nowfound

AI · August 24, 2026

Navigara

Connect Your AI Spend Directly to Your Roadmap

In plain words

Navigara connects AI coding tools to engineering roadmaps by analyzing code commits and tracking costs against specific features and tasks. The platform measures productivity gains from AI adoption, identifies spending on off-roadmap work and maintenance, and can route routine tasks to cheaper models. It integrates with Git, JIRA, Linear, and major AI coding tools to help engineering teams demonstrate ROI and understand whether AI investments translate to actual capacity or reveal spending waste.

written from the facts on this page · September 2026

From the sources

Navigara connects AI coding performance directly to your engineering roadmap. Analyzing code like a senior engineer to prove real capacity gains, Navigara tracks exact costs per roadmap item, isolates off-roadmap waste, and identifies maintenance burn. Cut spend further by automatically routing routine CRUD tasks to low-cost models without sacrificing quality. Connects in minutes via Git history, JIRA/Linear, and any AI coding license for spend.

Measure engineering before and after AI, then tie the speed to the roadmap and the roadmap to revenue. Navigara scores throughput from your commit history, so your AI bill stops being a number and starts being a feature list.

Pricing, as stated on its site

Free tier, paid plans from $7/mo — Navigara offers a free 14-day trial (Explore plan) with up to 1,000 pull requests analyzed. Paid plans start at $7/developer/month (Measure) and $30/developer/month (Pro). Enterprise pricing is custom

checked September 2026 · prices change

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 · 16d 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 · 26d ago · cactuscompute.com

  • Make your software self-driving

    AI · 30d ago · coldtea.ai

  • Soloop472

    Approval-first Agent OS for solo founders

    AI · 30d ago · soloop.io

Launched alongside, August 2026

the whole month →
  • TL

    Life & fun · 9d ago · louisabraham.github.io

  • Hey Noah641

    A proactive AI executive assistant for founders

    AI · Aug 2026 · heynoah.io

  • Let agents source clips from terabytes of your local video

    Work · 18d ago · clipto.com

  • SA

    Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…

    Life & fun · Aug 2026 · toneyalexander.github.io

  • AdAnt AI608

    Claude for viral, high-converting social ads

    AI · Aug 2026

  • 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 · 16d ago · simedw.com