AI SDR
Relevance AI
by Relevance AI
523 reviews
AI agent platform for building custom sales and marketing automation workflows with pre-built templates and no-code tools
📌Key Takeaways
- 1Relevance AI is a ai sdr AI agent by Relevance AI, founded in 2020.
- 2AI agent platform for building custom sales and marketing automation workflows with pre-built templates and no-code tools
- 3Top strengths: No‑code AI Agent Builder: A visual drag‑and‑drop interface lets non‑technical users create AI agents by describing desired behavior in plain language, selecting LLMs, and addin...; Multi‑agent Workforce: The Workforce feature lets users assemble hierarchies of specialized agents that collaborate like human teams. Agents can hand off tasks, share knowle....
- 4Rated 4.0/5 based on 523 reviews.
Category
AI SDR
Founded
2020
Headquarters
Surry Hills, New South Wales, Australia and San Francisco, California, USA
Overview
Relevance AI is a no‑code platform that lets subject‑matter experts build, deploy, and manage teams of autonomous AI agents to automate sales‑development tasks. The product combines a drag‑and‑drop agent builder, a multi‑agent "Workforce" canvas, and integration with over 2,000 third‑party tools (CRM, email, Slack, Google Workspace, etc.). By ingesting structured and unstructured data—such as equipment manuals, regulatory documents, news feeds, and company websites—its SDR agents can perform rapid prospect research, generate hyper‑personalized outreach messages, prioritize leads based on trigger events, and maintain consistent follow‑up sequences. The platform runs on AWS Bedrock and supports leading large language models (Claude Sonnet 4.5, Gemini, OpenAI), offering both free and credit‑based pricing that scales with usage. Enterprises benefit from SOC 2 and GDPR compliance, role‑based governance, and analytics dashboards that surface engagement metrics. Customers range from mid‑market SaaS firms to Fortune 500 manufacturers, with reported 2‑3× increases in qualified meetings and ROI figures as high as 3,000 % for some deployments. Relevance AI positions itself as an "agentic‑first" alternative to traditional rule‑based automation, enabling sales development reps to focus on high‑value conversations while the AI handles research, messaging, and routine coordination.
🎯 Key Differentiator
AI-ExtractedAgentic‑first no‑code multi‑agent system that lets non‑technical subject‑matter experts build, deploy, and manage autonomous AI teams
Source 5 describes the "agentic‑first approach" and integration with 2,000+ tools; Source 7 highlights Claude Sonnet 4.5 integration across the platform, confirming the unique combination of low‑code team orchestration and cutting‑edge LLMs.
This differentiator was AI-extracted from competitive research.
Claim this page to verify and unlock →Last verified: January 27, 2026
Key Features
No‑code AI Agent Builder
A visual drag‑and‑drop interface lets non‑technical users create AI agents by describing desired behavior in plain language, selecting LLMs, and adding tools. The builder abstracts model prompting, tool configuration, and workflow logic, enabling rapid prototyping and deployment without writing code. Empowers subject‑matter experts to automate complex sales tasks without relying on engineers, shortening time‑to‑value.
Multi‑agent Workforce
The Workforce feature lets users assemble hierarchies of specialized agents that collaborate like human teams. Agents can hand off tasks, share knowledge bases, and trigger one another via API, webhook, or built‑in triggers, supporting end‑to‑end sales processes from research to meeting booking. Scales complex, multi‑step sales workflows while preserving human‑like decision quality.
2000+ Integrations & Tool Library
Relevance AI ships with pre‑built connectors for CRMs (Salesforce, HubSpot), email platforms, calendars, databases, and cloud services. Users can also add custom HTTP or Zapier triggers, allowing agents to read/write data across the entire tech stack. Eliminates manual data entry and enables agents to act directly in the tools sales teams already use.
Credit‑based Scalable Pricing
Plans allocate a monthly credit pool (e.g., 10,000 credits for Pro) that is consumed per agent action, with optional extra vendor credits for higher‑capacity LLM usage. Credits reset monthly, and unused credits roll over on Enterprise plans. Aligns cost with actual usage, making the platform affordable for startups and predictable for large teams.
Advanced LLM Support (Claude Sonnet 4.5, Gemini, OpenAI)
The platform integrates the latest large language models, including Anthropic's Claude Sonnet 4.5 with up to 1 million‑token context windows, and offers a "Bring Your Own LLM" option for custom deployments on AWS Bedrock. Delivers higher reasoning quality, longer context handling, and competitive performance for complex sales conversations.
Pros & Cons
Pros
- +No‑code AI Agent Builder: A visual drag‑and‑drop interface lets non‑technical users create AI agents by describing desired behavior in plain language, selecting LLMs, and addin...
- +Multi‑agent Workforce: The Workforce feature lets users assemble hierarchies of specialized agents that collaborate like human teams. Agents can hand off tasks, share knowle...
- +2000+ Integrations & Tool Library: Relevance AI ships with pre‑built connectors for CRMs (Salesforce, HubSpot), email platforms, calendars, databases, and cloud services. Users can also...
- +Credit‑based Scalable Pricing: Plans allocate a monthly credit pool (e.g., 10,000 credits for Pro) that is consumed per agent action, with optional extra vendor credits for higher‑c...
- +Advanced LLM Support (Claude Sonnet 4.5, Gemini, OpenAI): The platform integrates the latest large language models, including Anthropic's Claude Sonnet 4.5 with up to 1 million‑token context windows, and offe...
Cons
- −Requires setup and configuration
- −Less turnkey than dedicated AI SDR tools
- −Learning curve for complex workflows
Use Cases
Explore all AI SDR use cases →Manufacturing SDR Outreach Automation→
Sales development reps in heavy‑equipment manufacturing spend days manually reviewing equipment manuals, compliance documents, and plant‑level news to understand each prospect’s technical environment. This research overhead limits the number of daily outreach attempts, leads to generic messaging, and often misses critical trigger events such as plant expansions or new regulatory requirements, resulting in low meeting conversion rates.
Industry Research Tool for SDR Personalization→
Company Research with Website Tool→
Verisoul Multi‑Agent Team for Scalable Outreach→
MongoDB Customer Lead Qualification→
Frequently Asked Questions
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