Original Summary

Most agent tooling I see is observability: traces, evals, alerts. Useful, but by the time an alert fires, the agent has already sent the email, run the query, or moved the money. We're building a runtime authorization layer that sits between agents and their tools instead. Rough shape: Every tool call and API request goes through a proxy (Envoy-based gateway/sidecar), so the agent has no network route to tools except through it Each action is checked against policies-as-code (spend limits, data boundaries, action allowlists) and returns allow, deny, or "ask a human" before it executes Decisions are written to an append-only, hash-chained, signed log you can replay offline Self-hosted (your VPC or air-gapped) and framework-agnostic (LangChain, CrewAI, MCP, homegrown) Where I'm least sure, and where I'd love input: Proxy vs SDK hooks. A network proxy gives mandatory enforcement, but an SDK gives semantic context (a refund vs a lookup). Is anyone running both? Policy model. Spend caps and allowlists are easy. How do you express something like "this agent can read customer records, but never in a session where it also has outbound email"? Human-in-the-loop. How do you defer to a human without approval fatigue making the agent useless? What have you tried that failed? Disclosure: I'm a co-founder at Unified AI (unified-ai.app). I'm not selling anything here. We're looking for a few teams in regulated industries to be design partners, but right now I mostly want to know whether we're solving a problem people actually have. Happy to answer questions, and my co-founder will jump in on the infra details.   submitted by   /u/Fresh_Spread_9223 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/19 19:50:31