Relevance AI

Relevance AI is a platform that helps developers and businesses build and deploy AI-powered applications, particularly focusing on vector search and retrieval-augmented generation (RAG) workflows. It provides tools for managing embeddings, building semantic search, and integrating with large language models.

• Offers a vector database and search API for semantic similarity and hybrid search.
• Supports building RAG pipelines with features like chunking, embedding, and reranking.
• Provides a no-code interface for creating AI agents and workflows.
• Integrates with popular LLMs and data sources for custom AI solutions.
• Founded in 2021 and based in Australia, with a focus on developer-friendly tools.

Relevance AI is an Australian-founded startup that provides a platform for building and deploying AI agents and multi-agent workflows without heavy coding. It positions itself around letting companies create an 'AI workforce' to automate tasks across sales, marketing, research, and operations.

• Founded around 2020, originally focused on vector embeddings and semantic search before pivoting more toward AI agents.
• Co-founded by Daniel Vassilev and Jacky Koh, headquartered in Sydney, Australia with a US presence.
• Offers a low-code/no-code platform to build AI agents and chain them into multi-agent teams.
• Raised venture funding from investors including Insight Partners and King River Capital.
• Common use cases promoted include sales prospecting, lead enrichment, research, and content workflows.