Relevance AI has introduced a powerful developer-first vector platform to help developers do more with unstructured data and aid data scientists to rapidly experiment with vectors.
Relevance AI’s products are already used by more than 3 million end users, with 100 million weekly requests across all sectors including SaaS, e-commerce, education and gaming.
Relevance AI attracts substantial funding
Relevance AI will use the funding to expand its global client base and double its headcount.
“Most businesses and organisations are not effectively utilizing vectors and are only relying on structured data analysis to salvage quantitative insights for decision making.”
“However, 80% of business data is unstructured that comes in forms such as text, images, audio, user interactions and other formats” said Relevance AI’s co-founder Jacky Koh.
“We are thrilled to secure this funding as it enables us to grow our team, continue pushing the industry boundaries, plus building a reliable and valuable product for our customers.”
“With this marvelous opportunity to leverage this incredible backing and unique perspective of the team at Insight Partners, we expect to grow rapidly over the next year.”
Relevance AI’s stakeholders’ comments
George Mathew, the Managing Director at Insight Partners expressed optimism.
“Only the tech giants have previously leveraged vectors in their machine learning architectures. Relevance AI enables companies of all sizes to leverage vector-based technology.”
“Relevance AI’s incredibly strong founding team has created an advanced API powered platform which has positioned the company as an innovative, early enterprise leader.”
“We are excited for partnering with Relevance AI as it continues to scale and grow.”
Relevance AI’s goal is to empower developers with the ability to experiment and analyse vectors for unstructured data analysis and to democratise a technique that is nearly exclusively used by large technology companies such as Google, Facebook, TikTok and Spotify.
Relevance AI harnesses vectors
Vectors are a specialized format that creates a high dimensional numerical representation of unstructured data for a computer to extract more semantic meaning and similarity out of it.
With vectors, developers and data scientists can use it to match data on semantic similarity.
Being facilitated with vector tools so as to determine similarity enables a wide range of applications such as semantic search, product recommendations and topic analysis.
Google vectorizes text data from search queries and web content to create the most powerful search engine that semantically matches a text query to the most relevant pages.
Spotify vectorizes music lyrics, audio, and reviews to find the most semantically similar songs to the songs you listen to help create the most personalized and addictive discovery playlist.
TFTactics is a gaming application that has been able to build an AI coach that collects unstructured game actions of their millions of users and performs an unstructured data analysis like identifying different cohort of play styles and most similar players.
Relevance AI’s Discovery engine is also available to customers as a simple way to indulge into the world of vectors as it’s embedded with a specialised API which simplifies the process for companies wanting to build a more powerful set of discovery features.
Guided onboarding and self-service are also available in the Relevance AI platform.