AgentStackPro: An OS for AI Agents
Langsmith + Temporal + OPA + Others — Unified for AI Agents
3 followers
Langsmith + Temporal + OPA + Others — Unified for AI Agents
3 followers
AgentStackPro is the all-in-one platform for teams building with autonomous AI agents. 🔍 Observe — Distributed tracing, session replay, cost analytics 🛡️ Govern — Constitutional policies, PII guardrails, human-in-the-loop approvals ⚡ Orchestrate — Durable workflows with DAG execution, crash recovery 🧪 Evaluate — Dataset-driven experiments, AI-powered scoring Drop-in TypeScript and Python SDKs. 2-minute setup. Free tier available. Built for the teams who need more than just LLM tracing
Hi Product Hunt! 👋 I am incredibly excited to introduce AgentStackPro to the community today.
Building a single AI agent is a fun experiment. But when you try to deploy dozens of them in a real-world production environment, you quickly hit a wall. Suddenly, you have no visibility into what they are doing, no guardrails to stop them from going rogue, and you are forced to stitch together 5 or 6 different tools just to track costs, orchestration, and compliance.
It is a logistical nightmare. That is exactly why I built AgentStackPro.
I wanted to create a single, unified command center that replaces the entire fragmented AI operations stack. With AgentStackPro, you can finally scale your AI workforce with total confidence.
Here is how we bring order to the chaos:
🕵️♂️ See Everything: Track token costs down to the penny, view distributed traces, and watch full session replays so you never have to guess what your agents are up to.
⚙️ Build Unbreakable Workflows: Coordinate multiple agents with durable workflows that automatically recover from crashes and pick up exactly where they left off.
🧠 Understand the "Why": Track every single decision your agent makes. If it selects a specific model, sub-agent, or MCP tool, you will see the exact reasoning behind why it made that choice.
Hashed Matrix Policy Gates: Instead of basic allow/block lists, it uses a hashed matrix system for action-level policy gates. This gives you cryptographic integrity over rate limits and permissions, ensuring agents cannot bypass authorization layers.
Deterministic Business Logic: This is the biggest differentiator. Instead of relying on prompt engineering for critical constraints, we use Decision Tables for structured business rule evaluation and a Z3-style Formal Verification Engine for mathematical constraints. It verifies actions deterministically with hash-chained audit logs—zero hallucinations on your business policies.
Smart Tool Deduplication: Hash-based detection instantly catches and stops agents from making duplicate MCP tool calls, saving you massive token costs and processing time.
Drift & Bias Detection: Real-time monitoring ensures your agents stay on-brand, alerting you instantly to hallucinations, behavioral drift, or bias over time.
Persistent Skills & Memory: Give your agents long-term recall. The system dynamically updates and retrieves context across multiple sessions, allowing agents to store reusable procedures (skills) and remember past interactions without starting from scratch every time.
Fast Setup: Drop-in Python and TypeScript SDKs that literally take about 2 minutes to integrate via a secure API gateway (no DB credentials exposed).
Interactive SDK Playground: Before you even write code, they have an in-browser environment with 20+ ready-made templates to test out their TypeScript and Python SDK calls with live API interaction.
We are bringing observability, governance, evaluations, and orchestration into one seamless platform.
I would absolutely love to hear your thoughts, answer any questions about the tech stack, and get your feedback on how we can make this even better.
Let me know what you think in the comments! 👇
Bringing full observability and 50+ production ready Agentic AI tools to OpenClaw 🦀 (Beta Release)
If you are building agents with OpenClaw, we just made it a lot easier to make them production-ready. We’re rolling out the beta version of the AgentStackPro OpenClaw plugin.
Instead of writing manual SDK calls for tracing and governance, you can just link this plugin. It uses OpenClaw's native lifecycle hooks (before_llm_call, after_llm_call, etc.) to automatically handle:
Zero-config observability: Traces, spans, latency, and token costs logged automatically.
50+ native tools: Your agents can instantly use our tools for durable workflows, DMN decision tables, PII detection, and human-in-the-loop approvals just by prompting them naturally.
🧪 Beta Disclaimer: We are releasing this early to get it into your hands. While the core features are working smoothly, it is still in beta and hasn't been completely stress-tested in all edge cases. Expect a few bugs, and please report them so we can squash them!
Check out the app and docs to try it out.