Wayforth
The API runtime for AI agents
What it does
Agents call APIs differently than developers do. They need discovery, payment, and execution in one step — not three separate integrations. Wayforth handles all three: search 3,271 ranked APIs by intent, execute 15 managed services with zero credentials, pay across card, USDC, or x402 automatically. WayforthRank scores every API on uptime, latency, and real payment history. Rankings cannot be bought — legally enforced, permanently. One install. One fee. 98.5% to providers.
Does the same job
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- ADAPIRank.dev – We crawled and ranked public APIs from the internet2023 · apirank.dev · ▲176
tl;dr we at Escape (YC W23), we scanned 5651+ public APIs on the internet with our in house feedback driven API exploration tech, and ranked them using security, performance, reliability, and design criteria. The results are public on https://apirank.dev. You can request that we index your own API to the list for free and see how it compares to others. Why we did that? During a YC meetup I spoke with a fellow founder that told me how hard it was to pick the right external APIs to use within your own projects. I realized that most of what we build relies on public APIs from external…
Keenable – A different web search API for AI agents12d ago · keenable.ai · ▲12Hey HN! We built https://keenable.ai, a different web search API for AI agents. Keenable searches our own 100B+ page index. We are focused on low cost and latency (p95 <250ms from us-east). We don’t believe in benchmaxxing, so we open-sourced our internal benchmarking suite, NEEDLE (available at https://keenableai.github.io/needle): a live benchmark that compares Keenable with other search APIs on fresh agent-like queries. I spent seven years at Amazon as a scientist working on web grounding for Alexa/AGI, and my co-founder Andrey previously led search at…
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
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 19d ago · company-app.joinastute.com
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
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.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