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Comparison

Beye vs Claude Code or Codex + Power BI: Who Keeps It Running?

Count the owners, the weeks to live data, and the wait for the next question.

A coding agent such as Claude Code or Codex can write code, change Power BI models and open pull requests. That is a real way to build. The harder question is who operates everything around it once it ships: gateways, refresh schedules, the agent’s access, a place for Python to run, code review and the history business users rely on. Beye is a boutique enterprise agentic stack that carries much of that surrounding work in one product, Its conversational analytics is where people dig in: ask the follow-up in plain language, see the query and steps behind the answer, and take it further in Python when SQL is not enough. Two clocks matter as much as headcount: how long until a report runs on live data, and how long someone waits for an answer when they need to dig in.

This compares an approach, not a product: a general-purpose coding agent (Claude Code or OpenAI Codex) building on Power BI, with your team operating the result. It is not a review of either agent or of Power BI as a reporting tool. Microsoft Fabric adds pipelines, notebooks and Fabric IQ that can cover more of this stack; each adds its own setup and ownership. Roles below are jobs, not headcount: one person can hold several.

Written by Beye, which has a stake in the outcome. Last reviewed .

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001 / Fit

Which approach fits the work?

Consider Beye when

Trade-off. Connections and business context still need setup. Connector coverage is not exhaustive, custom legacy sources can take longer, and automated agents are coming soon. Sources: Beye Fabric, tools and collective history

Consider coding agents + Power BI when

Trade-off. Each layer is capable, and each has its own owner. Gateways, refresh failures, the agent’s access, Python hosting and code review stay with your team. Sources: Power BI implementation planning: data gateways,Power BI scheduled refresh: limits and failures,Claude Code security: permissions, sandboxing and user responsibility

002 / Who runs it

Eight jobs that need an owner after launch

Write a name next to each job for your organization. A coding agent can help with most of them, but it does not own them: Anthropic and OpenAI both tell you to review the agent’s work. The Beye column shows which jobs move into the product and which stay with your team either way.

  1. Answering the follow-up question

    Beye

    The person asking, in conversational analytics

    Ask the follow-up in plain language against connected data and see the query, steps and result behind the answer. When SQL is not enough, the same work continues in sandboxed Python. Data that is not connected yet needs a Fabric connection first, and someone still checks the result.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    BI developer, again

    Copilot answers from the semantic model when a question relates to its data, and otherwise from general knowledge; Microsoft says an unprepared model can return generic or inaccurate results. A question that needs data or logic the model lacks goes back to whoever extends it, then through review, publishing and the next refresh.

    Sources: Copilot for Power BI: requirements, data preparation and answers,Power BI scheduled refresh: limits and failures

  2. Source connections and gateways

    Beye

    Beye, with your source access

    Fabric connects your systems and keeps pulling changes. Your team grants source access and agrees sources and cadence; coverage and cadence depend on the source, and custom legacy systems can need extra work.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    Gateway administrator

    On-premises sources reach Power BI through gateways installed on machines you maintain. Microsoft recommends clusters for business-critical work, testing monthly gateway updates and keeping up with Windows maintenance; it supports only the last six gateway releases.

    Sources: Power BI implementation planning: data gateways

  3. Refresh and data freshness

    Beye

    Beye

    Fabric keeps source data current as an ongoing part of the product, rather than a report refresh someone schedules. Update cadence depends on the source and configuration.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    Model owner or BI administrator

    Scheduled refresh runs up to 8 times a day on Pro and up to 48 on Premium or Fabric capacity. Power BI turns a schedule off after four consecutive failures or expired credentials, and pauses it after two months without report views; someone has to notice and re-enable it.

    Sources: Power BI scheduled refresh: limits and failures

  4. Models, measures and reports

    Beye

    Your analysts, in the workspace

    Ask questions of connected data in plain language and inspect the query, steps and answer. Dashboards are one outcome. Your business definitions still need someone who knows them.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    BI developer

    Coding agents can edit Power BI Project files and, through Microsoft’s Authoring MCP server, create and change tables, measures and relationships. Microsoft notes that edits outside Power BI Desktop can cause errors, and some project files are not supported for external editing.

    Sources: Power BI Desktop projects (PBIP): source control and external editing,Power BI MCP servers: authoring, Fabric IQ and security considerations

  5. Running the agent and reviewing its work

    Beye

    Your team reviews; Beye hosts the workspace

    The assistant writes queries and Python inside the Beye workspace, where the code and its changes stay inspectable. Someone who understands the business logic should still check the result.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    Developer who runs the agent

    Claude Code and Codex work in a repository, editing files and running commands. Anthropic says the user is responsible for reviewing proposed code and commands; OpenAI advises treating Codex suggestions like any other pull request, with targeted verification and diff review.

