Alternatives
Products that do what BoundrixAI does
The AI Firewall Your Enterprise Demands
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Block prompt inject & cut token costs for AI browser agents
Jun 2026 · github.com
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ArgusAI ▲7AI firewall for LLM calls, MCP tools, and agentic workflows
Jul 2026 · argusai-tau.vercel.app
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I work as a SAP Integration consultant and built this as a side project. Friction point: Most self hosted LLM observability tools require Postgres, Redis and non trivial infrastructure. Teams just want to see what their agents are actually doing in Production, that set up cost discorages adoption. Torrix runs as a single docker contained backed by SQLite. The full install is: curl -o docker-compose.yml https://raw.githubusercontent.com/torrix-ai/install/main/doc... docker compose up No external dependencies. All data stays in a local SQLite file on your machine.…
May 2026 · github.com
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"Your LLM's last line of defence against the internet."
May 2026 · wonderwallai.skintlabs.ai
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Much of my work right now involves complex, long-running, multi-agentic teams of agents. I kept running into the same problem: “How do I keep these guys in line?” Rules weren’t cutting it, and we needed a scalable, agentic-native STANDARD I could count on. There wasn’t one. So I built one. Here are two open-source protocols that extend A2A, granting AI agents behavioral contracts and runtime integrity monitoring: - Agent Alignment Protocol (AAP): What an agent can do / has done. - Agent Integrity Protocol (AIP): What an agent is thinking about doing / is allowed to do. The problem:…
Feb 2026 · mnemom.ai
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The ultimate Agentic Firewall & Telemetry Proxy for LLMs.
Jun 2026 · synapse-proxy.com
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We're excited to launch compliant-llm: an open-source toolkit that helps infosec and compliance teams audit AI agents against regulatory frameworks like NIST AI RMF, ISO 42001, and OWASP Top 10. Infosec and compliance teams are now responsible for tracking security and compliance risks of a growing number of AI agents across external and internal apps and third-party vendors. compliant-llm gives you a way to: - Define and run comprehensive red-teaming tests for AI agents - Maps test outcomes to compliance frameworks like NIST AI RMF - Generate detailed audit logs and documentation -…
2025 · github.com
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Hey HN, Sascha here, developer of OkaiDokai. Like many others, I fell in love with OpenClaw, but was longing for more control over what it can do without interrupting its autonomous, agentic nature. OkaiDokai solves this for me by allowing me to set up my own rule set of what is allowed by default, what is not, and what it should ask permission for. It comes with a hosted API, web and native apps including push notifications (with quick-response support), plugins for OpenClaw and Claude Code, and soon Codex. I'm still working on getting the apps onto the App Store (currently on TestFlight…
Feb 2026 · okaidokai.com
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Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…
Oct 2025 · archestra.ai
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