Open Source data framework with a fast real-time extraction engine and robust pre-built extractors. Build AI applications with reliability and precision, driving smarter decisions from enterprise data.
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To keep responses accurate, LLMs need access to up to date data. Indexify extracts continuously in near real-time (< 5ms) to ensure the data your LLM application depends on is current, without you needing to think about CRON jobs or reactivity.
To keep responses accurate, LLMs need access to up to date data. Indexify extracts continuously in near real-time (< 5ms) to ensure the data your LLM application depends on is current, without you needing to think about CRON jobs or reactivity.
Indexify is multi-modal and comes with pre-built extractors for unstructured data, complete with state of the art embedding and chunking. You can create your own custom extractors using the Indexify SDK, too.
Indexify is multi-modal and comes with pre-built extractors for unstructured data, complete with state of the art embedding and chunking. You can create your own custom extractors using the Indexify SDK, too.
Just because your data is unstructured doesn't mean it needs to be difficult to retrieve. Indexify supports querying images, videos, and PDFs with semantic search and even SQL, so your LLMs can get the most accurate, up to date data for every response.
Just because your data is unstructured doesn't mean it needs to be difficult to retrieve. Indexify supports querying images, videos, and PDFs with semantic search and even SQL, so your LLMs can get the most accurate, up to date data for every response.
Indexify runs just as smoothly on your laptop as it does across 1000s of autoscaling nodes. Start prototyping with Indexify’s local runtime and when you are ready for production, take advantage of our pre-configured deployment templates for K8s (or VMs) or even bare metal. Everything is observable out of the box, whether its ingestion speed, extraction load or retrieval latency.
Indexify runs just as smoothly on your laptop as it does across 1000s of autoscaling nodes. Start prototyping with Indexify’s local runtime and when you are ready for production, take advantage of our pre-configured deployment templates for K8s (or VMs) or even bare metal. Everything is observable out of the box, whether its ingestion speed, extraction load or retrieval latency.
Cost efficiency for LLMs today is about using the right hardware for the right parts of your stack at the best price points. Deploy Indexify across multiple clouds for maximum flexibility.
Cost efficiency for LLMs today is about using the right hardware for the right parts of your stack at the best price points. Deploy Indexify across multiple clouds for maximum flexibility.
Indexify can be deployed on Kubernetes. It can autoscale and handle any amount of data.
The retreival and extraction systems are instrumented. Know bottlenecks and optimize retrieval and extraction.
Works with existing LLM applications and vector databases. No need to change your existing infrastructure.