Alternatives
Products that do what LocalCloud: Complete AI Dev Platform does
Stop paying for AI experiments. Full stack runs locally
- 1LA
I built LocalGPT over 4 nights as a Rust reimagining of the OpenClaw assistant pattern (markdown-based persistent memory, autonomous heartbeat tasks, skills system). It compiles to a single ~27MB binary — no Node.js, Docker, or Python required. Key features: - Persistent memory via markdown files (MEMORY, HEARTBEAT, SOUL markdown files) — compatible with OpenClaw's format - Full-text search (SQLite FTS5) + semantic search (local embeddings, no API key needed) - Autonomous heartbeat runner that checks tasks on a configurable interval - CLI + web interface + desktop GUI - Multi-provider:…
Feb 2026 · github.com
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- 3
Local▲107Super excited to launch our new app Local today. What we’ve learned at Base Compute over the last months is that running AI directly on your laptop or workstation gives you maximum privacy and it’s free, but it’s also a massive headache to configure. So we’ve decided what matters is making the experience completely frictionless for users. Local analyses the hardware of your laptop, optimises the AI for it, and recommends the best models for your specific device. It let’s you do what you’re doing with cloud AI already, just for free and on your own machine: Chatting with PDF’s, Recording and…
17d ago · basecompute.co
- 4IP
The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol. Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day. A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship…
Mar 2026 · georgelarson.me
- 5JL
Hi HN! Here's a local-only stack I built over the weekend - hope it can be useful for you! I have been building a lot of AI apps - https://github.com/a16z-infra/ai-town https://github.com/a16z-infra/companion-app ... And there were definitely times I spent way too much $$ before deploying the app to production. So I was looking for a "local only" stack and found a few tools that worked well together. I used the following set of tools but may add more options later: - Inference: Ollama - VectorDB: Supabase pg-vector - LLM orchestration: langchain -…
2023 · github.com
- 6TC
Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
2022 · tensordock.com
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- 8WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat
- 9IB
I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You…
Apr 2026 · stream-sock-3f5.notion.site
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Submit a job via API or dashboard and get results for cheap
Feb 2026 · carmel.so
- 11
Scheduled agents fail in four ways: silent skips, tokens burned on nothing, no memory between runs, and needing your laptop awake. Routines answers all four.
27d ago · octomind.run
- 12BD
Hi HN, we’re Nick and Drew, and we’re building boxes.dev – the first cloud-only agentic dev environment (ADE) that gives every Codex and Claude Code agent its own cloud computer. We’re two engineers who previously built Gem (co-founder/CTO and first hire), and we spent the last year coding almost exclusively using Codex and Claude Code. It’s been a huge change to how we code, and it’s been exhilarating seeing the models keep getting better – but we eventually realized that developing on localhost was holding us back: - Git worktrees are clunky to set up and use for parallelizing work -…
Jun 2026 · boxes.dev
- 13RL
Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image. We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that. Imagine if you are a…
2023 · lepton.ai
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- 15OA
Built this after getting tired of fighting local AI setup (CUDA issues, dependencies, API configs). Goal was to make something that just runs locally without all the overhead. Happy to answer questions or get feedback.
Apr 2026 · store.steampowered.com
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Hi HN! I'm the author of mere.run a local first inference runtime built around an installable CLI. I believe that whenever possible we should use the stuff we already own (like our Mac laptops, decent machines gathering dust, our gaming PC) and the limited electrical power we have easy access to, like the socket in the wall next to most of us. We shouldn't have to send our data to the cloud hoping some T&C will prevent it from being used in a way that we'd regret. Most of the local AI solutions are technical, involved, and land a curious body in some package hell. People are optimizing for…
Jul 2026 · github.com
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- 18LR
I built localLLLM: a small community project for running local models. Live: https://locallllm.fly.dev The goal is simple: if someone has model + OS + GPU + RAM, they should get steps that actually work (ideally one liner) I need help populating and validating guides. If you run local models, please submit one working recipe (or report what failed). Would love to hear general feedback as well!
Apr 2026 · locallllm.fly.dev
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- 20RA
Hi, founder of Okteto here! We’ve been experimenting with AI agents in our workflows at Okteto. Running them locally worked at first, but quickly became painful. git worktrees, multiple terminals, and messy context switches slowed us down. So we built Agent Fleets: ephemeral, fully managed environments for AI agents, built on top of Okteto’s development platform. Each agent runs in its own containerized environment on your infrastructure, with the services, tools, and policies it needs. You can spin up agents with a single click or API call. No local setup. No git worktrees. The beta…
2025 · okteto.com
- 21AA
I'm a solo dev in Taiwan. I built 4 AI agents that handle content, sales leads, security scanning, and ops for my tech agency — all on Gemini 2.5 Flash free tier (1,500 req/day). I use ~105. Monthly LLM cost: $0. Architecture: 4 agents on OpenClaw (open source), running on WSL2 at home with 25 systemd timers. What they do every day: - Generate 8 social posts across platforms (quality-gated: generate → self-review → rewrite if score < 7/10) - Engage with community posts and auto-reply to comments (context-aware, max 2 rounds) - Research via RSS + HN API + Jina Reader → feed…
Mar 2026
- 22OC
CloudBot gives you a fully configured AI employee with its own cloud computer in one click. Built on OpenClaw. What you get: - Full Ubuntu desktop environment in the cloud - Pre-installed AI agent that sees the screen and controls the computer - 24/7 availability - your AI keeps working while you sleep - Uses your own API keys for AI models - Starting at $69/month The AI can use VS Code, browse the web, run terminal commands, manage files - anything you'd do on a real desktop. I wake up to completed code reviews, finished research reports, and updated documentation. Built this…
Feb 2026 · cloudbot-ai.com
- 23RA
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
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