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Vec
Speak, and be answered out loud, in the language you spoke.
A voice interface that hears you in any of twenty-two Indian languages and answers out loud in the same one, grounded in the vector store you connect.
Your vector store can answer questions. It just can't talk.
A Pinecone index. A Postgres with pgvector. A dataset parked in HuggingFace.
Today you reach them with code. Vec lets you just ask — out loud.
https://voice-vec.vercel.app
Because Vec holds no corpus of its own. Nothing to ingest, no schema to match,
no data handed over. You connect your own store with your own keys, and the
question is answered from that.
→ Retrieve — Pinecone, Astra, or your own Postgres + pgvector
It reads your table's columns and builds the search from what it finds.
→ Compute — a HuggingFace repo, or any .csv / .parquet URL
Paste the link and it's answerable in SQL, over rows nobody embedded.
→ Act — Gmail, Slack, Notion, GitHub, via your own Composio project
"Check my inbox" stops being a question and becomes a call.
The agent is never handed a menu of what you own. It holds one tool and goes
looking — so the prompt grows with the question, not with your account.
All of it spoken in 22 Indian languages, answered in the one you asked in —
whatever language your index was written in. 1.9s from the moment you stop
speaking to the first audio out.
Open source. Every credential stays yours.
🎙️ https://voice-vec.vercel.app
💻 github.com/Hitesh-s0lanki/voice-vec
Connect your index and ask it something you'd normally write a query for.
#VectorDatabase #AgenticRAG #pgvector #VoiceAI #AIAgents #OpenSource
About Vec on Product Hunt
“Speak, and be answered out loud, in the language you spoke.”
Vec was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #125 on the daily leaderboard. A voice interface that hears you in any of twenty-two Indian languages and answers out loud in the same one, grounded in the vector store you connect.
On the analytics side, Vec competes within Developer Tools, Artificial Intelligence, GitHub and Audio — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Vec performed against the three products that launched closest to it on the same day.
Who hunted Vec?
Vec was hunted by Hitesh Solanki. 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 Vec including community comment highlights and product details, visit the product overview.
Hitesh Solanki