Vectorize is now generally available!
Anyone who’s built an AI application using retrieval-augmented generation (RAG) knows how frustrating it can be. Most of your data is in places it’s not easy to access: buried deep in file systems, trapped inside SaaS platforms, or tucked away in knowledge bases.
Once you’ve figured out a way to extract your data, you still need to get it into a format your large language model (LLM) can use. You have to figure out which embedding model and chunking strategy works best for your data set, and build a RAG pipeline that populates your vector database.
After all that effort, you might find that your RAG application doesn’t work as well as you’d like. Your vector database returns irrelevant context, and your LLM generates poor responses, leaving you with subpar results.
We built Vectorize to tackle these pain points, giving developers a way to solve these data problems and deliver a high performing RAG application in a tiny fraction of the time.
Production-Ready RAG Pipelines
LLMs need seamless access to your data. Vectorize makes this possible with production-ready RAG pipelines which connect to structured, unstructured, and semi-structured data sources. These pipelines turn your data into search indexes in your vector database that are optimized for RAG.
Vectorize offers a growing number of connectors to source systems to allow you to quickly ingest your data. As new use cases emerge, this is a critical capability because data ingestion needs come not just from files and documents, but from every corner of your organization’s data portfolio.
With integrations to popular vector databases, Vectorize gives you complete control and ownership over your data.
Best of all, Vectorize can tell you up front how to best build your RAG pipeline, ensuring your LLM always has the most relevant context for inference.
RAG Evaluation
Vectorize allows you to take a data-driven approach to identifying the optimal strategy to vectorizing your data. It does this using a state-of-the-art RAG evaluation engine that’s built directly into the platform.
The RAG evaluation capabilities in Vectorize allow you to get quantitative insights into the best performing strategies for vectorizing your data. By testing up to four different embedding models and chunking strategies in parallel, you can determine which combination works best.
With the interactive RAG sandbox, you can inspect exactly what data gets returned from your vector database, and test how different LLMs use that data to generate a response.
With Vectorize, you’ll be certain your LLM will have the best data possible.
The Absolute Best Price Performance on the Market
Vectorize is designed to meet the demands of high-volume, mission-critical RAG pipelines. With a cloud-native architecture built for scale, Vectorize delivers top-tier performance while keeping pricing accessible to everyone—whether you’re an enterprise managing large-scale operations or an individual developer working on a side project for fun. With our pay-as-you-go model, you’re only charged for what you use.
Fresh data, on-demand
You never want your LLM responding to users with stale data, which can lead to outdated or irrelevant responses from your LLM. For some use cases, that means real-time change detection and vector database updates. For data that changes less often, that might mean weekly or daily refreshes.
Vectorize gives you full control how often your data is refreshed.
While a pipeline is running and listening for changes, you’ll be charged a low hourly rate. As changes are detected, they’ll be processed immediately. Depending on your requirements, you can configure to have your pipeline run on an interval that works for you such as:
- Real-time 24/7
- Daily
- Weekly
- Weekdays
Or you can use a custom schedule (e.g. M, W, F during business hours). With the Vectorize free tier, you can create a RAG pipeline that updates your data weekly at no cost.
Try Vectorize Free through October 2024
We’re offering access to our premium product plans at no cost through the end of October 2024, giving you the chance to explore everything Vectorize has to offer, risk-free.
To get started with Vectorize, visit https://platform.vectorize.io and sign up for a free account.