    Sources: Claude Code security: permissions, sandboxing and user responsibility,Codex agent approvals and security

  6. Somewhere for Python to run

    Beye

    Beye

    Complete Python programs run in Beye’s sandboxes against connected data, without a separate runtime for your team to host.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    Platform or DevOps engineer

    Inside Power BI, Python visuals need Python installed for authoring, plot up to 150,000 rows and time out after five minutes. Heavier Python runs somewhere you choose and operate, such as a developer machine, a CI job or, on Fabric capacity, a notebook job.

    Sources: Python visuals in Power BI: limitations and licensing,Power BI scheduled refresh: limits and failures,Claude Code overview: editing, commands, Git, CI and scheduled tasks

  7. Access, security and data handling

    Beye

    Beye, plus your vendor review

    One platform to review: sandboxed execution, inspectable work and SOC 2 Type II audited controls, detailed in the Trust Center. Your team still runs its own vendor review.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    Security and platform administrators

    Microsoft recommends a security review covering the Power BI MCP server, the agent client and the model provider, least-privilege roles, and governance of data sent to the model provider. Claude Code adds permission modes, sandboxing and managed settings for administrators to configure.

    Sources: Power BI MCP servers: authoring, Fabric IQ and security considerations,Claude Code security: permissions, sandboxing and user responsibility

  8. Shared tools and their history

    Beye

    Built into the workspace

    Turn a calculation into a tool with inputs. Colleagues change the inputs and run it again; revisions, code changes, inputs and previous runs stay inspectable.

    Sources: Beye Fabric, tools and collective history

    Claude Code or Codex + Power BI

    Whoever built the tool

    Code and Power BI Project files can live in Git with version history. Where a business user runs a custom tool, which inputs they can change, and where each run’s inputs and results are kept are things your team designs and maintains.

    Sources: Power BI Desktop projects (PBIP): source control and external editing,Claude Code overview: editing, commands, Git, CI and scheduled tasks

003 / Matrix

Data fabric, analytics and tools at a glance

Compare the workflow, then test your actual setup. Named products illustrate capabilities; they do not represent every product in the category.

Every cell has two labels. Capability says what exists. Evidence says where the claim comes from. The same standards apply to both vendors, and each side is the publisher's own statement, not independent testing.

Capability

  • Available In the product today, as stated by that product's publisher.
  • Depends on setup Exists, but depends on the source, configuration or scope.
  • Coming soon Announced as forthcoming. Not available today.
  • Not verified The public sources we reviewed do not settle it. This is not a "No".

Evidence

  • Beye reported Beye's own statement about its product. Not independent testing.
  • Vendor documented The vendor's public material about its own product. Beye has not tested it.
  • Sources inconclusive No public source we reviewed settles it.
Beye and Claude Code or Codex + Power BI, compared by approach. Same rows, same order.
DimensionBeyeClaude Code or Codex + Power BI
Conversational analytics: digging in
Asking in plain language Capability:Available Evidence:Beye reported

Conversational analytics: ask about connected business data in plain language, and Beye shows the query, steps and result behind its answer.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Power BI Q&A is free for all users today, but Microsoft says it is going away in February 2027 and recommends Copilot. Copilot needs paid Fabric (F2 or higher) or Premium (P1 or higher) capacity and an admin setting, and Microsoft advises preparing the model first. Fabric IQ serves custom agents.

Sources: Power BI Q&A: natural-language questions and retirement notice,Copilot for Power BI: requirements, data preparation and answers,Power BI MCP servers: authoring, Fabric IQ and security considerations
Digging into a follow-up Capability:Available Evidence:Beye reported

Keep asking in the same conversation, drilling into the exception without a model change or a ticket. Data that is not connected yet needs a Fabric connection first.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Copilot answers from the semantic model, or from general knowledge when a question falls outside it. A question that needs new data or logic goes back to the model owner, then review, publishing and refresh.

Sources: Copilot for Power BI: requirements, data preparation and answers,Power BI scheduled refresh: limits and failures
From an answer to deeper work Capability:Available Evidence:Beye reported

When SQL is not enough, the analysis continues in sandboxed Python, and a useful calculation can become a reusable tool.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Copilot helps report authors write DAX and build report pages. Python or a new calculation outside the model goes to a developer and the coding agent.

