Vectorize is a data platform for retrieval augmented generation (RAG). It combines RAG evaluation to identify the best way to vectorize your data with a cloud-scale RAG pipeline engine. Vectorize populates your vector database and keeps your vector data fresh.
Hi Product Hunters! 🏹
I’m excited to introduce Vectorize, a cloud data integration platform designed to make building AI apps faster and with less hassle. We solve the tough, annoying parts of implementing Retrieval-Augmented Generation (RAG) applications so you can focus on the fun parts of AI development. Here’s how:
🔄 Automate Data Extraction: Seamlessly pull data from documents, SaaS platforms, and more. Forget manual data wrangling—we take care of it.
🗂️ Source Connectors: Connect to a variety of sources, including Amazon S3, Azure Blob Storage, Confluence, Discord, Dropbox, Google Drive, Google Cloud Storage, Intercom, and more.
📊 Vector Databases: Supports integrations with Astra DB, Couchbase Capella, Elastic Cloud, and Pinecone
🧪 RAG Evaluation: Automatically test and find the best vectorization strategy for your unique data. Instead of writing throw-away code to try different embedding models, let us handle it for you.
⚡ Real-Time RAG Pipelines: Keep your vector indexes fresh and up-to-date. We take care of data ingestion issues like error handling, retries, and back-pressure so you don’t have to spend time troubleshooting.
⏱️ Accelerate AI Development: From concept to deployment, we help you move faster by automating the difficult parts of RAG implementation. Your vector indexes will stay current without the constant manual upkeep.
🎯 Stay Accurate & Relevant: We ensure your data is always fresh and your AI stays accurate. You’ll have real-time visibility into your vector data and know exactly what’s being processed.
💸 Cost-Effective: We offer a forever free tier for developers, and as your needs grow, our pricing scales affordably with you.
📈 Scalable & Flexible: Whether you’re a startup or an enterprise, Vectorize adapts to your needs. It integrates with your existing vector database, so you maintain full control over your data.
I hope you will give us a try. If you do, I’d love to hear your feedback here in the comments!
Chris Latimer
Co-Founder & CEO, Vectorize
This is extremely useful for anyone building LLM applications. Currently evaluating!
This is a very useful data platform for RAG. everyone can vectorised their data with RAG.Thank you.
Interesting. Going to give this a try. Haven't been super thrilled by the various RAG services yet so hoping this does the job.
I'm an idiot when it comes to this stuff, but it seems this would be great for e.g. generating content in the style of e.g. my twitter history, or like, articles on Techcrunch?
Keeping vector indexes fresh without extra manual steps is such a benefit when data is constantly changing.
Huge congrats to the Vectorize team on today's launch! I'm intrigued by the promise of optimized RAG pipelines tailored to specific data. Quick question: How do you handle scenarios where the underlying data structures or schemas are constantly evolving - does Vectorize's auto-vectorization adapt to these changes in real-time?
@chrislatimer
Congrats on launching Vectorize! Excited about how it helps with RAG and keeps data fresh. The cloud-scale RAG pipeline engine sounds powerful. Great for anyone needing efficient data vectorization.
Love your ideas @chrislatimer but I’d suggest including more integration options with popular data platforms for wider adoption. Overall amazing work.
Great job @chrislatimer but I’d suggest adding a visualization dashboard for data flow and freshness indicators which would be super helpful for monitoring data updates.
Great job @chrislatimer Would love to know more as that would make it incredibly versatile for varied datasets. Great work keep it up.
@chrislatimer does Vectorize support hybrid search, like combining both traditional keyword and vector search? Overall good work.
This is exactly what I needed for our RAG implementation! Been wrestling with vector databases and data pipelines for weeks, and Vectorize just handles all the messy parts. The automatic embedding model testing is brilliant - saved me hours of trial and error. Plus, the forever free tier means I can actually experiment without worrying about costs. Solid work on solving a real pain point! 🚀
