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Alternatives

Products that do what Predict.sh – Deploy AI Models into REST APIs does

Hi HN! I've been struggling to deploy AI models in previous projects and thought it would be fun to merge serverless and AI. It's still a prototype: https://predictsh.herokuapp.com/

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    Koxy AI118

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    Make machine learning work for you, not the other way around

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  15. 15MA

    Hi, I'm working on a project that regroups all best AI (AIaaS) from different providers (GCP, AWS, Azure, DeepL, etc.) in one API (https://github.com/edenai/edenai-apis). I've got asked the question : why aren't you regrouping Open Source models (instead of proprietary APIs) into one repo? Well because it doesn't make sens to deploy and maintain large pytorch (or other framework) AI models (especially for document parsing, image and video moderation or speech recognition) in every solution that wants AI capabilities. So using APIs makes way more sens. Deployed OpenSource…

    2023 · github.com

  16. 16

    AI models to apps, fast

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  17. 17MZ
  18. 18FS

    Hi everyone! I've been loving building with AI, and over the past few years I've been leaning more and more into Typescript (and bun). My team at inference.net is constantly trying to get more leverage out of AI and find ways to setup our codebase to be able to increase the level of correctness that our AI is able to write code at. This starter repo is a very opinionated way to lay out a repo to lean into AI heavily. It leverages Cloudflare Workers as a deployment target for the API (my goal is to never have to deploy an API on a AWS/Azure/GCP server ever again unless I get to a…

    2025 · abeahmed.com

  19. 19IM

    Heya HN, after spending +1 year building an ML-driven analytics product (that didn't pan out unfortunately), I've pivoted to solving a problem my team and I found while building the previous product … why the hell is it so hard to move a model from a Jupyter notebook, to a development server, then to a production pipeline!? To solve this my team and I started the open source KitOps project under the Apache 2 license. KitOps includes the Kit CLI that uses a Kitfile manifest to create ModelKits: 1. The kit CLI packages your model, datasets, code, and configuration into an OCI compliant…

    2024 · kitops.ml

  20. 20IB

    Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…

    Dec 2025 · docs.trysoma.ai

  21. 21PS

    I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.

    27d ago · pacslate.com

  22. 22AA

    Hey HN! I really like local apps for their simplicity and privacy and hate paying Saas bills and I wanted a way to start automating my life with AI so I started building Anything. Anything is built on Tauri so the front end is React and the "backend" is Rust. It's 100% local & 100% doesn't ask you to spin up docker to use. Another core goal of the app is to get away from "package bloat" you see in other general purpose AI oss projects where they have a package.json that is 300 lines long ( more on that later. ) Oh btw I suck at Rust! I learned Rust while building this so the code is _not…

    2024 · github.com

  23. 23S1

    I wanted to build an inference provider for proprietary AI models, but I did not have a huge GPU farm. I started experimenting with Serverless AI inference, but found out that coldstarts were huge. I went deep into the research and put together an engine that loads large models from SSD to VRAM up to ten times faster than alternatives. It works with vLLM, and transformers, and more coming soon. With this project you can hot-swap entire large models (32B) on demand. Its great for: Serverless AI Inference Robotics On Prem deployments Local Agents And Its open source. Let me know if anyone…

    Nov 2025 · github.com

  24. 24OA

    Built this after getting tired of fighting local AI setup (CUDA issues, dependencies, API configs). Goal was to make something that just runs locally without all the overhead. Happy to answer questions or get feedback.

    Apr 2026 · store.steampowered.com

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