https://www.cassidyai.com/blog/cassidy-vs-relevance-ai

Cassidy vs Relevance AI: The Difference Between AI That Adapts to Your Business - and AI That Asks You to Adapt to It

Cassidy Team, Nov 28, 2025

Overview

By now, you’ve seen the promise.

AI that can take work off your plate. Agents that operate like employees. Automations that run entire processes without a human touch. But when you get past the marketing pages and into the platforms themselves, two philosophies quickly emerge.

There’s AI that slots into your business, working alongside your team, using your data, your tools, and your workflows. And then there’s AI that wants your business to adapt to it, to learn its structure, speak its language, and shift processes to match how it thinks things should work.

Relevance AI falls into that second camp. It’s a platform built around the idea of “AI employees” — agent personas with names, titles, and predefined routines. It’s clean, visual, and opinionated. But it comes with limitations. You operate how the platform is designed, or you don’t operate at all.

Cassidy isn’t built to show off AI employees. It’s built to strengthen your business.

Cassidy vs Relevance AI

We built a platform that lets your actual team automate real work. With custom workflows, AI Assistants, full-text reasoning, and deep tool integration, all running on a no-code interface built for anyone to pick up and understand.

This is the difference between AI designed for outcomes, and AI designed for outputs.

Below is a complete breakdown of how Cassidy compares to Relevance AI — from automation style to integration depth to enterprise fit.

Relevance AI: AI Agents You “Hire” and Connect

Relevance AI markets itself as a way to build and manage your own “AI workforce.” You assign digital agents to roles like lifecycle marketer, support specialist, or researcher. Each comes with a preset scope and a set of workflows that define what it can and cannot do.

That structure makes it easy to get started, but hard to customize. Want to modify a flow? You will need to adjust logic, handoff conditions, and model behavior. Need a new use case that doesn’t fit an existing agent? You will need to spin up a new persona from scratch or adapt your use case to the closest available fit.

Cassidy: Custom Automations That Map to Your Business

Cassidy doesn’t ask you to adapt your processes to prebuilt AI personas. Instead, it helps you build AI-powered workflows around how your business already operates.

You can trigger actions from any tool, apply reasoning at each step, and design end-to-end automations that fit your needs. This isn’t just for developers. Business users from CS leads to ops managers … and anyone in between — they all use Cassidy every day to automate their most valuable work without writing code.

Setup Experience

The platform you choose needs to empower more than just your technical team. It should help everyone build confidence.

Relevance AI: Requires Low-Code Logic and Configuration

While Relevance AI offers a visual interface, its real power relies on low-code customization. Building or modifying agents means configuring logic statements, triggers, or JSON-like structures. That’s doable for technical users, but it slows down non-technical teams who don’t have time to learn a new system.

Cassidy: Built for No-Code from the Start

Cassidy makes AI automation approachable.

Whether you start with a blank canvas or use the Copilot to describe what you want, Cassidy walks you through the process with drag-and-drop steps and visual logic that anyone can understand.

No technical experience required. You don’t need to configure APIs, write conditions, or figure out syntax. Just build what your team needs.

AI Capabilities: Rigid Logic vs Contextual Reasoning

Both Cassidy and Relevance AI incorporate multiple large language models — including GPT-4, Claude, and Gemini — but the way each platform applies that intelligence leads to very different outcomes.

Relevance AI uses these models inside siloed agents. Cassidy embeds them across end-to-end workflows. That distinction matters more than the models themselves.

Relevance AI: Structured, Single-Purpose Agents

Relevance AI’s agents are designed for consistency. Each one is built for a fixed role, like researcher or copywriter, and executes a narrow process reliably.

But they are limited by structure. If a task includes unexpected inputs or spans multiple systems, you need to define logic for every edge case. These agents don’t adapt or share memory. And when multiple agents are involved, collaboration becomes friction.

You end up managing workflows like a team of bots, not a system.

