nowfound

AI · May 7, 2026

BasicSoccer AI

Upload your soccer training, and get instant feedback

What it does

Meet BasicSoccer AI. Whether you're a parent helping your kid improve, a player working on your game, or a coach looking for an extra set of eyes, BasicSoccer AI gives you instant, personalized feedback on soccer skills using the power of AI. Record or upload, and get clear tips on technique, positioning, and what to work on next. No jargon. No guesswork. Just friendly, useful coaching you can actually use. Upload or record drill, Watch playback with feedback overlay, and review session report.

Does the same job

all alternatives →
  • Impakt: AI Coach2023 · ▲432

    Train smarter, not harder

  • IT
  • PLAYBACK SPORTS AIApr 2026 · playbacksports.ai · ▲70

    AI match capture and highlights for youth and amateur clubs

  • Soccer Drills App2016 · ▲81

    App that shows you how to be a youth soccer coach

  • IM
    I made a football/soccer formation and squad app2024 · apps.apple.com · ▲17

    Inspired by watching my sons coach using a carry around whiteboard, plus also starting to coach my wifes over 30s womens amateur team I wrote a mobile app for amateur football/soccer coaches. It allows you to add your players information, manage substitutions during games (who's on the field, whos on the bench) as well as drag around players into formations, draw tactics on the screen and share using the IOS share features to email, messages etc. Build your tactic and share it with the team between games. It's free and its designed to just be an easy thing for coaches to take around…

  • Saideline Jul 2026 · saideline.com · ▲3

    Create Soccer Drills & Sessions in Seconds

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

  • 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/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