Anaplan vs Board (2026)

Data reaches Anaplan through Anaplan Data Orchestrator, which connects, transforms and loads data from source systems into planning models, and through CloudWorks for cloud storage, a prebuilt Informatica connector, a command line utility for on premises jobs and transactional and bulk APIs. The agents work on that data inside Anaplan.

Analyst writes updates back to the live planning model within the user's permissions, CoModeler edits import data sources and creates list import actions, and the role based agents start Anaplan workflows. None of them posts a change into an ERP, CRM or HR system on its own.

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Data reaches Board's models through Data Readers, JDBC and an SAP connector, native links to Amazon S3, Azure and Google storage, REST API call steps inside Procedures, and a Cloud Connector that also writes back to on premises sources through a secure tunnel. The agents sit on top of that data rather than calling those systems. They query Datasets through the Board engine, recommend matches, mappings and corrections, and can pass an answer table to a Smart Import object, where nothing loads until a planner reviews and saves it.

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Anaplan Workflow breaks a planning process into tasks, approvals and handoffs with owners and deadlines, and ties them to data updates run by Data Orchestrator. Workflow Agent builds those flows from a typed or spoken description, a document or a whiteboard image, adjusts them as the process changes and flags bottlenecks with fixes such as adding a reviewer. The role based agents for finance, sales, supply chain and workforce share one calculation and data foundation, so each one works with the plans of the other functions in view.

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An Agent Orchestrator takes each request with the context of the Screen it came from, decides which agent fits and which steps the task needs, and can sequence work across agents so that one coherent answer comes back. The FP&A, Controller, Supply Chain and Merchandiser Agents sit behind it, and an Agent Manager supervises the network. No calculation runs inside an agent. Each data request goes through a Dataset to the Board engine, which applies the model's logic and security, and the agent then explains the result and proposes next steps.

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Workflow launches tasks by itself when a threshold is crossed, a condition is met or an upstream change lands in the model, and any task can run on a schedule. Data updates triggered by Data Orchestrator feed the same process. The role based agents watch performance continuously and send alerts when they spot a deviation or a risk, so the finance agent can surface a variance before anyone asks. People also reach the agents by typing or speaking a question inside their Anaplan applications, on desktop or mobile.

Sourceanaplan.com/platform/anaplan-workflowread 2026-10-13

A planner starts every agent session from the AI icon on a Screen the agent is linked to, by typing a question or choosing one of the suggested prompts a developer prepares, up to six groups of six. The agent takes the Screen's selections and filters as its starting context and answers inside Board. Nothing starts an agent without a person. Scheduled Procedures and email broadcasts run on their own, but no Procedure step calls an agent, and the agents do not reach people in email or a team chat.

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Agents answer from the customer's live planning models, modules and lists, and Anaplan's data ontology ties them to the business context of finance, supply chain, sales and workforce planning. Analyst queries across every model behind an application, works from a synced copy of the data that honors selective access, and reads extra context admins add in the notes of any line item.

The calculation engine computes the numbers, so each figure in an answer comes from the model, and Analyst shows the source data behind it. CoPlanner works from key data points in the application's models, refreshed on a regular cadence, so its answers can lag the latest change to a plan.

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Agents answer from the customer's own Board Data Models through Datasets switched on for AI, which fix the Entities, Cubes and selections an agent may query, and the Board engine runs every aggregation on that persisted multidimensional model. Data Attribute descriptions tell an agent what an ambiguous Entity or Cube means, and each agent can carry up to five uploaded text files of definitions, business rules, mappings and process guidance. An agent works on Screens built on a single Data Model, and Flex Grid layouts cannot yet feed an AI Dataset.

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CoModeler knows the current state of the model and remembers the last few prompts of the conversation, which survives a page refresh, an accidental close or signing in again, but conversations are not saved from one session to the next. Analyst carries follow up questions within a session and keeps no chat history once the session ends or the user moves to another page. What lasts beyond that is the planning model itself, the workflow history and the audit trail, all of which belong to the application.

