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Relevance AI

Chain prompts & transformations for custom AI experiences.
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What is Relevance AI?

Relevance AI offers a platform where users can build and manage an “AI Workforce” consisting of digital agents designed to handle routine and repetitive tasks. The agents are equipped with tools specifically tailored to individual businesses, developed by domain experts. Users can create these agents using a no-code workflow builder and deploy them within their organization as part of a multi-agent system. Relevance AI supports various large language models such as OpenAI, Anthropic, Cohere, and Palantir. The platform ensures data security by storing datasets in a SOC 2 Type II compliant environment and not retaining user inputs or outputs.



⚡Top 5 Relevance AI Features:

  1. AI Workforce: A digital team of agents equipped with tools specific to your business operations, designed by domain experts.
  2. No-Code Platform: Allows users to build AI teams without requiring coding knowledge.
  3. LLM Chains: Combines multiple steps of large language models with other transformations to build advanced functionality and features.
  4. Multi-Agent Systems (MAS): Deploy AI tools as a shareable app, embeddable form or an API endpoint within your organization.
  5. Support for Multiple Providers: Supports OpenAI, Anthropic, Cohere, PaLM, and more; users can request additional providers through live chat.



⚡Top 5 Relevance AI Use Cases:

  1. Personalized Outreach: An AI agent that learns about leads and their companies to send customized emails, initiating qualification processes.
  2. Automated Meeting Scheduling: An AI agent autonomously schedules meetings with sales-ready leads.
  3. Document Retrieval: Utilizes LLM chains to retrieve relevant documents based on user queries.
  4. Vector Search: Enables users to search for specific vectors within large datasets.
  5. API Requests: Allows integrating external APIs into AI workflows for enhanced functionality.

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