Alternatives
Products that do what Ferqon does
Your hardware lab. From anywhere.
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10DL
2014 · databaselabs.io
- 11
- 12
- 13IB
Built a simple web app that tells you which open-source LLMs will work on your hardware. It auto-detects your specs, shows compatible models from Hugging Face, gives realistic performance estimates (tokens/sec), and recommends quantization settings. You can also manually input specs to see "what if I upgraded my RAM?" Made this after wasting time downloading giant models only to find they crawled on my hardware. Hope it saves you some frustration!
2025 · caniusellm.com
- 14CA
Hi HN, I've been working with LLMs in production for a while both as a solo dev building apps for clients and working at an AI startup. The one thing that always was a pain was to pay OpenAI/Gemini/Anthropic a few dollars a month just for me to say "test" or have a CI runner validate some UI code. So I built this server called ChunkBack, that mocks the popular llm provider's functionality but allows you to type in a deterministic language: `SAY "cheese"` or `TOOLCALL "tool_name" {} "tool response"` I've had to work in some test environments and give good results for experimenting…
Nov 2025 · github.com
- 15PB
Hi HN, We're Rishabh, Aashish, and Noah, the creators of ProtoType: a platform for building GraphQL backends. You can check it out here: https://www.useprototype.com We were fed up with creating the same sort of APIs over and over again when building web applications so we built this tool for ourselves. As we're all in university, we showed it around to our friends and they enjoyed using it to kickstart their projects. After that, we thought we'd host it on a website and allow anybody to use it! ProtoType is different from similar GraphQL backend builders such as 8base in that it…
2019
- 16FC
Hi HN! I'm Jean-Paul, the creator of Fire CI (https://fire.ci). I've been a dev for 10 years and building Fire CI for the past 6 months. Fire CI is a server that runs local builds in Docker on your own computer. It uses an installable agent to broker the builds with GitHub and also co-ordinates builds between your local server and other members of your team (optional). It's fast because there is no queueing and a tiny piece of your computer is more powerful than most hosted or rented cloud servers. It's scalable by design: each developer brings his own computing power. And IMHO the…
2019
- 17GG
2015 · hueyql.herokuapp.com
- 18RA
Hey HN, I built SuperHQ, an app that lets you run coding agents in local sandboxes (powered by Shuru). No custom UI wrapping the agents, they run as CLI/TUI like they were designed to. It just provides you the tools most of us (okay, maybe just me?) needed for running multiple coding agents in parallel without worrying about breaking your system or work environment. Each agent runs in its own microVM. You mount your projects in, writes go to a tmpfs overlay so your host is never touched, and you get a unified diff view to accept or discard changes. API keys never enter the sandbox, they…
Apr 2026 · superhq.ai
- 19WM
Hi HN, I’ve spent the last decade building hardware products like humanoid robots, 3D printers, and self-driving tractors. I needed a tool to navigate technical documents faster, so I created one with friends. This tool helps with component search, cross-referencing, comparison, and debugging. We’d love your feedback, whether you find it useful or not. Thank you! Try it here: www.convergelab.ai
2024 · convergelab.ai
- 20LF
Hi HN, I just wanted to share what I have been working on for the past few months: A firmware analyzer for embedded Linux systems that helps uncovering security issues running entirely in the browser. This is a very early Alpha. It is going to be rough around the edges. But I think it provides quite a lot of value already. So please go ahead and drop a firmware (only .tar rootfs archives for now) and try to break it :)
Mar 2026 · xray.boldwark.com
- 21FF
It uses your local Claude and GitHub CLI and git worktrees, so there's nothing to configure beyond what you already have. Our AI coding workflow was a hodgepodge of scripts and ad-hoc processes, so we built this to centralize and streamline - and most importantly adapt as things change. Some cool features so far (lots more planned): 1. One click github issue to agent working on it. 2. Ratcheting mode, where it watches CI for code review comments and build failures, and automatically fixes them. Would love genuine feedback, bug reports, PRs, suggestions, etc.
Feb 2026 · github.com
- 22HO
Hello HN, I’m excited to share something we’ve been working on: Cloud Troubleshooting Labs. This tool provides on-demand environments for engineers to practice hands-on troubleshooting with AWS, GCP, Azure, and Kubernetes. What it does: We use Pulumi to spin up these environments. Each scenario includes a diagram and an explanation of the available IT infrastructure. Engineers are tasked with fixing configuration issues to make the application work. Depending on the test type, the environment could range from a simple terminal to a full cloud environment or a web-based VSCode. Many of our…
2024 · brokee.io
- 23OC
Hi everyone, I'm Vasek (https://x.com/mlejva), the CEO of the company behind this - https://e2b.dev. The company is called E2B. We're an open-source (https://github.com/e2b-dev) devtool that makes it easy to run untrusted AI-generated code in our secure sandboxes. You can think of us as coding runtime for LLMs. You can self host us on GCP (https://github.com/e2b-dev/infra/blob/main/self-host.md) and we're working on AWS, then Azure, and any Linux machine. This repo is one of our open-source projects that we're…
2025 · github.com
- 24RA
We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
Sep 2025 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →