GTM Hub
What is Odie (formerly Totango)?
Odie (formerly Totango) is a Customer Knowledge Engine designed for post-sales and GTM teams. It captures company knowledge and team expertise, combines it with daily AI analysis of customer data (CRM, usage, emails, calls, meetings, feedback), and creates living customer narratives to predict churn, identify expansion signals, and power AI agents.
Odie (formerly Totango) news
Totango rebrands to Odie as Customer Knowledge Engine
After 15 years as a Customer Success platform leader, Totango announced a rebrand to Odie with a new platform, refined vision for post-sales, and customer-grade AI focused on customer knowledge and AI agents.
Source: Odie LinkedIn ↗Totango announces Unison growth-intelligence engine
Unison is Totango's AI-powered growth intelligence engine with standard and custom AI models for renewal propensity, built from customer data and business context. Custom models are isolated per customer and can achieve 99%+ accuracy.
Source: Totango LinkedIn ↗
Key features
Living Narrative Index
Self-updating customer knowledge graphs combining company, customer, and employee knowledge into a context engine for AI agents
AI Churn Prediction (Unison)
Standard models (1-2 days deployment) and custom models (4-16 weeks, tailored to business data with up to 99% accuracy)
MCP Server Access
Easy integration between Odie's living customer intelligence and enterprise LLMs or agents
Markers
Rule-based or AI-driven signals (e.g., budget pressure, competitive threat, renewal dates) applied automatically to accounts
Customer Operating System (optional)
Guided workspace with prebuilt post-sales agents, workflow automation, predictive renewal models, daily account briefings
AI-Guided Workspace
For individual contributors and managers to prioritize accounts, manage workflows, and view daily intelligence briefs
Expansion Intelligence
Data-driven signals to identify optimal upsell and cross-sell opportunities
Custom Dashboards
Executive dashboards combining data from multiple sources for strategic GTM and revenue decisions
Odie (formerly Totango) pricing
Odie is priced on two inputs: Knowledge Maintenance (number of knowledge graphs and refresh frequency) and Knowledge Usage (MCP access fee). No seat-based or token-based pricing. Minimum term is one year; most customers sign two years.
| Plan | Price | What's included |
|---|---|---|
| Customer Knowledge Engine | Starting at $500/month | Living Narrative Index, knowledge curation agents, Odie MCP server, all data source integrations. Priced by knowledge graph volume and MCP access. |
| Customer Operating System | Starting at $1,500/month | All Knowledge Engine features plus guided workspace, AI-guided interface, predictive renewal models, workflow automation, prebuilt agents, chat copilot, AI Success allocation pool |
Pros & cons
Pros
- + Data privacy by design: custom models are isolated per customer, not pooled across accounts
- + Token-efficient AI with significant performance benchmarking (statistically significant on 70+ production instances)
- + No hidden costs—predictable pricing based on known inputs (entities, refresh frequency)
- + Fast standard model deployment (1-2 days) for rapid time-to-value
- + Integrates with existing tools via MCP (uses any enterprise LLM or agent framework)
- + No seat-based pricing—accessible to entire team at same cost
- + Proven customer results: customers report 50% revenue growth, 20% churn reduction, 16% retention lift
Cons
- − Custom AI models require 4-16 weeks of white-glove service (significant time commitment)
- − No monthly payment option; minimum 1-year commitment required
- − Advanced AI churn prediction (Unison) is sold separately from base CSP functionality
- − Requires AI Success pool budget for on-demand work in Customer Operating System
Who is Odie (formerly Totango) best for?
- • Enterprise B2B SaaS companies protecting and growing revenue from existing customers
- • Customer Success teams managing 100+ accounts who need predictive churn and expansion signals
- • Organizations building custom AI agents (using MCP) that need customer context
- • Teams with complex customer data (CRM, usage, calls, feedback) needing unified intelligence
- • Revenue-oriented GTM orgs (post-sales, expansion, CS leadership) requiring forecastable metrics
Frequently asked questions
Does Odie analyze product usage data?
Yes, but it requires custom models. Work with Odie account team to explore usage data from data warehouses (e.g., Snowflake). Standard models focus on engagement (calls, emails, tickets, meetings).
How much historical data do I need?
Odie supports various data sources: CRM with activity (required), email, call transcripts, meeting records, support tickets. Standard models work quickly; custom models learn from all historical data to build more accurate churn models.
Is Totango the same as Odie?
Yes. Totango rebranded to Odie on September 10, 2026. Legacy Totango and Catalyst platforms still run under existing contracts with the same pricing and product.
How is Odie different from general AI like ChatGPT?
Odie is context-aware. It learns your company's hard-won customer knowledge from your team, combines it with your data, and keeps that context current. General-purpose AI lacks this customer-specific context needed for revenue-bearing decisions.
Can I build my own agents on Odie?
Yes. Odie exposes its Customer Knowledge Engine via MCP server, allowing you to build or use any agents/tools you already own.
