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How FunnelStory Works

FunnelStory is built around a modular three-layer architecture — Get, Set, Go — designed to take your scattered enterprise data and turn it into grounded, actionable intelligence for every team and every AI system in your organization.

Step 1: GET — The Intelligence Layer​

The Intelligence Layer is the foundation. It ingests your enterprise data and builds the Customer Intelligence Graph — a patent-pending graph that synthesizes four pillars (Usage, CRM, Conversations, and Business Intel) into a single source of truth. This graph maps every interaction from the first touchpoint, enabling Time-Travel Discovery: the ability to reason about historical patterns, not just current state.

The Intelligence Layer has two sub-components that work in sequence.

Context Layer

FunnelStory connects to your data sources and consolidates all enterprise data into the shared Customer Intelligence Graph:

  • Structured data — product usage, CRM records, tickets, billing and revenue data
  • Unstructured data — meetings, chats, documents, and notes
  • 3rd party data and intelligence — enrichment data, social signals, news, articles, and external intelligence feeds

The graph links accounts, users, products, and interactions into a single unified context that every downstream layer builds on.

Pre-computed Intelligence Layer

On top of that context, FunnelStory continuously runs intelligence computations and materializes the outputs. Pre-computing intelligence centrally means every team member and every AI agent works from the same shared reality — eliminating individually computed, divergent versions. Intelligence is generated once, not re-derived per query, which eliminates token inflation, reduces latency, and enables role-based access controls over which outputs each user or agent is permitted to see.

There are two types of pre-computed intelligence:

Out-of-the-box Intelligence

FunnelStory ships a standard set of intelligence models that activate as soon as your data is connected:

  • Predictive Scores — renewal likelihood, expansion signals, and churn risk for every account
  • Needle Movers — leading indicators of risk and opportunity that surface accounts needing immediate attention
  • Customer Journey — where each account sits in their lifecycle at any point in time
  • Historical Engagement Patterns — how an account has engaged with your product, support, and team over time
  • Temporal Analysis — what behavioral patterns look like in defined windows, such as the six months preceding churn
  • Topics and Sentiments — themes and tone extracted from support tickets, calls, and conversations
  • Revenue Forecast — ARR projections based on renewal signals and expansion likelihood
  • Cohort Analysis — performance and behavior comparisons across account groups

Custom Intelligence

The pre-computed intelligence layer is extensible. Teams can add externally computed scores, outputs from custom AI agents, or third-party models alongside the out-of-the-box set. Custom intelligence can be tailored to any team's workflows — from Customer Success QBR prep and churn modeling to Marketing's advocacy pipeline and Product's adoption funnel analysis — and surfaces through the same shared layer with the same RBAC guarantees.

Step 2: SET — The Agent & Automation Layer​

The Agent & Automation Layer is a control plane for configuring, managing, and running AI Agents through FunnelStory. It features a "LEGO block" approach, allowing teams to snap together modular workflows and components without writing code.

Agents are triggered by intelligence signals — a prediction change, a needle mover, a stage transition — and execute actions such as summarizing account activity, flagging contract risks, updating CRM records, or generating briefings. Workflows provide the orchestration layer for routing outputs to Slack, HubSpot, Salesforce, or any webhook.

Two capabilities define this layer:

  • Vibe Coding — create custom AI agents and automations by describing what you want in natural language. No engineering dependency.
  • Background Execution — vibe-coded agents continuously analyze data and trigger workflows even while your team is offline.

Step 3: GO — The UX & AX Layer​

This is where intelligence and action surface to humans and AI systems. FunnelStory supports three access surfaces that can be used independently or in combination.

UX — FunnelStory UI

FunnelStory's built-in interface gives frontline and leadership teams direct access to pre-computed intelligence through views like the Accounts dashboard, Renewal Management, Needle Movers, and custom dashboards. Teams can consume intelligence, take notes, manage workflows, and configure agents without leaving the platform.

UX — External Apps

FunnelStory's intelligence is also consumable from the tools teams already work in. Third-party apps like Slack, CRM platforms, and CSM tooling can surface FunnelStory data in-context — for example, account health alerts in Slack or renewal scores embedded in Salesforce. Developers can build custom applications on top of FunnelStory's APIs to create tailored experiences for specific workflows or personas.

AX — AI Experience

FunnelStory uses a Bring Your Own Copilot (BYOC) model, piping the Customer Intelligence Graph directly into AI interfaces via a secure Enterprise MCP Server. This eliminates tool fatigue — CSMs and other team members access all intelligence within the tools they already use:

  • Renari — FunnelStory's built-in AI assistant. Ask questions about any account, get briefings, run analyses, and take action without leaving the platform.
  • External AI Copilots — connect Claude Desktop, Cursor, ChatGPT Enterprise, or any MCP-compatible client to query accounts, predictions, and activity directly.

Across all three surfaces, three categories of work are supported:

  • Pre-computed intelligence — surfacing out-of-the-box and custom intelligence outputs to frontline and leadership teams, on demand
  • Skills — generating customized intelligence and executing actions tailored to a specific account, role, or workflow
  • Vibe coding — creating, updating, and testing agentic workflows directly through a conversational interface, without writing pipeline code