Anaplan CoModeler is an intelligent, role-based AI agent built directly into the Anaplan platform. Think of it as a collaborator sitting beside your model builder: describe a planning model in plain English (or hand it a CSV specification) and CoModeler drafts the underlying lists, modules, line items, formulas, and hierarchies for review, following Anaplan’s DISCO and Planual best practices. It reached general availability in Q1 2026, alongside Anaplan Analyst (for querying models in natural language) and Agent Studio (for managing the agents themselves).
Every change CoModeler proposes is reviewable, auditable, and only applied after a builder approves it. Configuration moves to the agent; design, review, and governance stay with the team.
Model building has been the quiet bottleneck nobody quantified. Anaplan’s own benchmark for CoModeler is minutes per model, not days or weeks (Anaplan, March 2026). Most Centres of Excellence run a handful of specialists, a scarcity Gartner underlined in an early-2026 survey where CFOs ranked building AI and digital talent in finance as one of their two toughest near-term priorities (Gartner, March 2026). Five outcomes explain why planning leaders are paying attention:
- Accelerated time-to-value. AI-guided model generation replaces manual, time-intensive configuration. Prompts or CSV specs become structured hierarchies, modules, and line items in minutes rather than weeks.
- Automated optimization. Inefficient formulas and redundant structures get flagged and improved against proven best practice, protecting scalability and performance at enterprise volume.
- Improved agility. Teams can prototype and stress-test scenarios (supply chain shocks, market shifts, restructures) on the fly and react to internal and external drivers in near real-time.
- Reduced key-person risk. Plain-language documentation for formulas and modules is generated automatically, which speeds up onboarding, eases audits, and de-risks builder handovers.
- Enterprise governance. CoModeler integrates directly into Anaplan’s existing security framework across Classic and Polaris engines. No customer data trains the AI, and every change needs explicit workspace administrator approval.
CoModeler collapses several jobs a builder used to do by hand into a governed, AI-assisted workflow. Five capabilities do most of the work:
- Conversational model building. Translates plain-language prompts and structured specifications into functional model components, automatically generating lists, modules, hierarchies, and calculations.
- Model extension. Modifies and expands existing applications or custom models by integrating new business logic, structures, and scenarios without hand-tracing every dependency.
- Performance optimization. Analyzes model structures and formulas to identify inefficiencies, then applies AI-guided best-practice improvements for scale, speed, and accuracy.
- Documentation and governance. Generates plain-language explanations of complex model logic, boosting transparency, accelerating user onboarding, and easing audit.
- No-code scenario prototyping. Lets planners spin up and test new decision-making scenarios without deep coding or scripting expertise.
CoModeler uses a well-defined four-step approach that keeps the model builder in charge throughout:
- Define. Explain your model goals in plain English or import a structured CSV specification. CoModeler drafts an initial structure for your review.
- Review. CoModeler produces a detailed specification with modules, lists, dependencies, and milestones, so you know exactly how your planning model will be built before a single change is made.
- Apply. Once approved, CoModeler creates or extends model components inside your existing workspace permissions and governance controls, following Anaplan best practices throughout.
- Validate and refine. Review generated structures, ask follow-up questions in natural language, and refine as business needs evolve, with auto-generated documentation supporting every step.
For a short walkthrough of that flow inside the Anaplan environment, see the official CoModeler demo video.
Polestar Analytics is a preferred global AI delivery partner for Anaplan. We help enterprises operationalize CoModeler across three sharp areas:
- Estate assessment. We audit your existing Anaplan model estate and CoE backlog to identify the highest-value CoModeler use cases: undocumented models, mission-critical builds queued for months, and areas of concentrated key-person risk.
- Governed proof-of-value pilots. We run controlled pilots on real bottlenecks (not curated demos), with a certified builder on review from day one, so wins are auditable and defensible in front of your CIO, CFO, and internal audit.
- Operating-model redesign. We rebuild your CoE around CoModeler: role definitions, ALM discipline, review cadences, and governance guardrails, so your team owns the agent post-launch instead of depending on external hands.
This work sits inside our enterprise planning practice and connects to our broader agentic AI engagements, so CoModeler is treated as one agent in a larger role-based system, not a standalone tool. For a technical view of where builder judgment still drives outcomes, see our CoModeler analysis. For teams extending pre-built solutions, the Anaplan applications guide is the fastest starting point.
CoModeler and Anaplan Analyst are two role-based AI agents released in the same March 2026 wave, but they serve different users. CoModeler is the model-builder’s agent: it designs, extends, optimizes, and documents planning models through natural-language conversation. Anaplan Analyst is a query-and-insight agent that lets business users interrogate those models in plain English, pulling forecasts and scenario answers without editing anything. Same agent suite, complementary roles: CoModeler works on the architecture, Analyst works on the outputs.
Yes, and this is one of its highest-value uses in mature Anaplan estates. CoModeler reads an existing model and explains its structure, dependencies, and formula logic in plain language, effectively generating documentation for legacy builds that never had any. Point it first at your most business-critical, least-documented model, where key-person risk is highest and a generated model map pays back immediately. Teams inheriting large multi-workspace estates from consulting handovers or M&A activity often use this before any new build.
They build to Planual and DISCO conventions when prompted, which puts the output closer to a certified builder’s first draft than a naive attempt. That said, structural correctness is not the same as performance. Review sparsity, calculation order, and module design before you apply, because a structurally valid model can still be slow at enterprise volume. Treat CoModeler’s output as a strong starting point that a certified builder still refines, especially on high-volume forecasting or supply-chain models.
It changes the mix more than the headcount. The scarce work shifts from hand-assembling modules toward requirement definition, model design, review, and governance. In most cases, the stronger business case is upskilling existing builders into design and review roles, then redirecting saved build hours to the backlog your COE never reaches. A blanket hire-fewer decision often costs more later than the salary savings, because governance debt and rework surface downstream. Model this against your real backlog, not a theoretical productivity gain.
It runs on development models inside your existing workspace permissions, slotting in before your normal ALM promotion path rather than replacing any part of it. Nothing CoModeler produces bypasses your revision tags, deployed-mode controls, or sign-off gates. The build-and-document stage compresses; test and release governance stays exactly where it was. Teams with mature ALM discipline can adopt CoModeler on new work without renegotiating their promotion process or auditor obligations.