This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
RemiAI
Local AI assistant with powerful tools.
RemiAI is a local AI assistant designed to help you interact with your files, run searches, and connect to external tools (MCP servers). It is built with Next.js, TypeScript, and the AI SDK libraries, offering a lightweight, self‑hosted alternative to cloud‑based assistants.
Have you considered adding a built-in vector store option so the local assistant can index files for semantic search right out of the box. That would make it way more useful for people working with large doc collections without needing to bolt on a separate database.
About RemiAI on Product Hunt
“Local AI assistant with powerful tools.”
RemiAI was submitted on Product Hunt and earned 0 upvotes and 5 comments, placing #45 on the daily leaderboard. RemiAI is a local AI assistant designed to help you interact with your files, run searches, and connect to external tools (MCP servers). It is built with Next.js, TypeScript, and the AI SDK libraries, offering a lightweight, self‑hosted alternative to cloud‑based assistants.
On the analytics side, RemiAI competes within Productivity, Artificial Intelligence, GitHub and Virtual Assistants — topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how RemiAI performed against the three products that launched closest to it on the same day.
Who hunted RemiAI?
RemiAI was hunted by Nicolas H.. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of RemiAI including community comment highlights and product details, visit the product overview.
Nicolas H.
Have you considered adding a built-in vector store option so the local assistant can index files for semantic search right out of the box. That would make it way more useful for people working with large doc collections without needing to bolt on a separate database.