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Within one session an agent keeps the thread of earlier prompts and builds on them. That context resets when the page refreshes, when the user moves to a Screen with another agent or none, or at log out, so nothing carries into the next session. Inputs, outputs and conversation logs stay in the customer's Board environment and session histories are kept there, though an administrator cannot export the full set in bulk. A user can export single answers as text or Excel and charts as images.

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CoModeler lays out a step by step build plan with annotations and dependencies and executes no change without the builder's explicit confirmation, though a builder who opens a prompt with Approve skips the plan and lets it build at once, and Anaplan steers CoModeler toward development environments.

Analyst writes back to a live plan only within the permissions the user already holds, and Anaplan Workflow routes submissions to assigned approvers with deadlines and notifications. Agent Studio keeps every agent inside the platform's existing roles, so an agent cannot reach data or actions its user could not.

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Agents recommend and explain, and the decision stays with the user. Policy driven guardrails set which actions each agent may take, which workflows it may work in and when a person must approve, and an agent reaches only the data, models and actions its user may. An answer table sent to a Smart Import object loads into the plan only after a planner reviews and saves it, and the Controller Agent's proposed corrections and account mappings come to a person for review.

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Anaplan holds SOC 1 Type 2 and SOC 2 Type 2 reports and ISO/IEC 27001, 27017, 27018, 27701 and, since September 2026, 42001 certificates, and its trust center adds CSA STAR Level 1, Cyber Essentials, ENS, TX-RAMP and TRUSTe.

Sign in runs through SAML 2.0 single sign on, with OAuth for APIs and integrations, role based access control, central identity management and IP allow lists, and only users with the AI Admin role can open Agent Studio. Data is encrypted at rest and in transit, a bring your own key add on puts the key in the customer's hands, and customer data, model structures and metadata never train a foundation model. Every agent and every AI Gateway request runs under the user's existing Anaplan permissions.

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Agents inherit Board's four layer security model, so roles, feature rights, folder security and data security on Entities and Cubes limit what an agent can reach exactly as they limit its user. Sign in runs on Board credentials with a custom password policy or through a SAML2 or OIDC identity provider, with SCIM provisioning and OAuth clients for API access.

Data is encrypted at rest with AES 256 and in transit with TLS 1.2 or higher, and customers can bring their own key. Board Cloud holds ISO/IEC 27001, 27017 and 27018 certificates, SOC 1 and SOC 2 Type II reports on request and a public SOC 3 report, and Board sits on the CSA STAR registry at Level 1.

Sourcehelp.board.com/docs/regulatory-compliance-certificationsread 2026-10-12

Workflow keeps timestamped audit trails and flow chart reports of tasks, approvals and progress, and the platform sends audit events to a customer's SIEM for alerting. Every change CoModeler makes lands in model history under the user who directed it, marked AI assisted, and Analyst and CoPlanner show the source data, model and timestamp behind each answer. AI Gateway records every tool call an outside assistant makes, with a timestamp and usage details, and throttles heavy use, and Agent Studio shows AI credits, interactions and usage per user.

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Every agent answer carries an Answer tab and, where relevant, a Chart tab, a Steps tab showing the steps and actions the agent took to build it and a Data Source tab showing the data behind it. Conversation logs and session histories stay in the customer's environment. Administrators track API Credit use against the monthly entitlement in the Subscription Hub, and its audit logs of user, connection and system events can be filtered, exported or pulled through an Audit Log API into a SIEM.

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Anaplan runs as its own cloud service, with in country data centers that keep customer data local for residency rules, among them AWS hosted locations in Singapore and the UAE and data centers in Indonesia, India and Australia. The Singapore center keeps data inside Singapore for public sector and financial services clients. The platform is also sold through AWS Marketplace. There is no customer hosted or on premises edition.

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Board Cloud runs on Microsoft Azure in a dedicated tenant for each customer, segregated from other tenants, with one or more production instances and optional sandboxes.

