LM Studio
Ollama
GPT4All
Jan.ai
AnythingLLM
ChatGPT
llama.cpp
Claude AI
Threadbound
Notion
Threadbound turns messy Slack threads into clean, structured docs in Notion.
Important decisions happen in Slack threads and then disappear the moment the conversation moves on, buried under sidetracked replies and a wall of ๐ reactions. Threadbound fixes that.
React to any message in a thread with a configured emoji, and Threadbound:
No manual write-ups. No "can someone document this." React, and the doc shows up in your team's Notion database, linked back to the original thread.
Free to start, with unlimited captures on paid plans.
LM Studio ThreadboundThreadbound's answer:
General AI assistants inside Slack (like Notion's own Custom Agents or Atlassian Rovo) are built to answer questions and search your workspace on demand. Threadbound does one thing specifically: turn a single thread into a permanent, structured record the moment someone reacts to it, no prompting, no asking the AI a question, no separate workflow to remember. It's a single emoji react, not a tool you have to learn.
Threadbound's answer:
Most Slack summarizer tools give you a paragraph. Threadbound gives you a document: a summary, the decisions that were made with the reasoning behind them (when it was actually stated in the thread), and any action items pulled out as checkboxes, published straight to Notion. It's also built for reliability rather than just a single API call, if one model returns a malformed or low-quality result, it automatically retries or falls back to another model rather than publishing something broken.
Threadbound's answer:
Small to mid-sized teams, mostly engineering and product teams, who already run Slack and Notion side by side and make a lot of decisions asynchronously in threads. It's built for teams that feel the pain of "wait, what did we actually decide?" a few times a week, not occasionally.
Threadbound's answer:
It started from a personal frustration: important decisions kept happening inside long Slack threads, and a week later nobody could reconstruct what had actually been agreed on, just an endless scroll and a pile of reactions. What began as a simple "summarize this thread" bot turned into a more serious project once it became clear that getting reliable, correctly-formatted output out of an LLM consistently is the actual hard part, not calling the API.
Threadbound's answer:
Next.js and TypeScript for the app, hosted on Vercel, with Supabase for the database and auth. It integrates with the Slack Web API and the Notion API, uses Stripe for billing, and the LLM layer is built on the Vercel AI SDK with support for multiple providers (Claude, Gemini, and others) so it isn't locked to a single model.
Based on our record, LM Studio seems to be more popular. It has been mentiond 58 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I use Bionic (https://lmstudio.ai) and various local models like Qwen Coder Next to work on various tasks. Honestly, none of the models that are runnable on a typical MacBook Pro come close to the cloud-based frontier models (open or closed) but Bionic provides a nice experience and makes trying new models out trivial. - Source: Hacker News / 2 days ago
They hid it well at the bottom of the page: https://lmstudio.ai/. - Source: Hacker News / 24 days ago
A good place to browse is the LocalLLaMa subreddit. [0] A good software to start is LM Studio [1]. Another popular alternative is Ollama [2]. A better software when you're used to it all is llama.cpp as it's usually a bit faster and more frequently updated [3]. A good place to get models is HuggingFace, particularly the Unsloth models [4] Most popular models lately to run on "regular" gaming PC's, workstations,... - Source: Hacker News / about 2 months ago
LM Studio wraps the same inference engine in a desktop application with a visual model browser, one-click downloads from Hugging Face, and a built-in chat interface. - Source: dev.to / about 2 months ago
LM Studio is the reference standard for running local models. It's not really an "AI client" in the workspace sense โ it's a local inference engine with a chat UI attached. Its MLX backend on Apple Silicon is noticeably faster than Ollama for many models, especially on larger ones, though both now use MLX on Mac so the gap has narrowed over time. The built-in model browser lets you discover, download, and run... - Source: dev.to / about 2 months ago
Ollama - The easiest way to run large language models locally
Notion - All-in-one workspace. One tool for your whole team. Write, plan, and get organized.
GPT4All - A powerful assistant chatbot that you can run on your laptop
Jan.ai - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs like OpenAIโs GPT-4 or Groq.
AnythingLLM - AnythingLLM is the ultimate enterprise-ready business intelligence tool made for your organization. With unlimited control for your LLM, multi-user support, internal and external facing tooling, and 100% privacy-focused.
ChatGPT - ChatGPT is a powerful, open-source language model.