Vectara lands $28.5M to supercharge enterprise search

Vectara lands $28.5M to supercharge enterprise search

a year ago
Anonymous $KxGqLmj_R3

https://techcrunch.com/2023/06/13/vectara-lands-28-5m-to-supercharge-enterprise-search/

Some years ago, three former Googlers — Amr Awadallah (who previously founded Cloudera), Amin Ahmad and Tallat Shafaat — set out to build what they describe as a “conversational search” platform for the enterprise. Their goal was to help organizations unlock data from their text-based files, chiefly by empowering developers to build conversational AI apps that can retrieve and summarize text from vast corporate data stores.

The fruit of their labor, Vectara, launched in late May. Backed by $28.5 million in seed funding led by Race Capital with participation from Emad Mostaque, the founder of Stability AI (the AI startup behind the text-to-image system Stable Diffusion), Vectara provides AI-powered, API-based search tech that it claims can handle queries of an arbitrary length, level of ambiguity and language across troves of multilingual documents.

Vectara lands $28.5M to supercharge enterprise search

Jun 13, 2023, 5:33pm UTC
https://techcrunch.com/2023/06/13/vectara-lands-28-5m-to-supercharge-enterprise-search/ > Some years ago, three former Googlers — Amr Awadallah (who previously founded Cloudera), Amin Ahmad and Tallat Shafaat — set out to build what they describe as a “conversational search” platform for the enterprise. Their goal was to help organizations unlock data from their text-based files, chiefly by empowering developers to build conversational AI apps that can retrieve and summarize text from vast corporate data stores. > The fruit of their labor, Vectara, launched in late May. Backed by $28.5 million in seed funding led by Race Capital with participation from Emad Mostaque, the founder of Stability AI (the AI startup behind the text-to-image system Stable Diffusion), Vectara provides AI-powered, API-based search tech that it claims can handle queries of an arbitrary length, level of ambiguity and language across troves of multilingual documents.