The customer picks a supported Azure region, from Ireland, the Netherlands, Frankfurt, Paris, Milan, Zürich, Oslo and London to Virginia, Iowa, Illinois, Texas, California, Toronto, São Paulo, Pune, Hong Kong, Tokyo, Singapore, Canberra, New South Wales, Victoria, Dubai and Johannesburg, and Board's Cloud Team can validate one outside that set. Daily backups serve disaster recovery and restore points replicate across regions.

Azure's abuse monitoring can keep samples of agent prompts and answers for review by Microsoft staff in the European Economic Area, and the agents need the Board 15 cloud, although Board itself also installs on premises.

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Prebuilt role based agents cover financial planning and consolidation, revenue performance management, supply chain planning and workforce planning, each embedded in the matching Anaplan application.

Agent Studio switches on ready Analyst configurations, Finance Analyst, Supply Chain Analyst, Sales Analyst and Workforce Analyst, for an application, and CoModeler and Workflow Agent arrive as ready agents for building models and processes.

Packaged applications such as Integrated Financial Planning, Demand Planning, Territory and Quota Planning and Operational Workforce Planning give each agent a ready model to work in.

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Four ready made agents ship for distinct jobs, and a developer picks one by name and version when configuring it in a Data Model. The FP&A Agent covers variance and root cause analysis, statement alignment, external drivers and narrative commentary.

The Controller Agent brings a validation rule assistant, intercompany reconciliation that matches balances with learned patterns, data collection insights, group account configuration, cash flow mapping and local account mapping. The Supply Chain and Merchandiser Agents, from release 15.1, analyze, explain and simulate options before a change or a buy. The Architect Agent is in preview.

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Anaplan pairs a language model's reasoning with its own deterministic calculation engine, so the arithmetic in an answer is computed by Anaplan, not by the model, which also keeps token use down. A customer has no say in which model runs the agents, and the provider is not named. The Claude, Gemini and Copilot connections through AI Gateway are outside assistants reading Anaplan data, not a choice of model for Anaplan's own agents.

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Board Agents run on OpenAI language models served through Microsoft Azure, and a customer cannot move them to another provider or its own model. What a customer does control is the agent version, chosen from recommended, supported or deprecated releases and upgraded only when the customer decides. Bring your own model in Board means predictive forecasting models, brought in through Azure ML Studio, Databricks, R, Snowflake or REST APIs, not the model behind the agents.

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Transactional and bulk APIs extend the platform for integration work, with OAuth that a customer sets to its own authentication and access policies. AI Gateway adds a supported MCP interface with permissions, rate limits and audit, through which outside assistants and agents query planning data. Access through the gateway starts read only, so an outside agent can look up a forecast but cannot change a model, a formula or a plan through it.

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Outside systems call Board through its Public APIs, REST endpoints that return API Query results as JSON, browse Capsules, Presentations, Slides and Screen objects, search the platform, list a Data Model's Entities, members and Cubes, and start a Data Model Procedure with a POST. Access runs through OAuth clients an administrator creates in the Subscription Hub, with scopes and rotating secrets, beside SCIM APIs for users and groups and an API for audit logs. The agents themselves have no API, and outside assistants cannot reach Board through an MCP server.

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CoModeler finds error prone formulas, redundant structures and slow spots in a customer's planning model, then documents each formula in plain language, and Workflow Agent studies how long tasks take to suggest a faster flow. Both of those check the customer's own model and process. A team has no way to test how an agent answers or acts before rolling it out to planners.

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Each answer shows its steps and source data so a user can check it, and Board asks users to validate every answer. Agent versions stay pinned until a developer upgrades, so a new release changes nothing on its own. No test set or measured evaluation run checks how an agent answers before a team relies on it. The Architect Agent, in preview, assesses a planning model's dependencies before a change, which checks the model rather than the agents.

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Everything the agents do happens inside Anaplan, through its models, workflows and data connections. Data from other systems arrives through Data Orchestrator, CloudWorks and the APIs, and none of the agents clicks through another application on a user's behalf.

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Board Agents query Datasets that the Board engine computes, and an answer table can go to a Smart Import object for a planner to review and save. No agent opens or drives another application's screen, a browser or a desktop session for a user.

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