Life & fun · alternatives · 2026
24 alternatives to Convect – Instant Serverless Deployment of ML Models
Convect is a deployment platform launched in 2021 that enables users to quickly host machine learning models on serverless infrastructure. It simplifies the process of taking trained ML models and making them available… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Convect – Instant Serverless Deployment of ML Models launched in 2021; newer entries below may have overtaken it.
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Cerebrium▲300If you haven’t noticed, GPUs are scarce right now. The global boom in inference has demand growing faster than supply can keep up, and at Cerebrium ...
2024 · cerebrium.ai · 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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Mave▲232Drop-in viral invite page w/ suggested contacts, in your app
2015 · mave.io · its alternatives →
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Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
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Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
2019 · github.com · its alternatives →
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2018 · modeldepot.io · its alternatives →
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Bring DevOps practices to your projects for automatic, reproducible, and fast machine learning.
2020 · cml.dev · its alternatives →
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The simplest way to serve AI/ML models in production - basetenlabs/truss
2022 · github.com · its alternatives →
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An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
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Informasi Akurat, Berita Terupdate – Hanya di Sini
2020 · modelzoo.dev · its alternatives →
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Production infrastructure for machine learning at scale - cortexlabs/cortex
2019 · github.com · 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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Hello, I am excited to announce the release of my project that I've been working on for quite a while. It has gone through many iterations. I believe that I now have a scalable platform that can efficiently ingest, search and report on large quantities of data. If you are at a very large scale, there will need to be some work to streamline your database access, but it is very possible to build a flexible and robust solution. Delve is built using Django, Django Rest Framework, webpack, JS and SCSS. Delve can be extended with apps, which are actually specially built Django apps. Delve has a…
2025 · github.com · its alternatives →
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Powerful cloud-based predictive analytics, ML as a Service
2014 · azure.microsoft.com · 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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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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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 →