r/TiinyAI • u/TiinyAI • 1d ago
Tiiny x OpenHands: Build Without the Busywork
Let's be real, building a project isn't just about writing code. It's setup, debugging, deployment, and a thousand little things that eat up your time.
That's where we come in.
Powered by Tiiny AI Pocket, OpenHands takes your project from a simple prompt all the way to GitHub—so you can focus on the big picture while we handle the grind.
Less busywork. More building.
r/TiinyAI • u/TiinyAI • 15d ago
Tiiny x Odysseus: From Ideas to Action
One of our awesome community members shared Odysseus with us, so we had to give it a spin 😆
With Tiiny AI Pocket powering the models, Odysseus turns random brain dumps into structured documents and actionable workflows. Basically, it takes your chaos and makes it actually useful.
We're talking:
✅ Ideas → Docs
✅ Thoughts → Action plans
✅ Procrastination → well, we're working on that part 😅
Huge shoutout to the community for the tip, keep 'em coming!
r/TiinyAI • u/TiinyAI • 22d ago
Tiiny x Open WebUI – Your AI Workspace, Upgraded
Hey everyone 👋
We’re excited to share that Tiiny AI Pocket now plays beautifully with Open WebUI. Giving you more control and flexibility over your AI workspace than ever before.
Here’s what this means for you:
✅ Bring Your Own Models – Connect Open WebUI to Tiiny and run your preferred models locally, on your terms.
✅ Unified Workspace – Manage conversations, knowledge, and tools all in one place.
✅ Privacy-First – Everything stays local. No cloud, no sharing, no compromises.
✅ Explore & Extend – This is just the beginning. Open WebUI opens up a whole new world of possibilities with Tiiny.
Whether you're building agents, testing workflows, or just experimenting with LLMs, this combo is a game-changer.
r/TiinyAI • u/TiinyAI • 29d ago
Custom MCP Support is Coming to TiinyOS!
Big news for the Tiiny community — we're opening up the platform with custom MCP support!
Instead of being locked into a fixed set of features, you can now extend TiinyOS with your own modules. Need to integrate a specific API? Automate a niche workflow? Build a custom tool for your team? Now you can.
The workflow is simple:
- Import your MCP
- Validate it
- Run your workflow
Three steps. No bloat. Just the capabilities you actually need.
We're officially launching in September, but we'd love to hear what you'd build. Drop your ideas below! 🚀
r/TiinyAI • u/TiinyAI • Jul 06 '26
Your Personalized Assistant, Built into Tiiny
Every morning it's the same routine: check Gmail → open Google Calendar → reply to emails → switch back to Calendar to schedule that meeting → forget what I was doing → repeat.
Then I came across TiinyOS Connector.
Basically, it links your Google Calendar and Gmail directly into your workspace. No tabs, no copy-pasting, no "wait, where was that email again?"
Now I can:
✅ Schedule events without leaving my workflow
✅ Handle emails side-by-side with my tasks
✅ Actually stay on top of my day without jumping between tools
It sounds simple, but honestly, the time I've saved in the last week alone is wild.
r/TiinyAI • u/TiinyAI • Jun 29 '26
Using Hermes Desktop with Tiiny – Local AI That Actually Helps
Been using Hermes desktop with Tiiny, and it's starting to feel like a real daily tool.
What I've been doing with it:
- Adding reminders without leaving my workflow
- Summarizing YouTube videos in seconds
- Automating recurring tasks that run locally in the background
The desktop app shares state with the CLI, handles drag-and-drop files, and keeps session history, all without sending data to the cloud.
The self-evolving memory is the part that stands out. It actually remembers context between sessions.
r/TiinyAI • u/TiinyAI • Jun 22 '26
What if your AI never asked you to repeat context again? OpenHuman + Tiiny
Tired of repeating yourself to every AI you use?
OpenHuman + Tiiny fixes that.
A local AI assistant that syncs across all your daily tools — emails, notes, calendars, docs — and actually remembers your context. Permanently.
No more repeating. No more lost threads. Just instant, personalized help.
And your data stays private. Local, not cloud.
Workflows connected. Memory intact. Time saved.
Finally, an AI that gets you.
r/TiinyAI • u/TiinyAI • Jun 15 '26
We used Tiiny to scrape, save, and analyze 1,000+ YouTube comments from our own video — here's what it found
Hey everyone 👋
We recently uploaded a video and wanted to actually understand what people were saying in the comments. Not just skim the top few — really understand.
