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Case Study

Turning Unstructured Data into Insights

How Instabase delivers enterprise-ready AI with Weaviate

The AI Application Platform for Unstructured Data

Instabase is an enterprise-grade AI Application Platform that turns unstructured data into insights, instantly. They solve one of the most acute problems businesses face – slow or inaccurate decisioning due to unstructured data. Their engineering team was looking for a database that would allow them to deliver data insights to their users with a high degree of accuracy and rapid performance. They chose Weaviate because of the flexibility that a leading open-source tool gave them while hitting Instabase’s critical performance metrics better than any other database they tested. Built-in features like hybrid search and distance metrics, as well as support from an engaged developer community, made Weaviate the clear choice for Instabase.


Instabase processes over 500K highly varied documents per day and needs to scale to the ever-growing demand of their customers. They needed a database solution that would allow them to index, store, and retrieve massive volumes of data while delivering results with an incredibly high level of accuracy to their users. “Accuracy determines the amount of savings any large institution can get,” said Shaunak Godbole, Head of Infrastructure Engineering at Instabase. “If the results aren’t accurate or take too long to surface, a human needs to get involved, and the cost savings goes away. So accuracy and speed are critical for us.”  Additionally, Instabase needed to support customers in highly regulated environments. European customers needed to ensure their data didn’t leave certain countries, while financial institutions didn’t want their data to leave their on-premises servers. They needed a database solution that could be deployed anywhere while maintaining a high level of performance. If accuracy, speed, and flexible deployment criteria were not met, Instabase would not be able to reduce the need for human intervention in complex data workflows for their customers.

Why Instabase Chose Weaviate

Instabase wants to empower their customers to focus on making fast and accurate decisions. They achieve this by classifying, extracting, and validating information from highly unstructured data. “The collaboration with Weaviate’s team, the community, and the results of our performance tests made Weaviate an easy choice,” notes Godbole. “In terms of performance, nobody needed convincing – the benchmarks spoke for themselves.”

Weaviate checked all of Instabase’s boxes:

  • Powerful performance: Instabase had their own benchmarks for the use cases they knew they had to solve really, really well. These benchmarks focus on retrieval accuracy and latency, and the queries are complex aggregation and composition where both dense and sparse searches are required. Each use case had different benchmarks, and Weaviate was a clear winner with high retrieval accuracy and low latency for vector search. Once the benchmarking team was convinced Weaviate was up for the challenge, teams across the organization worked together to bring Weaviate into production.
  • High adaptability: By using an AI-native open-source vector database, Instabase could meet their customers wherever they operated, whether in the cloud or on-prem. This allowed for maximum flexibility to fulfill the strict deployment needs of organizations in highly regulated regions and industries.
  • Modular architecture: Instead of having to build out their own capabilities, Instabase developers saved time by using Weaviate’s out of the box features like hybrid search and distance metrics, as well as easy integrations with popular large language models (LLMs).
  • Strong support: Weaviate has cultivated an engaged, open source community with over 6M downloads and tens of thousands of organizations using the platform. Over 5K developers have direct access to the experts and comprehensive documentation they need to quickly problem solve as they build their applications. In addition, Weaviate’s core team was very collaborative with Instabase and was able to provide short, medium and long-term solutions to existing and anticipated challenges.

“Accuracy determines the amount of savings any large institution can get. If the results aren’t accurate or take too long to surface, a human needs to get involved, and the cost savings are greatly reduced. So accuracy and speed are critical for us.”

Shaunak Godbole, Head of Infrastructure Engineering at Instabase

Rapid performance

Instabase is able to store 50K+ tenants in the Weaviate cluster and query data from specific tenants within milliseconds.

Scales to unlimited document size

 Instabase has seen the same impressive results whether customers engage with single-page handwritten notes, 200 pages of documentation, or 400 pages of financial filings.

450+ data types supported

With Weaviate, Instabase was able to support the ingestion and indexing of 450+ data types for a single customer solution.

Instabase helps organizations across large enterprises, mid-market companies, and the federal government solve mission-critical automation problems and obtain insights from unstructured data. Their platform, called AI Hub, enables customers to obtain instant insights in Converse mode. When in Build mode, they can extract data from any content, classify, clean it up and embed the newly structured data downstream into existing systems. These automations enable customers to quickly and accurately make vital business decisions for complex processes like mortgage underwriting, driver’s license verification, or insurance broker submissions. Instabase’s customers include the world’s largest financial institutions, insurance companies, transportation, retail, and public sector organizations.


In 2017, the engineers at Instabase made the choice to build entirely on Kubernetes. They have several microservices that run on top of that and are deeply integrated with the AWS ecosystem, making use of products including AWS EC2, ECS, EKS, ELB, S3, ElastiCache, CDN, and Shield. AWS allows Instabase to build a highly-available, secure, scalable, and performant platform to support even their largest customers.

About Weaviate

Vector databases are becoming core to the AI tech stack because they can handle a very large amount of unstructured data in an efficient way. Weaviate is an AI-native vector database available on the AWS marketplace that can scale to handle billions of vectors and millions of tenants. Customers and community members use Weaviate to power large-scale search and generative AI applications like chatbots and agents. Weaviate’s extensible architecture offers easy pluggability with the AI ecosystem, empowering developers of all levels to build and iterate faster. And flexible deployment options let teams abstract the burden of hosting and managing their database, while still meeting enterprise requirements for security and compliance.

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