Apollo.io vs Attio

Go-to-market platform combining a B2B contact database with email sequencing, whose AI agents research accounts, build lists, write outreach, follow up and book meetings.

Announced Apollo tool in which a user describes a go-to-market system in plain language and an agent writes the code for it, with conversational editing, delivery as Apollo-hosted pages, a Salesforce embed or Slack, and scheduled or signal-triggered runs.

Chat assistant inside Apollo that takes a request in plain language and carries it out in the product: finds prospects that match the ideal customer profile, researches accounts and builds outreach sequences, asking before any step that spends credits.

Apollo's agent layer for go-to-market work: it learns the customer's products, ideal customer profile and playbooks, plans multi-step work from one prompt, draws on a shared library of sales skills and keeps agents supervised until the customer lets them act alone.

CRM for sales teams with built-in AI: Ask Attio analyses and creates from CRM data, workflows and custom agents run revenue processes, and sequences send personalised outreach at scale.

Attio's meeting recorder: it records and transcribes sales calls, summarizes them, flags buying signals and blockers, and logs the conversation to the CRM so follow-up can be triggered from it.

Chat assistant in Attio that answers questions across a team's CRM records, emails, calls and notes or researches the web, and then acts on the answer: updating and creating records and drafting the follow-up.

Attio agent that reads the open web to answer a question about each company or person in the CRM and writes a sourced answer, with its confidence and reasoning, back to the record, on one record, a whole column or a workflow trigger.

Attio's context layer underneath its agents: it captures and connects a company's emails, calls and connected tools into one store that Ask Attio, Custom Agents and workflows read from when they reason and act.