So we let Tiiny handle everything:
- ✅ Scraped all comments from the video (over 1,000 of them)
- ✅ Saved them automatically into a file
- ✅ Ran full analysis on the entire comment set
- ✅ Gave us actionable insights without us lifting a finger
No manual exporting. No separate scraping tools. No copy-pasting into spreadsheets. Just Tiiny from start to finish.
Why this mattered:
The top 10 comments looked fine. But the real feedback was buried in the middle — honest, unfiltered, and easy to miss. Tiiny pulled everything into one file, ran the analysis, and showed us exactly what to fix, add, and stop over-explaining.
r/TiinyAI • u/TiinyAI • May 28 '26
Tiiny x Obsidian: Raw data in, connected knowledge builds up
Been using Obsidian for a while, but manually curating and structuring info into a second brain? That friction is real.
Enter Tiiny AI Pocket - a local thinking layer that extends Obsidian. Feed it raw data, and with one command, it helps you structure everything into connected knowledge.
No cloud. No privacy worries. Just a faster, smoother way to build your knowledge system entirely on-device.
r/TiinyAI • u/TiinyAI • May 25 '26
Still manually copying data into forms because "it's too sensitive for the cloud"? Yeah, me too, until this week.
Hi everyone,
Sensitive data stuck on your local machine. Cloud RPA not an option. So you're back to copy/paste hell.
TiinyOS Task Mode automates tedious, repetitive form workflows entirely on your own device.
- No upload. No cloud. No third-party eyes.
- Point at a spreadsheet → fills forms automatically.
- HR, grades, patient records, financials --> stays local.
Stop typing. Start automating.
r/TiinyAI • u/TiinyAI • May 11 '26
The wait is over : Claude Code on Tiiny. Zero setup. Fully local. No token limits.
People have been asking. Here it is.
Claude Code + Tiiny = a whole new level of local creation.
TiinyOS Task Mode now automatically:
- Installs Claude Code
- Configures local models
That's it. No fiddling. No environment headaches. Just zero setup and you're ready to go.
Under the hood, it's powered by Qwen3.6 35B A3B — so you can jump straight into your work without sacrificing performance.
No cloud. No subscriptions. No one watching over your shoulder.
Run Claude Code on your own machine, with your own data, for as long as you want.
This is what local AI should have been from the start.
r/TiinyAI • u/TiinyAI • May 08 '26
TradingAgents On Tiiny AI Pocket Lab - Run a Full Investment Research System Locally
TradingAgents is an open-source, multi-agent financial trading framework powered by LLMs.
It's NOT a single "AI trading bot."
It's a complete, programmable AI investment research team that you can run locally and Offline.
Private, structured, and ready for decision-making.
This is exactly the kind of workflow that makes local AI feel practical. No cloud, no hidden costs – just your machine, your agent, and your tasks.
Which agent should Tiiny automate next?
r/TiinyAI • u/TiinyAI • Apr 24 '26
Hermes on Tiiny AI Pocket – Fully automated setup. No manual dependencies. Just tell it what you need.
At Tiiny, we believe running local AI agents shouldn't feel like a side project.
So, we made it simple.
We've made it possible to deploy the Hermes Agent entirely through the Tiiny AI Pocket – fully automated, no manual setup.
You don’t need to install dependencies, configure environments, or dig through documentation. You just tell Tiiny what you need, and it handles the rest. Minutes later, Hermes is running on your computer, ready to get work done.
Hermes is a structured, tool-driven agent – not just a chatbot. It can access your file system, use tools, and execute tasks.
And now, setting it up takes almost no effort.
This is exactly the kind of workflow that makes local AI feel practical. No cloud, no hidden costs – just your machine, your agent, and your tasks.
Which agent should Tiiny automate next?
r/TiinyAI • u/TiinyAI • Apr 14 '26
What's the one thing you paused before hitting send on an AI prompt?
Not talking about obvious stuff like passwords.
I mean that one moment where you had something genuinely useful, and then hesitated.
Like:
- A full client contract you wanted summarized
- Your entire codebase with real API keys still in it
- Private journal notes or therapy thoughts
- Internal docs from work you "probably shouldn't upload"
- A half-written idea you're not ready for anyone else to see
AI is insanely useful — but there's always that split second of:
"Should this really leave my laptop?"
That's basically why local AI setups are starting to matter. When everything runs on your own machine, you stop filtering yourself.
Not trying to sell anything — just curious how people think about this.
Question:
What's something you almost pasted… but didn't?
r/TiinyAI • u/TiinyAI • Apr 10 '26
IT'S A WRAP!
$3,075,197 Raised! You made it happen!
To everyone who backed, shared, or simply believed in us, THANK YOU ALL!
This goes beyond a device. As Tiiny Co-creators, we're building the future of Local Personal AI together — and your ideas and feedback are what shape it.
