nowfound

AI · May 26, 2026

Sturna.ai

The AI execution layer built for compliant industries

What it does

446+ specialist AI agents compete on every compliance task. HMAC-signed outputs. Append-only audit log. SEC 17a-4(f) ready, Reg S-P compliant, PQC-ready. Built for RIAs, CCOs, and legal teams who need AI they can explain to examiners. <18ms latency. 86% first-attempt success rate. Free tier available.

Does the same job

all alternatives →
  • Flagright AI Forensics2023 · ▲108

    The modern standard in AML compliance through AI agents

  • AIO.GEO Protocol24d ago · aiogeoprotocol.com · ▲79

    Audit AI search structure. Dry run fixes. Receipts.

  • CL
    Compliant-LLM: Audit AI Agents for Compliance with NIST AI RMF2025 · github.com · ▲11

    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 -…

  • GoderashMay 2026 · ai.goderash.com · ▲4

    The audit layer for regulated AI agents

  • VIS42Jun 2026 · vis42.com · ▲7

    AI agents for books, audit, VAT & reconciliation

  • BeaconMay 2026 · beaconone.net · ▲3

    Turn 12-month compliance workflows into weeks with AI agents

More ai this month

the category →
  • I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes&#x2F;sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.

    AI · 17d ago · simedw.com

  • Astute585

    Automate your B2B brand going viral, with new media creators

    AI · 18d ago · company-app.joinastute.com

  • Grok Bot547

    AI teammates that you can give real work to

    AI · 25d ago · x.ai

  • Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens&#x2F;sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens&#x2F;sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

    AI · 27d ago · cactuscompute.com

  • Monid474

    OpenRouter for agent tools

    AI · 6d ago · monid.ai

  • Turn website visitors into qualified pipeline

    AI · 19d ago · clarasdr.ai

Launched alongside, May 2026

the whole month →
  • Brew 905

    Like Claude design for email marketing

    AI · May 2026 · brew.new

  • Parallel agents, diff reviewer, and multi-model comparisons

    Dev tools · May 2026 · kilo.ai

  • StoreClaw805

    Grow your store profits with agents that know how to sell

    AI · May 2026 · storeclaw.ai

  • Give your agent a real number and voice to make calls.

    AI · May 2026 · pollyreach.ai

  • NW

    Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok&#x2F;s prefill and 1200 tok&#x2F;s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

    Life & fun · May 2026 · github.com

  • FM

    Dev tools · May 2026 · github.com