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What is Backstory (formerly People.ai)?
Backstory (formerly People.ai) is an AI-powered revenue intelligence platform that automatically analyzes communications across emails, meetings, and calls to provide actionable insights about deal status and next steps. The platform answers questions revenue leaders ask every day: Is this deal real? Where's my risk? What changed in the forecast?
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Backstory (formerly People.ai) news
People.ai Rebrands to Backstory
People.ai officially changed its name to Backstory, signaling a strategic shift from data and analytics toward delivering actionable answers to revenue leaders' questions. CEO Jason Ambrose noted the rebrand reflects the company's evolution and the core capability of connecting activity data, relationship intelligence, and AI-driven insights.
Source: Backstory Newsroom ↗
Key features
Automatic Activity Capture
Collects data from emails, meetings, calls, and chat without requiring manual CRM updates
Deal Risk Identification
Identifies at-risk deals and pipeline slippage before forecast calls
Revenue Forecasting
Provides pipeline visibility and forecasting based on actual activity rather than CRM data alone
Stakeholder Mapping
Tracks engagement across multiple contacts within accounts
CRM Integration
Connects with Salesforce, Microsoft Dynamics, Oracle, and other platforms
AI Assistant Integration
Integrates with Claude, ChatGPT, Copilot, and Slack for seamless workflow integration
Revenue Reasoning Layer
Applies revenue-specific reasoning built on years of execution data and engagement patterns to reconstruct what is actually happening inside deals
Backstory (formerly People.ai) pricing
Backstory uses a hybrid, usage-based pricing model without traditional per-seat licensing. Customers pay for connected customer-facing reps and consumption (answers delivered), with unlimited viewers at no additional cost. Specific pricing tiers are not publicly listed; interested customers must request custom quotes.
Who is Backstory (formerly People.ai) best for?
- • Enterprise sales teams
- • Revenue operations leaders
- • Sales leaders seeking better pipeline visibility
- • Organizations struggling with forecast accuracy
- • Teams looking to reduce manual CRM data entry
