TrueGradient vs Anaplan: Agentic AI vs Structured Model Building
Modern planning is shifting from model-building interfaces to agentic AI interaction. Here’s how TrueGradient’s AI-driven workflow compares to Anaplan’s structured modeling environment.
Planning Interfaces Are Evolving
Planning platforms historically required users to build and maintain structured models manually.
Modern AI-native systems introduce agentic interfaces that allow users to query, simulate, and interpret intelligence conversationally.
The future of planning is less about building models — and more about interacting with intelligence.
Anaplan: Structured Model Construction
Anaplan centers around structured module configuration.
Teams define hierarchies, formulas, assumptions, and reporting structures.
This structured approach provides transparency and governance, particularly for enterprise-scale organizations.
However, interacting with the system often requires navigating predefined modules and dashboards.
TrueGradient: Agentic AI Interaction
TrueGradient integrates agentic AI capabilities directly into its planning environment.
Users can query demand behavior, simulate capital impact, and explore forecast drivers through natural-language interaction.
This reduces friction between question and insight.
Decision Velocity
In structured modeling environments, generating new insights may require adjusting modules or creating additional scenario layers.
Agentic AI systems allow leaders to explore multiple outcomes dynamically without reconfiguring models.
For fast-moving growth brands, this may accelerate decision-making.
Reducing Dependency on Technical Specialists
Enterprise modeling platforms often require trained administrators to modify complex structures.
AI-native agentic systems aim to reduce reliance on technical intermediaries by allowing business users to explore scenarios directly.
This democratization can increase adoption across functions.
Transparency and Control
Structured model-building offers explicit visibility into formulas and assumptions.
Agentic AI systems provide interpretability through explainable model outputs and factor contribution insights.
The difference lies in whether transparency is achieved through visible formulas or model explainability layers.
Planning as a Conversational Workflow
As organizations become more data-driven, leaders expect faster access to forward-looking intelligence.
Agentic AI workflows enable iterative questioning — for example, exploring downside capital exposure or SKU-level volatility patterns instantly.
Structured modeling platforms may require more deliberate configuration steps to achieve similar insights.
Interface Design Reflects Planning Philosophy
Anaplan emphasizes structured model building with governance-focused transparency.
TrueGradient emphasizes agentic AI interaction with adaptive intelligence embedded at the core.
The optimal choice depends on whether your organization prioritizes structural control or conversational agility.
Planning maturity increasingly depends on how easily intelligence can be accessed — not just how it is built.
Experience AI-native planning with conversational intelligence.
Request a demo