Cassidy: Context-Aware Automation That Grows With You

Cassidy embeds intelligence across every step of your workflows. It does not rely on fixed roles or personalities. Instead, it gives you the ability to build logic that uses memory, understands documents, interprets real-time data, and generates accurate outputs.

This enables real business impact across workflows:

Generate polished proposals by combining CRM insights, pricing rules, and recent activity, then send them for approval automatically.
Draft accurate responses by analyzing sentiment, summarizing history, and referencing internal knowledge.
Answer internal questions with context-aware replies, customized by location, policy, or access level.
Review documents for risky language, suggest compliant edits, and highlight prior decisions for comparison.

The possibilities are endless. Which is why our use case library continues to grow almost daily. As we continue to see a variety of ways that people in different positions use Cassidy.

Integrations: App Layer vs Embedded Infrastructure

Integration depth determines how well a platform fits your existing stack.

Relevance AI: API-Level Access With Limitations

Relevance AI connects with tools like Intercom, Notion, and HubSpot — but usually just to move data in or out of an agent. Customizing beyond that requires managing API keys, structuring payloads, and understanding each app’s configuration.

That limits what business users can build on their own.

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Cassidy: 100+ Deep Integrations and Counting

Cassidy connects natively to over 100 widely used tools across teams and industries — with full bi-directional access.

Some of the most popular integrations include:

Business Tools: Salesforce, Slack, Notion, Zendesk, SharePoint, HubSpot, Asana, Airtable, Google Sheets, Intercom, Typeform, Linear
Data Infrastructure: Postgres, MongoDB, Snowflake, BigQuery, Amazon S3, Datadog
DevOps + Extensibility: Internal HTTP APIs, secure webhooks, token-auth systems, CLI triggers, script-based actions

You can ingest data, reason over it, and push results out — all in one unified, no-code interface.
Non-technical users can build across systems, while technical teams can customize and extend where needed.

Security and Compliance: Enterprise-Ready or Just Checkboxes?

Automation touches sensitive systems and data. The right platform should treat security as foundational.

Relevance AI: Meets the Basics, Leaves Gaps

Relevance AI supports SOC 2 Type II and GDPR. That’s enough for many mid-market teams — but not enough for regulated industries or enterprises with strict controls.

There’s no HIPAA support, no row-level permissions, and no CASA alignment. Role-based access exists, but lacks granularity, making permissioning hard to manage at scale.

Cassidy: Built for Enterprise From the Ground Up

Cassidy meets modern security, privacy, and compliance standards — out of the box.

SOC 2 Type I and II
HIPAA, GDPR, and CASA aligned
Role-based access control (RBAC)
Row-level security
SSO and SCIM support
End-to-end encryption
Detailed audit logs and approval tracking

There’s nothing extra to bolt on or configure. Security is built into every layer of the platform. Because we understand that when it comes to enterprise security, every base has to be covered.

Reporting and ROI Tracking: Outcomes or Guesswork?

Relevance AI: Limited Dashboarding

Once your agents are live, Relevance AI tracks basic usage stats — how many times they’ve run, and what actions they performed. But there’s no clear way to define success or track outcomes like hours saved or content produced.

That makes it harder to justify investment, or expand adoption beyond early users.

Cassidy: ROI Reports and Guided Expansion

Cassidy includes real-time analytics, monthly ROI summaries, and quarterly reviews with your AI success manager. You’ll know what workflows are working, how much time you’re saving, and where to scale next.

You’re not just automating tasks, you’re tracking the outcomes.

You Don’t Need an AI Workforce. You Need AI That Works for You.

Relevance AI offers a structured, visual metaphor for work. But that structure comes with boundaries. It’s a good place to explore the idea of AI agents — until your real-world complexity gets in the way.

Cassidy is different. It doesn’t ask how your business is shaped. It asks what outcome you want to drive.

You get automations built around real data, real context, and real systems, with governance, flexibility, and results that scale across the enterprise.

If your goal is to experiment with AI agents, Relevance AI is a solid place to begin. If your goal is to automate meaningful work across every role and cross-functions, Cassidy is here to elevate your business.

If you’d like to learn more, book a demo today.