AI · alternatives · 2026

24 alternatives to ML Studio

Build, deploy and manage ML models using one service

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. ML Studio launched in 2020; newer entries below may have overtaken it.

1
ML Studio▲3
Machine Learning Model Building and Data Analysis Platform.
Jul 2026 · mlstatsoft.com · its alternatives →
2
Prompt Engineering Studio▲501
Build, test & deploy AI prompts across 1600+ models at scale
2025 · portkey.ai · its alternatives →
3
Plexe▲273
Build and deploy ML models in English
Oct 2025 · plexe.ai · its alternatives →
4
Label Studio 1.8.0 Release▲185
Open source data labelling platform for AI model tuning
2023 · labelstud.io · its alternatives →
5
Layer AI▲124
Metadata store for production ML
2022 · layer.ai · its alternatives →
6
Deploy ML Models on a Budget▲117
Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
7
ML Kit (by Google)▲195
Machine learning for mobile developers
2018 · developers.google.com · its alternatives →
8
ML Blocks – Deploy multimodal AI workflows without code▲112
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 →
9
Mljar Studio – local AI data analyst that saves analysis as notebooks▲73
Hi HN, I’ve been working on mljar-supervised (open-source AutoML for tabular data) for a few years. Recently I built a desktop app around it called MLJAR Studio. The idea is simple: you talk to your data in natural language, the AI generates Python code, executes it locally, and the whole conversation becomes a reproducible notebook (*.ipynb file). So instead of just chatting with data, you end up with something you can inspect, modify, and rerun. What MLJAR Studio does: - Sets up a local Python environment automatically, runs on Mac, Windows, and Linux - Installs missing packages during the…
May 2026 · mljar.com · its alternatives →
10
MLConsole – web app to train ML models, for free and client-side▲86
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 →
11
Machine learning automation from creating to using models in production▲72
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 →
12MM
MLEM – ML model deployment tool▲24
Hi, I'm one of the project creators. MLEM is a tool that helps you deploy your ML models. It’s a Python library + Command line tool. 1. MLEM can package an ML model into a Docker image or a Python package, and deploy it to, for example, Heroku. 2. MLEM saves all model metadata to a human-readable text file: Python environment, model methods, model input & output data schema and more. 3. MLEM helps you turn your Git repository into a Model Registry with features like ML model lifecycle management. Our philosophy is that MLOps tools should be built using the Unix approach - each tool solves a…
2022 · its alternatives →
13
Zoo Design Studio v1.0▲140
Professional CAD platform + Text-to-CAD powered by ML
2025 · zoo.dev · its alternatives →
14
Plexe – ML Models from a Prompt▲130
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 →
15
Compile ML models into dependency-free source code for easy deployment▲37
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 →
16
YourGPT 2.0▲215
Today we are launching YourGPT 2.0, an update focused on making support, sales, and operational workflows work together more smoothly in one system. This release improves how workflows are built, how the platform connects to external tools, and how context is maintained across long, multi-channel interactions. AI Studio now makes it much easier to create and refine workflows. You can describe the process you want in natural language and the system generates the full workflow for you. It can also help debug issues by showing what happened at each step and explaining where things went off…
Nov 2025 · yourgpt.ai · its alternatives →
17
3D AI Studio V3▲156
Generate & Texture 3D models faster, smarter-now even better
2025 · 3daistudio.com · its alternatives →
18
Bulk AI Image Generation by table.studio▲131
Generate images in bulk using ChatGPT's new image model
2025 · table.studio · its alternatives →
19MZ
Model Zoo: Deploy your machine learning model in a single line of code▲34
Informasi Akurat, Berita Terupdate – Hanya di Sini
2020 · modelzoo.dev · its alternatives →
20
Metabase Data Studio▲153
Build the semantic layer that makes AI analytics trustworthy
Mar 2026 · metabase.com · its alternatives →
21
Model Zoo▲74
Deploy your machine learning model in a single line of code.
2020 · its alternatives →
22
Baseten – Build ML-powered applications▲112
Hi HN, Three months ago, I took a job at Baseten to help craft and document an application builder that lets data scientists build full-stack, production-ready applications around their ML models without worrying about containers, Flask, or React. From my first day, everyone was focused on what would happen today: opening up our public beta. I’m super excited to see what you build with Baseten. If you want to take Baseten for a full-speed test drive, follow along with this tutorial, where you can build and deploy an application in 20 minutes:…
2022 · baseten.co · its alternatives →
23
Truss – Serve any ML model without boilerplate code▲68
The simplest way to serve AI/ML models in production - basetenlabs/truss
2022 · github.com · its alternatives →
24
Cortex▲81
Deploy, manage, and scale machine learning applications
2019 · 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 →