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Products that do what TAB Platform does

The independent verification layer for AI agents

  1. 1OA

    Scored 65.2% vs google's official 47.8%, and the existing top closed source model Junie CLI's 64.3%. Since there are a lot of reports of deliberate cheating on TerminalBench 2.0 lately (https://debugml.github.io/cheating-agents/), I would like to also clarify a few things 1. Absolutely no {agents/skills}.md files were inserted at any point. No cheating mechanisms whatsoever 2. The cli agent was run in leaderboard compliant way (no modification of resources or timeouts) 3. The full terminal bench run was done using the fully open source version of the agent, no…

    Apr 2026 · github.com

  2. 2
    oqoqo340

    Build evals and custom benchmarks for real-world tasks

    28d ago · oqoqo.ai

  3. 3

    An open benchmark for AI agents that test APIs

    May 2026 · resources.kusho.ai

  4. 4

    Your site scores X/100 for AI agents with next steps

    May 2026 · indexedai.tech

  5. 5
    0xAudit110

    The security layer for AI agents to scan, fix verify via MCP

    Feb 2026 · 0-x-audit.com

  6. 6TB

    After training calculator agent via RL, I really wanted to go bigger! So I built RL infrastructure for training long-horizon terminal/coding agents that scales from 2x A100s to 32x H100s (~$1M worth of compute!) Without any training, my 32B agent hit #19 on Terminal-Bench leaderboard, beating Stanford's Terminus-Qwen3-235B-A22! With training... well, too expensive, but I bet the results would be good! *What I did*: - Created a Claude Code-inspired agent (system msg + tools) - Built Docker-isolated GRPO training where each rollout gets its own container - Developed a multi-agent…

    2025 · github.com

  7. 7

    Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…

    Jul 2026 · oodle.ai

  8. 8

    The Only AI Tool That Doesn't Trust AI

    Mar 2026 · triall.ai

  9. 9OS

    GitHub - https://github.com/vostride/agent-qa Live Demos - https://vostride.com/demo/agent-qa

    May 2026 · vostride.com

  10. 10EY

    I built an open-source AI agent for security testing to find and fix vulnerabilities in your code. I’ve noticed how bad security vulnerabilities have gotten with everyone shipping AI code slop, so I wanted to build something that allows for vibe-coding at full speed without compromising security. Traditional security tools aren’t effective, and manual pen-testing can’t keep up with the rapidly growing AI code This tool runs your code dynamically, finds vulnerabilities, and validates them through actual exploitation. You can either run it against your codebase or enter your (or someone…

    2025 · github.com

  11. 11OS

    We build runtime security for AI agents. The playground started as an internal tool that we used to test our own guardrails. But we kept finding the same types of vulnerabilities because we think about attacks a certain way. At some point you need people who don't think like you. So we open-sourced it. Each challenge is a live agent with real tools and a published system prompt. Whenever a challenge is over, the full winning conversation transcript and guardrail logs get documented publicly. Building the general-purpose agent itself was probably the most fun part. Getting it to reliably use…

    Mar 2026 · github.com

  12. 12S2

    Hey HN, We’re Suchintan and Shu from Skyvern (https://www.skyvern.com). We’re building an open source AI Agent that can browse the web and take actions. Our open source repo can be found at https://github.com/Skyvern-AI/Skyvern. We’ve re-built Skyvern with a Planner-Actor-Validator agent architecture and achieved 85.8% state of the art (SOTA) on the WebVoyager Benchmark. You can see the results for yourself here: https://eval.skyvern.com/ For reference, here were the previous SOTA results: 83.5% - Google Mariner…

    2025 · eval.skyvern.com

  13. 13AA

    Hi, I built Axiomeer, an open-source marketplace protocol for AI agents. The idea: instead of hardcoding tool integrations into every agent, agents shop a catalog at runtime, and the marketplace ranks, executes, validates, and audits everything. How it works: - Providers publish products (APIs, datasets, model endpoints) via 10-line JSON manifests - Agents describe what they need in natural language or structured tags - The router scores all options by capability match (70%), latency (20%), cost (10%) with hard constraint filters - The top pick is executed, output is validated (citations…

    Feb 2026 · github.com

  14. 14

    Keep your OpenClaw agents running. Free beta, no code change

    Apr 2026 · openinfer.io

  15. 15MD

    We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…

    2025 · github.com

  16. 16

    Benchmark AI models for YOUR use case

    Jan 2026 · openmark.ai

  17. 17AB

    Hi everyone! My team and I just open-sourced a bunch of cool agent dev tools: Invariant Explorer to visually inspect and understand AI traces and a testing framework, building on pytest.

    2024 · github.com

  18. 18

    we had hundreds of discussions with engineering leaders over the past few months, and everyone's trying to understand where they are in the AI journey. we collected all this data into a benchmark and built a free grader to let you know where you stand. you answer on a 1–5 scale (e.g., autonomy runs from "suggestions only" to "agents own multi-hour workflows across code, infra, and external systems") - takes about 5 minutes. https://agent-benchmarks.com/software-factory/ waiting for your results!

    Jul 2026 · agent-benchmarks.com

  19. 19LO

    Hi HN, Martin, Nils, and Jannes here. We are building Legit, an open source version control and collaboration layer for AI agents and AI native applications. You can find the repo here https://github.com/Legit-Control/monorepo and the website here https://legitcontrol.com Over the last years, we worked on multiple developer tools and AI driven products. As soon as we started letting agents modify real files and business critical data, one problem kept showing up. We could not reliably answer what changed, why it changed, or how to safely undo it. Today, most AI…

    Jan 2026

  20. 20VA

    Hi all, Gorkem here. I started VerifyWise [1] to make AI governance less painful. Today, we’re launching our open-source platform to help teams take control of their AI compliance process. VerifyWise helps organizations navigate AI governance by providing audit readiness, risk registers, model fairness checks, and compliance documentation. Those are all built into a single platform you can self-host. We’ve been quietly building VerifyWise for a while, and we’re now at a place where it’s ready for more teams to try. Since we started, we've: - Released our core platform on GitHub:…

    2025 · verifywise.ai

  21. 21

    Find out if ChatGPT recommends you — or your competitor

    18d ago · tabyian.com

  22. 22BA

    I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…

    Jan 2026 · fabceolin.github.io

  23. 23

    AI SEO readiness checker, built in 5 days by OpenClaw agents

    Mar 2026 · ai-readiness.mingles.ai

  24. 24AT

    Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.

    Mar 2026 · agents.zalor.ai

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