Overview

Attio is a modern, AI-native CRM platform designed for go-to-market teams, startups, and growing businesses. Unlike traditional CRMs that treat data as rigid forms, Attio treats customer data as a relational database—allowing teams to create custom objects, associations, and automations without extensive coding or setup.

Key differentiator: Attio combines flexible data modeling with AI-native capabilities built from the ground up. Features like AI Attributes automatically research and classify contacts, while Call Intelligence provides real-time insights during conversations. This isn't AI bolted onto legacy architecture—it's AI woven into the foundation.

With a $50M Series B raised in late 2025, Attio positions itself as "the next gen of CRM" for GTM operators who want to build, not just use. Perfect for product-led and outbound-focused teams (5-200 employees) seeking speed, flexibility, and AI-readiness over enterprise complexity.

Key Features

AI Attributes

Automatically research and classify contacts using AI—enrich profiles with funding rounds, key hires, industry signals

Flexible data model

Create custom objects and associations without code—treat CRM as a relational database

Real-time data enrichment

Sync data from email, calendars, and third-party sources automatically

Call Intelligence

AI-powered call analysis with real-time insights and summaries

MCP integration

Connect to AI tools like Claude via community MCP servers for natural language CRM operations

Custom workflows

Build automated pipelines and triggers without engineering support

API-first architecture

Developer-friendly REST API for custom integrations and data flows

Fast setup

Get started in under a minute for basics; full implementation in 1-4 weeks

Use Cases

Sales & Revenue Teams

Managing deal pipelines with custom stages and automated progression
Lead qualification using AI-enriched contact profiles
Sales forecasting with real-time pipeline analytics
Territory planning using flexible custom objects

Customer Success

Tracking customer health scores with custom attributes
Automating renewal workflows and engagement triggers
Managing customer segments with dynamic lists
Syncing product usage data for expansion signals

Product-Led Growth

Connecting billing systems (Stripe) for revenue-qualified leads
Tracking user behavior alongside CRM interactions
Building custom PLG metrics without engineering
Automating outreach based on product signals

Operations & RevOps

Building custom reporting dashboards
Integrating data from multiple sources via API
Creating workflow automations across GTM functions
Maintaining data hygiene with enrichment rules

Considerations

Before You Adopt

Less mature for massive enterprises (1000+ users)—better suited for agile teams
Fewer legacy integrations than Salesforce—focused on modern tools (Slack, Notion, Stripe)
No built-in strategic alignment—executes CRM tasks without organizational context
MCP servers are community-maintained, not official Attio products
Advanced AI features may require higher pricing tiers
Learning curve for teams migrating from structured CRMs like HubSpot

Attio