Otto-m8 – A low code AI/ML API deployment Platform
Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based BERT model with an LLM at work, and I realized it would be cool if I could do that instantly(especially since it was a prototype). At the time, I was considering a platform that could essentially help you train deep learning models without any code. It was my observation that much…
Otto-m8 – A low code AI/ML API deployment Platform launched on December 21, 2024 with 10 votes, #1,989 of 5,365 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Otto-m8 is a low-code platform for deploying deep learning workloads as APIs. It lets users connect multiple models—including large language models and Hugging Face models—without writing code, then instantly deploy them as functional APIs. The platform is designed for developers and teams who need to prototype and launch AI model combinations quickly, focusing on inference deployment rather than model training.
written from the facts on this page · September 2026
From the sources
Flowchart-like UI to interconnect LLM's and Huggingface models, and deploy them as a REST API with little to no code. - farhan0167/otto-m8
An open source Flowchart based automation platform to run deep learning workloads with minimal to no code. otto-m8 (automate) is a low code platform that allows users to build AI/ML workflows through a flowchart like UI. In other words, you can visually declare how you build AI workflows or agents. Its low code because you are still in control over the implementation of a block(yes you can not only add custom blocks but also modify out of the box blocks), and more importantly, its a platform that isn't specifically built on top of an existing AI framework like Langchain. What this means is that, you can build you workflows with any framework you see fit, whether it is Langchain, Llama Index…from github.com
In the maker’s words, at launch
Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based…
Does a similar job
all alternatives →
SimplAI2025 · simplai.ai · ▲589Hey HN, I've been building SimplAI for the past several months — it's a platform for building, testing, and deploying LLM-powered agents and multi-step workflows. The problem I kept running into: spinning up an AI agent pipeline means stitching together prompt management, tool calling, memory, evals, and deployment — often from scratch every time. SimplAI tries to be the layer that handles all of that so you can focus on what your agent actually does. What it does: - Visual + code-first workflow builder for chaining LLM calls, tools, and APIs - Built-in prompt versioning and A/B testing…
TensorZero2025 · github.com · ▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
Opper AIJul 2026 · opper.ai · ▲229Hey HN! After the Car Wash Test post got quite a big discussion going (400+ comments, https://news.ycombinator.com/item?id=47128138), I spent the past few weeks building a tool so anyone can run these kinds of questions and get structured results. No signup and free to use. You type a question, define answer options, pick up to 50 models at a time from a pool of 200+, and they all answer independently under identical conditions. No system prompt, structured output, same setup for every model. You can also run a debate round where models see each other's reasoning and get a…
Marvin – build AI functions that use an LLM as a runtime2023 · github.com · ▲127Hey HN! We're excited to share our new open-source project, Marvin. Marvin is a high-level library for building AI-powered software. We developed it to address the challenges of integrating LLMs into more traditional applications. One of the biggest issues is the fact that LLMs only deal with strings (and conversational strings at that), so using them to process structured data is especially difficult. Marvin introduces a new concept called AI Functions. These look and feel just like regular Python functions: you provide typed inputs, outputs, and docstrings. However, instead of relying on…
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 20d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 28d ago · world.pixverse.video
Source: Show HN post ↗ · launch text quoted in part
