AI · alternatives · 2026
24 alternatives to Redditflow
Build ML models of future, and never run out of data.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Redditflow launched in 2022; newer entries below may have overtaken it.
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Tapflow 2.0▲1,125We built Tapflow for devs, designers, PMs, and tech folks who’ve been sitting on internal docs, templates, and systems — but never productized them. Upload a PDF, notes, or workshop deck, and Tapflow drafts a structured product (with chapters, teaser and pricing plans). It’s good for AI kits, onboarding guides, design systems, and frameworks. You can sell through Stripe, LemonSqueezy, or PayPal. Real-time collaboration is in early beta. No site builder, no LMS — clean design and just focused tools to ship. Fully bootstrapped and just launched on PH today →…
2025 · tapflow.ai · its alternatives →
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Pre-trained computer vision models and public datasets
2021 · universe.roboflow.com · its alternatives →
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We built Valohai LLM for tracking and comparing LLM evaluation results. Whether your evals live in notebooks and spreadsheets, or you're using an observability tool that wasn't built for comparison, this gives you a purpose-built eval comparison dashboard. Run evals with a Python library (pip install valohai-llm), results stream in, and you can compare up to 6 configurations side by side. Group by any dimension (model, category, difficulty) to see where each model excels. It doesn't do tracing or production observability, for now just eval tracking and comparison. What's cool is that you can…
2020 · valohai.com · its alternatives →
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ML Console is a free tool to build an AI model without writing a single line of code. Simply pick a column to predict, and let us handle the rest.
2021 · mlconsole.com · its alternatives →
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Hey HN! We’re Vaibhav and Marcello. We’re building Plexe (https://github.com/plexe-ai/plexe), an open-source agent that turns natural language task descriptions into trained ML models. Here’s a video walkthrough: https://www.youtube.com/watch?v=bUwCSglhcXY. There are all kinds of uses for ML models that never get realized because the process of making them is messy and convoluted. You can spend months trying to find the data, clean it, experiment with models and deploy to production, only to find out that your project has been binned for taking so long.…
2025 · github.com · its alternatives →
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GitRanks▲127Hi HN, I built GitRanks because I’ve always wanted a clear, fun way to see how my open-source work compares - both globally and right here at home. The app pulls in GitHub data to give every developer an at-a-glance “scorecard”, then rolls those into live leaderboards so you can: - Track rankings by stars, contributions and followers - Filter worldwide vs. your own country - Refresh daily - no waiting weeks to see your progress - Discover rising devs you’ve never heard of and follow their work Tech Stack: - Back: MongoDB | NestJS | BullMQ | GraphQL - Front: Next.js | Tailwind | Shadcn Data:…
2025 · gitranks.com · its alternatives →
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datagran▲130Put ML pipelines into production, fast. Without coding
2019 · datagran.io · its alternatives →
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Hey everyone, ML Blocks is a node-based workflow builder to create multi-modal AI workflows without writing any code. You connect blocks that call various visual models like GPT4v, Segment Anything, Dino etc. along with basic image processing blocks like resize, invert color, blur, crop, and several others. The idea is to make it easier to deploy multi-step image processing workflows, without needing to spin up endless custom OpenCV cloud functions to glue together AI models. Usually, even if you're using cloud inference servers like Replicate, you still need to write your own image…
2024 · mlblocks.com · its alternatives →
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I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a compiler that simply converts the model into plain source code with no dependencies, and it actually solved all my deployment problems. Now I'm curious if it can help anyone else too. Through the link you can submit your model file (Keras h5, onnx soon to be supported), and I'll…
2023 · waveworks.dk · its alternatives →
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TLDR: Product developers need tools designed for them to build ML models. We’d love for you to try a demo of Mage without needing to sign up: https://www.mage.ai/onboarding My name is Tommy DANGerous (or Tommy Dang) and I’m the CEO and co-founder at Mage. I worked at Airbnb for over 5 years as a product developer building features for guests. Mage is a web-based tool for building, training, and deploying ML models that make predictions based off your data. Training and using ML models in production typically requires working knowledge of building data pipelines, algorithms,…
2022 · its alternatives →
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machine learning, python, programming, beginner, software
Jul 2026 · mirthi.gumroad.com · its alternatives →
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My Machine Learning Web Service. Contribute to pplonski/my_ml_service development by creating an account on GitHub.
2020 · github.com · its alternatives →
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We are the developers of an open-source package Metaflow that we started at Netflix. Metaflow provides a human-friendly interface to the full stack of ML infrastructure, including data access, compute, workflow orchestration, and versioning. It is used by hundreds of companies across industries. Over the past years, we have seen that there are two major stumbling blocks for folks who want to learn to build real-world ML applications: 1) Setting up the full infrastructure stack in the cloud costs time and money. The investment is worth it once you know what you want to do, but that's not…
2023 · outerbounds.com · its alternatives →
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a delightful machine learning tool that allows you to train, test, and use models without writing code - GitHub - nidhaloff/igel at v0.4.0
2021 · github.com · its alternatives →
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Hi Developers, I'm Luca, the creator of Modeloop. I've spent the last 18 months building, from scratch, a model-based design tool and today I'm finally opening the Open Beta. Modeloop is a tool designed to generate code and deploy on embedded systems. The core idea behind this product is to create a vertical solution to design, test and iterate on the model faster, leveraging the modern software practices like Git. For this reason, Modeloop avoids vendor lock-in by saving model data as readable JSON rather than proprietary formats, making model reviews significantly easier. At its core,…
Jun 2026 · modeloop.app · its alternatives →
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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 · its alternatives →
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Hey HN! A few months ago we shared our AI dataset generator as an open source repo, and the response was incredible (https://news.ycombinator.com/item?id=44388093). We got requests from folks who wanted to use it without the hosting overhead, so we created both options: a hosted version (https://www.metabase.com/ai-data-generator for instant use and the source code fully open (https://github.com/metabase/dataset-generator) for anyone who wants to self-host or contribute. Looking forward to seeing how you use it and what you build on top of…
2025 · metabase.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →