Cube vs Vena (2026)

Cube connects to hundreds of source systems, with guides for NetSuite, Salesforce, Workday, Sage Intacct, Snowflake, Databricks, ADP Workforce Now, QuickBooks, HubSpot, Rillet, Dynamics 365 Business Central and Campfire, and syncs them on a schedule or on demand. Agents can start a fresh import from an existing connection before they answer, and they put their work into Cube scenarios, Boards, Tables and decks. None of them books an entry, updates a deal or changes an employee record back in the ERP, CRM or HR system.

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Source data comes into Vena's central database through prebuilt native integrations, Microsoft Fabric connections and open import APIs, with export APIs for an extra fee, and Vena sits inside Microsoft Excel, Teams, Power BI, PowerPoint and Dynamics 365 Business Central. The agents work on that data in Vena and in the workbook.

The Planning Agent writes driver based budgets into Excel templates, the Reporting Agent builds reports and charts with drill down, and changes made through Vena MCP in Excel can be written back to forecasts and scenarios. None of them changes a record in an ERP, CRM or HR system.

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Charlie, the super agent, breaks a question into tasks, routes each piece to one of four agent teams (Data Managers, Analysts, Planners and Business Partners), lets them pull, reconcile, model and draft, then checks the combined answer against the source data before returning it. One request can run from a data refresh through variance analysis to a drafted board deck. Cube Workflows add task lists with owners, assignees, statuses and due dates for processes such as the month end close.

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A visual workflow builder maps a whole process, from budget input through review, approval, upload and distribution, automates report sends and task reminders and notifies each person when their step comes up, and the same builder runs compensation planning and financial close management. Inside a single request the Analytics Agent breaks a variance, trend, comparison or ranking question into several steps, shows each one and asks when context is missing, and the Planning Agent turns one plain language request into a structured, driver based budget aligned to the CubeFLEX model.

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People reach Charlie in the Cube Workspace, in the Excel and Google Sheets add ins, in Slack and Teams, and from any MCP assistant such as Claude or ChatGPT. Anomaly Detection watches the numbers and flags lines that look off before anyone asks. Source systems sync on a schedule, so fresh actuals land in the model and the plans update around them without someone starting the work.

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People reach Vena AI in Excel, in the web app and in Microsoft Teams, where it can sit in a meeting as a private chat, and anyone in the business with a Vena AI license can ask the Reporting Agent for a report. Recurring work runs through skills and scheduled automations in the customer's own AI tools connected by Vena MCP, which can send proactive alerts and repeat an analysis on Vena data. Vena's own agents start when someone asks, and none of them wakes on a new close, a data load or a threshold.

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Charlie answers from the customer's own Cube. It decides which slices of actuals, budgets, forecasts and scenarios it needs and fetches them through the governed layer, with the company's formulas, account and entity hierarchies and currency conversions already applied, so revenue means what the company means by revenue. It can drill from a summary figure to transaction lines in the connected source systems, and every number opens back to the records behind it.

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Vena AI reads the live CubeFLEX model the team already maintains, with no extra setup, and inherits its data, application and per user permissions.

Vena Omega, the context engine underneath, adds each company's operating model, fiscal calendar, chart of accounts, entity structure, cost centers, historical performance, KPIs and terminology, industry considerations and seasonality, and the stage and dependencies of the planning and close cycle.

Answers drill down to the data behind each number, and the calculations stay deterministic on the governed model while the language model reasons over them.

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Each conversation with Charlie and each Planner session is saved for the user who started it, and a History view reopens any of them to carry on where it left off. Context stays inside one conversation, so starting a new one for an unrelated question keeps the earlier context from carrying over. Admins can also write standing instructions for Charlie, such as always showing budget against actuals or how the fiscal calendar runs, which apply in every conversation for every user. Nothing an agent learns in one conversation reaches the next.

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The Analytics Agent, in open beta, builds context about each user's role, preferences and business from what people share with it. Admins save organization wide context, each user can add personal instructions and preferences that carry into later conversations, and Vena Omega tunes the depth, framing and format of an answer to the user's role and permissions. How long that context lasts, and how a user reviews or clears it, is left open.

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Agent writes land only in scenarios opened for AI write back or created by the AI, so the live budget stays untouched unless someone opens it, and each write carries the user's name and an AI flag. Writing through MCP needs its own permission, which only Finance or Admin users can hold, new workflows and tasks arrive as drafts with no assignee, and a publish can be undone. Data Manager agents score each proposed mapping or bulk change by confidence, and the team approves it before anything lands.

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Budgets move through Vena workflows with review and approval steps and a notice to each approver in turn. The Analytics Agent shows how it reached an answer, flags missing context or uncertainty and asks before it fills a gap, and the user can correct a GL account, period or assumption and rerun. Every output is the customer's to review under Vena's AI terms, and agent output itself has no approval step of its own before it lands in a workbook.

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Cube holds SOC 2 Type II and SOC 1 reports, the SOC 2 examined by Dansa D'Arata Soucia, and handles data to HIPAA requirements. Sign in runs through SAML or OIDC single sign on with Okta, Duo, Google or Microsoft Entra, which an admin can enforce, plus app or text based multifactor authentication. Role based access and each user's Data Access Scope reach down to the cell, the agents inherit the asker's permissions, and separate permissions govern Charlie, the Planner, MCP read, MCP write and AI administration, so AI can be switched on or off for each use through the same roles.

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Deloitte performs Vena's annual SOC 1 and SOC 2 Type II audits, both available on request, and a SOC 3 report is public. Vena is a Cloud Security Alliance Trusted Cloud Provider and takes part in TRUSTe's privacy certification program.

Customers can turn on SAML 2.0 single sign on, multifactor authentication and IP restrictions, and role based access sets per user permissions on sensitive data, which the agents inherit.

Each customer gets its own database instance, data is encrypted at rest with AES 256 under keys held in AWS Key Management Service and in transit with TLS 1.2 or higher, and Vena staff reach production only through federated sign in with MFA and a VPN.

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Every agent query, answer and publish is recorded with the user, the permission scope applied and the sources used, and denied actions are recorded too. The audit trail shows each data change with who made it, the event type, the number of values changed and the before and after figures, and change history marks which changes came from AI. Because answers open to the transactions behind each figure, a reviewer can see exactly what an agent relied on.

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Audit trails record every document, spreadsheet, budget, report, template and cell level change with date, time and user, with version histories and rollback. Admins get a view of every question put to Vena AI and every response, and answers marked wrong can be audited. The Analytics Agent shows the steps and logic behind each answer so a user can inspect what it used, and visual workflow tracking shows where each step of a process stands.

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Cube runs as a hosted service on AWS, with all data and infrastructure in US based regions, and offers a data processing agreement for GDPR needs. A company that needs its financial data held in the EU or another country cannot get that, and there is no customer hosted edition.

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Vena Hubs run in AWS or Azure data centers in Canada, the United States or the EU, and each customer chooses its hub region to meet residency rules and keep transfers fast. Nightly backups go to Amazon S3 or Azure Blob Storage across several regions in the same geography, so data stays in that geography, and current data is always stored redundantly. Vena AI runs on Azure OpenAI Service, and Vena does not promise that its AI features are available in every region. There is no edition a customer can host itself.

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Four agent teams come with every plan. Data Managers handle mapping, bulk edits, connection setup and hierarchy upkeep, and Analysts bring slices, Smart Variance and Anomaly Detection. Planners carry the Planner Agent, Smart Forecaster and Formula Modeler, and Business Partners carry Visualization, Board Builder and Deck Builder. The Agent Exchange adds ready plays, such as a variance bridge to budget, a rolling forecast refresh, an investor update or a new entity mapping, which Charlie runs once the user fills in the bracketed inputs.

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Three agents are ready for different jobs. The Planning Agent drafts driver based budgets and forecasts in Excel from plain language, aligned to the CubeFLEX model. The Reporting Agent lets anyone in the business request ad hoc reports and charts with drill down, which teams edit together in Excel Live inside Teams.

The Analytics Agent, in open beta with general availability expected later in October 2026, works through variance, trend, comparison and ranking questions in steps. A Scenario Agent for modeling cost, pricing, M&A and timing decisions across entities is announced and not yet available.

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Charlie and the agent teams run on language models from providers available through Amazon Bedrock, chosen by Cube, with Anthropic named among Cube's subprocessors since March 2026, and Cube trains no models of its own for these features. AI settings hold a company's standing instructions and nothing else, so a company cannot pick the model behind its agents. Outside assistants such as Claude or ChatGPT can work on Cube data through the MCP server, but those are the customer's own tools reading Cube.

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Vena AI runs on OpenAI models through Microsoft Azure OpenAI Service, under Microsoft's code of conduct for that service, combined with the CubeFLEX model, and customer data is never used to train public models. A customer cannot move its agents to another provider or model. Claude Cowork, ChatGPT Work and other assistants can work with Vena data through Vena MCP, but those are the customer's own tools, not a choice of model for Vena's agents.

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The Cube MCP Server, generally available on every plan with usage limits, signs users in with OAuth and offers a full tool set, from get_financial_slice_of_data and get_drilldown_data to publish_data, duplicate_scenario, create_dashboard, create_planning_table, create_workflow and initiate_import, so a team can point any agent framework at the governed model and write plans, Boards, Tables, scenarios and workflows back under the user's permissions. The Cube REST API has a public OpenAPI reference covering agent chat and Planner sessions, AI settings and credits, canvases, workflow runs and connection syncs, authenticates through OAuth with a PKCE flow, and is sold as an add on.

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Open platform APIs move data into Vena, with import APIs included in every plan and export APIs for an extra fee. Vena MCP gives supported AI tools such as Claude Cowork and ChatGPT Work read access to ledger, transaction and operational data under Vena's permissions, and changes made through it in Excel can be written back to forecasts and scenarios. Vena's AI terms bar calling its AI features by any route other than the ones Vena provides, and the MCP endpoint and full tool list are not public.

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Before Charlie returns an answer it checks each figure against the source data, and every query, answer and AI write sits in the log for review afterward. The Planner, still in open beta, asks clarifying questions before it builds a scenario. Cube tested its own accuracy on its own books and does not warrant AI output, reminding users on every AI surface to check results. A finance team cannot run an agent against a set of known questions to see how it does before giving it to the wider team.

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The Complete plan adds a sandbox environment to test, refine and validate new features and data sets before end users see them. Users give feedback on responses as they arrive, wrong answers can be audited, and admins can write natural language rules for phrases the AI misreads, while the Analytics Agent lets a user fix an input and rerun an analysis. None of this scores agent answers against a test set, so a team judges agent quality by checking results itself.

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The agents work through Cube's governed data layer, its source connections and the spreadsheet, Slack, Teams and MCP surfaces. None of them opens another application and clicks through it for a user.

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The agents work inside Vena's model and the Excel, Teams and Power BI surfaces Vena connects to, and data from other systems arrives through integrations and APIs. None of them takes over another application's screen for a user.

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