nowfound

AI · May 5, 2026

AI Codex

Cryptographic identity layer for autonomous AI agents

What it does

AI agents have no persistent identity every run is anonymous, untraceable, unaccountable. AI Codex fixes this. Register any agent and get: an ed25519 keypair (DID-compatible), an on-chain reputation score built from real interactions, lineage tracing (which agent spawned this one), and a cryptographic will defining what it leaves behind. The identity primitive your multi-agent stack is missing. Works with LangChain, AutoGen, CrewAI, ElizaOS. Free to register.

Does the same job

all alternatives →
  • NervePayFeb 2026 · ▲74

    Give AI agents identity, secrets vault & analytics

  • LoomalApr 2026 · ▲92

    Identity infrastructure for AI agents

  • KakuninMay 2026 · kakunin.ai · ▲20

    Cryptographic identity for autonomous AI agents

  • AP
    Agent Passport – OAuth-like identity verification for AI agentsFeb 2026 · ▲14

    Hi HN, I built Agent Passport, an open-source identity verification layer for AI agents. Think "Sign in with Google, but for Agents." The problem: AI agents are everywhere now (OpenClaw has 180K+ GitHub stars, Moltbook had 2.3M agent accounts), but there's no standard way for agents to prove their identity. Malicious agents can impersonate others, and skill/plugin marketplaces have no auth layer. Cisco's security team already found data exfiltration in third-party agent skills. Agent Passport solves this with: - Ed25519 challenge-response authentication (private keys never leave the…

  • Agent IDApr 2026 · ▲2

    Verifiable identity & trust for every AI agent

  • TraceaAug 2026 · tracea.online · ▲2

    Verify any AI agent Identity, legal proof & x402 payments

More ai this month

the category →
  • I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/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/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

    AI · 27d ago · cactuscompute.com

  • Turn website visitors into qualified pipeline

    AI · 19d ago · clarasdr.ai

  • Kane CLI446

    Natural language browser & mobile app tests from terminal

    AI · 24d ago · testmuai.com

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/s prefill and 1200 tok/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