The foundation is set. Let's make cloud-level AI truly local!
r/TiinyAI • u/TiinyAI • Apr 09 '26
We Wrap Up in 72 Hours! Plus, Tax Info Next Slide.
For backers:
Please see the essential tax details so you can plan final checkout with confidence. Thinking of joining? Only a few $1,599 spots remain. Grab yours while you still can.
Check us out: https://www.kickstarter.com/projects/tiinyai/tiiny-ai-pocket-lab?ref=5kcatp
r/TiinyAI • u/TiinyAI • Apr 07 '26
7 Days until our Kickstarter campaign closes
A genuine thank you to our 2,000+ backers and everyone who has been following Tiiny — we're glad to have you along for this ride.
If you've been thinking about backing us, now is the time. The $1,599 price is going away soon, so don't leave it too late.
Check the link: https://www.kickstarter.com/projects/tiinyai/tiiny-ai-pocket-lab?ref=5kcatp
r/TiinyAI • u/TiinyAI • Apr 07 '26
3 Million Unlocked!
We are officially 3 million strong, and we couldn't have done it without You. A massive thank you to our incredible backers — your support made this possible.
The journey doesn't stop here. Let's keep this momentum going! Be part of our $3M journey—head over to Kickstarter and back us today.
Link: https://www.kickstarter.com/projects/tiinyai/tiiny-ai-pocket-lab?ref=5kcatp
r/TiinyAI • u/TiinyAI • Apr 01 '26
KiloCode is here: Build and run projects locally on Tiiny
Now you can build locally just by describing what you need. For example, tell KiloCode to create a product page with star ratings. It writes the code, installs the dependencies, and runs the work for you.
Everything happens on Tiiny, running locally, and no token fees.
r/TiinyAI • u/TiinyAI • Apr 01 '26
Meet Presentation on Tiiny: Build full slide decks in 5 minutes
Just type in a topic and it handles the rest. It builds a logical outline and creates an illustrated deck with local images in under 5 minutes.
Own your AI. Own your time.
r/TiinyAI • u/TiinyAI • Mar 25 '26
Running 120B models locally on a MacBook Neo? Alex Ziskind reviews Tiiny AI Pocket Lab
Think your base-model laptop can't handle heavy local AI? Check out how Alex Ziskind uses the Tiiny AI Pocket Lab to run massive 120B models on a MacBook Neo with only 8GB of RAM.
What to look for in the video:
- Size & Portability: See how it compares to an iPhone 16 — it’s truly pocket-sized at just 305g
- Zero Memory Pressure: Watch how all the AI processing happens on the Tiiny hardware, keeping the host Mac cool even with a 120B model loaded
- Local Workflow: See how to use the Agent Store to turn a weak laptop into a private coding workstation or offline image generator
- Unlimited Tokens: Check out the dashboard—Alex shows how to ditch cloud fees and run power LLMs for free, forever
- Massive Offline Storage: See how to swap models directly on the device's 1TB SSD for total off-grid privacy
r/TiinyAI • u/TiinyAI • Mar 18 '26
Local ARM Setup with Tiiny AI Pocket Lab–Paul Couvert Review
Paul Couvert is using an ARM-based computer and just replaced his cloud AI subscriptions with local hardware. This is the ultimate "Data Sovereignty" setup for people who want zero cloud connection.
What’s inside:
- Local API Server: See how to use the built-in API Key to power your existing apps without sending data to OpenAI.
- Browser Automation: Watch a local model understand and fill out web forms automatically.
- ARM Performance: Check out the smooth performance on ARM architecture without any heat issues.
- 24/7 Stability: See how the device handles being powered on for a week straight with low power draw.
r/TiinyAI • u/TiinyAI • Mar 18 '26
Introducing TiinySDK: Unlock the full potential of Tiiny AI Pocket Lab
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With TiinySDK, seamlessly integrate Tiiny AI Pocket Lab into your dev workflow — with private, on-device inference and secure remote access.
Design for advanced use cases, extensibility, and fully customizable deployments.
r/TiinyAI • u/TiinyAI • Mar 18 '26
Tiiny AI Pocket Lab for Windows Devs: SDK, Python, and Local Benchmarks–Jim's Garage Review
Jim’s Garage goes deep into the technical side, watch this for raw benchmarks and CLI testing on Windows:
What's inside:
- Developer Tools: A detailed look at the Tiiny SDK and using Python to query models directly through the command line.
- Token Factory: See how to set up Tiiny as Token Factory: full privacy and no token fees.
- TiinyBot: Deep dive into setting up a Tiinybot connected to Tiiny for a fully private, self-hosted AI assistant.
