pay an LLM to re-evaluate the same database query? We use blake3 to hash the underlying JSON-RPC intent (ignoring trivial metadata) to instantly serve L1 cached responses.
Relying on DLP tools is insufficient. Our engine deobfuscates shell hex encodings and runs synchronous regex redaction inline, masking PII before it ever hits a public API.
Traditional proxies only understand standard HTTP routes. When agents communicate using the Model Context Protocol (MCP) or Agent-to-Agent (A2A), typical reverse proxies go blind.
Deep packet inspection to intercept the true intent of autonomous actions.
Compiled in pure Rust to eliminate garbage collection pauses on the critical path.
async fn handle_proxy(req: Request) -> Response {// 1. Synchronous AgentTrust Filterlet deobfuscated = deobfuscate_shell(&payload);redact_pii(&mut deobfuscated);// 2. Blake3 Semantic Cachingif let Some(res) = cache.get(hash) {return Ok(res);}// 3. Fast Streaming (SSE) to Agentlet stream = upstream.bytes_stream();process_response_body_async(stream).await;}