Sources: Copilot for Power BI: requirements, data preparation and answers,Claude Code overview: editing, commands, Git, CI and scheduled tasks
Time to data and freshness
Time to a first report on live data Capability:Depends on setup Evidence:Beye reported

Beye says it gets your data AI-ready in weeks through Fabric. Timing depends on your sources and scope, and custom legacy systems can take longer.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Microsoft documents the steps: install and configure a gateway, add data source connections, publish a model and configure scheduled refresh. The sources we reviewed give no typical timeline; it depends on your sources, team and existing Power BI setup.

Sources: On-premises data gateways in Power BI: setup steps,Power BI scheduled refresh: limits and failures
Connected, current source data Capability:Depends on setup Evidence:Beye reported

Fabric brings source data together and keeps pulling changes. Source coverage and update cadence depend on the connection and configuration.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Power BI refreshes from cloud and on-premises sources; on-premises sources use a gateway you install and maintain. Scheduled refresh runs up to 8 times a day on Pro and 48 on Premium or Fabric capacity.

Sources: Power BI implementation planning: data gateways,Power BI scheduled refresh: limits and failures
Building and execution
AI-assisted building Capability:Available Evidence:Beye reported

Describe the work in plain language; the assistant writes queries and Python in the workspace, and you inspect the result.

Sources: Beye Fabric, tools and collective history		Capability:Available Evidence:Vendor documented

Claude Code edits files, runs commands and opens pull requests. Microsoft’s Authoring MCP server lets agents create and change semantic models; the local server is generally available and the hosted endpoint is in preview.

Sources: Claude Code overview: editing, commands, Git, CI and scheduled tasks,Power BI MCP servers: authoring, Fabric IQ and security considerations
Python execution Capability:Available Evidence:Beye reported

Run complete Python programs in sandboxes against connected data.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Python visuals in Power BI use up to 150,000 rows and time out after five minutes. Coding agents run Python wherever you host them, locally or in their sandboxes.

Sources: Python visuals in Power BI: limitations and licensing,Claude Code security: permissions, sandboxing and user responsibility,Codex agent approvals and security
Reusable tools with inputs Capability:Available Evidence:Beye reported

Turn a calculation into a tool with inputs, then change the inputs and run it again.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

A coding agent can build a script or application with inputs. Hosting it for business users, access and support are decisions your team designs and maintains.

Sources: Claude Code overview: editing, commands, Git, CI and scheduled tasks
Traceable work
Attributed revisions Capability:Available Evidence:Beye reported

Inspect revisions and code changes to tools in the workspace.

Sources: Beye Fabric, tools and collective history		Capability:Depends on setup Evidence:Vendor documented

Power BI Project files and agent-written code can live in Git with version history; Claude Code writes commits and pull requests. History depends on your repository and review setup.

Sources: Power BI Desktop projects (PBIP): source control and external editing,Claude Code overview: editing, commands, Git, CI and scheduled tasks
Saved runs with inputs and results Capability:Available Evidence:Beye reported

Revisit the inputs, revision and results of previous tool runs.

Sources: Beye Fabric, tools and collective history		Capability:Not verified Evidence:Sources inconclusive

The sources we reviewed do not describe a saved record of each custom tool run’s inputs and results. Decide where that history would live and who maintains it.

Automation and controls
Scheduled and event-driven automation Capability:Coming soon Evidence:Beye reported

Event-driven, scheduled and manually triggered agents are coming soon on the same foundation. They are not available today.

Sources: Beye Fabric, tools and collective history		Capability:Available Evidence:Vendor documented

Claude Code documents cloud scheduled tasks and CI runs through GitHub Actions or GitLab. Power BI schedules model refreshes.

Sources: Claude Code overview: editing, commands, Git, CI and scheduled tasks,Power BI scheduled refresh: limits and failures
Execution controls Capability:Available Evidence:Beye reported

Python runs in sandboxes, work stays inspectable, and controls are audited under SOC 2 Type II.

Sources: Beye Fabric, tools and collective history		Capability:Available Evidence:Vendor documented

Claude Code offers permission modes and sandboxing. Codex uses an OS-enforced local sandbox or isolated cloud containers, with an approval policy for when it must ask first.

