What You Can Do with Vector Search

TNS publisher Alex Williams spoke with Ben Kramer, co-founder and CTO of Monterey.ai Cole Hoffer, Senior Software Engineer at Monterey.ai to discuss how the company utilizes vector search to analyze user voices, feedback, reviews, bug reports, and support tickets from various channels to provide product development recommendations. Monterey.ai connects customer feedback to the development process, bridging customer support and leadership to align with user needs. Figma and Comcast are among the companies using this approach. 

In this interview, Kramer discussed the challenges of building Large Language Model (LLM) based products and the importance of diverse skills in AI web companies and how Monterey employs Zilliz for vector search, leveraging Milvus, an open-source vector database. 

Kramer highlighted Zilliz's flexibility, underlying Milvus technology, and choice of algorithms for semantic search. The decision to choose Zilliz was influenced by its performance in the company's use case, privacy and security features, and ease of integration into their private network. The cloud-managed solution and Zilliz's ability to meet their needs were crucial factors for Monterey AI, given its small team and preference to avoid managing infrastructure.

Learn more from The New Stack about Zilliz and vector database search:

Improving ChatGPT’s Ability to Understand Ambiguous Prompts

Create a Movie Recommendation Engine with Milvus and Python

Using a Vector Database to Search White House Speeches

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