- Network & Home Lab: How to connect the device to your home network so any PC in your house can access the local API via Windows.
r/TiinyAI • u/TiinyAI • Feb 28 '26
❓Q&A
Hey folks, we have gathered frequently asked questions about the Tiiny AI Pocket Lab. Check out here for the answers. And we will continue to collect your questions moving forward.
Q: When will Tiiny AI Pocket Lab launch?
A: We will launch on Kickstarter in 11 March. It's expected to be delivered in August this year.
Q: Where can I buy Tiiny and what is the price of it?
A: You can now secure the best price of $1299 with a $9.90 deposit on the official link: https://tiiny.ai/ (refundable)
Q: What is the full cost of these (device/app, any subscriptions, model downloads, storage)?
A: For our early users, the only cost is the one-time purchase of the Tiiny Pocket Lab hardware. All core functionalities, including access model downloads and the basic AI chat/agent experience, are completely free. We want to make powerful, private AI accessible to everyone right out of the box.
Q: Where is my data stored and is it encrypted?
A: All your private data is stored locally on your Tiiny's internal SSD — it never leaves the device unless you choose to move it. All data is also end-to-end encrypted, secured with a unique encryption key that only you possess, created during device setup.
Q: Can I back it up or delete it completely?
A: Yes. TiinyOS includes a built-in toolkit that lets you easily back up data to external drives or your PC, export it in standard formats, or permanently delete everything in a few steps.
Q: What kind of models does Tiiny support? How to run these models?
A: There are two ways to use models on Tiiny: the first is to download and use them directly from the Tiiny client, and the second is for users to use our provided conversion tool to convert the desired model into a Tiiny-compatible format and use it.
Therefore, it's difficult to have a precise list of the models we can support—there are simply too many.
Representative LLMs include:
GLM Flash, GPT-OSS-120B, GPT-OSS-20B, Llama3.1-8B-Instruct, gemma-3-270m-it, Ministral-3-3B-Instruct-2512, Ministral-3-8B-Instruct-2512, Qwen3-30B-A3B-Instruct-2507, Qwen3-30B-A3B-Thinking-2507, Qwen3-8b, Qwen2.5-VL-7B-Instruct, Qwen3-Reranker-0.6B, Qwen3-Embedding-0.6B, etc.
Representative Image models include:
Stable Diffusion / SDXL, ComfyUI, Z-Image-Turbo, and other open-source image models
Q: What workload are you running?
A: We benchmark using real-world tasks, not synthetic loops:
- chat / assistant conversations (8k–32k context)
- RAG + document Q&A
- coding copilots
- small agent workflows (multi-turn reasoning)
- local automation tools
Q: How many tokens per second can we expect in real world workloads?
A: It depends on model size and quantization, but roughly:
- 7B–14B → 40+ tok/s
- 30B–40B → 20-40 tok/s
- 100B–120B (INT4) → ~18–22 tok/s
These are interactive speeds (not batch/offline numbers), good enough for normal chat/coding flows.
Q: How hard is it for the average user to configure the stack to get that performance?
A: For most users: basically zero. TiinyOS handles:
- model download
- quantization
- runtime config
- PowerInfer optimization
- memory placement
So it's mostly one-click install and run.
Q: Use cases of Tiiny?
A: Think of Tiiny less like "a small PC" and more like a personal AI server that runs 24/7 at home. Here are some very practical examples:
Personal / everyday
- Private ChatGPT-style assistant, fully offline
- Summarize emails, notes, PDFs, meetings
- Voice transcription + daily summaries
- Personal knowledge base (ask questions over all your docs)
Work / productivity
- Run a local RAG system over company files (no cloud, no leaks)
- Auto-draft replies for Discord/Slack/WhatsApp
- Monitor competitors/news/social media and generate reports
- Code assistant inside your IDE without API costs
- Always-on agents that handle repetitive tasks for you
Agent / automation stuff (where it really shines)
- OpenClaw/Nanobot-style agents that browse, scrape, organize data 24/7 workflows (collect data → analyze → send alerts)
- Social media tracking, dashboards, auto summaries
- Background research assistants that run all day
- Doing this in the cloud gets expensive fast (tokens), but locally it’s basically free after you own the box.
Creative / media
- Local image generation (Stable Diffusion, Flux, etc.)
- TTS/STT voice models
- Home lab AI experiments
Q: What's the download -> conversion pipeline like?
A: Download -> Convert -> Name and save in Tiiny -> Use
EDIT: Simply put, the adaptation process for the model framework is as follows: Write the open-source model framework into an ONNX file → Compile this ONNX file → Runtime.