Sources: Claude Code security: permissions, sandboxing and user responsibility,Codex agent approvals and security

Conversational analytics: digging in

Asking in plain language

Beye

Capability:Available Evidence:Beye reported

Conversational analytics: ask about connected business data in plain language, and Beye shows the query, steps and result behind its answer.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Power BI Q&A is free for all users today, but Microsoft says it is going away in February 2027 and recommends Copilot. Copilot needs paid Fabric (F2 or higher) or Premium (P1 or higher) capacity and an admin setting, and Microsoft advises preparing the model first. Fabric IQ serves custom agents.

Sources: Power BI Q&A: natural-language questions and retirement notice,Copilot for Power BI: requirements, data preparation and answers,Power BI MCP servers: authoring, Fabric IQ and security considerations

Digging into a follow-up

Beye

Capability:Available Evidence:Beye reported

Keep asking in the same conversation, drilling into the exception without a model change or a ticket. Data that is not connected yet needs a Fabric connection first.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Copilot answers from the semantic model, or from general knowledge when a question falls outside it. A question that needs new data or logic goes back to the model owner, then review, publishing and refresh.

Sources: Copilot for Power BI: requirements, data preparation and answers,Power BI scheduled refresh: limits and failures

From an answer to deeper work

Beye

Capability:Available Evidence:Beye reported

When SQL is not enough, the analysis continues in sandboxed Python, and a useful calculation can become a reusable tool.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Copilot helps report authors write DAX and build report pages. Python or a new calculation outside the model goes to a developer and the coding agent.

Sources: Copilot for Power BI: requirements, data preparation and answers,Claude Code overview: editing, commands, Git, CI and scheduled tasks

Time to data and freshness

Time to a first report on live data

Beye

Capability:Depends on setup Evidence:Beye reported

Beye says it gets your data AI-ready in weeks through Fabric. Timing depends on your sources and scope, and custom legacy systems can take longer.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Microsoft documents the steps: install and configure a gateway, add data source connections, publish a model and configure scheduled refresh. The sources we reviewed give no typical timeline; it depends on your sources, team and existing Power BI setup.

Sources: On-premises data gateways in Power BI: setup steps,Power BI scheduled refresh: limits and failures

Connected, current source data

Beye

Capability:Depends on setup Evidence:Beye reported

Fabric brings source data together and keeps pulling changes. Source coverage and update cadence depend on the connection and configuration.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Power BI refreshes from cloud and on-premises sources; on-premises sources use a gateway you install and maintain. Scheduled refresh runs up to 8 times a day on Pro and 48 on Premium or Fabric capacity.

Sources: Power BI implementation planning: data gateways,Power BI scheduled refresh: limits and failures

Building and execution

AI-assisted building

Beye

Capability:Available Evidence:Beye reported

Describe the work in plain language; the assistant writes queries and Python in the workspace, and you inspect the result.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Available Evidence:Vendor documented

Claude Code edits files, runs commands and opens pull requests. Microsoft’s Authoring MCP server lets agents create and change semantic models; the local server is generally available and the hosted endpoint is in preview.

Sources: Claude Code overview: editing, commands, Git, CI and scheduled tasks,Power BI MCP servers: authoring, Fabric IQ and security considerations

Python execution

Beye

Capability:Available Evidence:Beye reported

Run complete Python programs in sandboxes against connected data.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Python visuals in Power BI use up to 150,000 rows and time out after five minutes. Coding agents run Python wherever you host them, locally or in their sandboxes.

Sources: Python visuals in Power BI: limitations and licensing,Claude Code security: permissions, sandboxing and user responsibility,Codex agent approvals and security

Reusable tools with inputs

Beye

Capability:Available Evidence:Beye reported

Turn a calculation into a tool with inputs, then change the inputs and run it again.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

A coding agent can build a script or application with inputs. Hosting it for business users, access and support are decisions your team designs and maintains.

Sources: Claude Code overview: editing, commands, Git, CI and scheduled tasks

Traceable work

Attributed revisions

Beye

Capability:Available Evidence:Beye reported

Inspect revisions and code changes to tools in the workspace.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Depends on setup Evidence:Vendor documented

Power BI Project files and agent-written code can live in Git with version history; Claude Code writes commits and pull requests. History depends on your repository and review setup.

Sources: Power BI Desktop projects (PBIP): source control and external editing,Claude Code overview: editing, commands, Git, CI and scheduled tasks

Saved runs with inputs and results

Beye

Capability:Available Evidence:Beye reported

Revisit the inputs, revision and results of previous tool runs.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Not verified Evidence:Sources inconclusive

The sources we reviewed do not describe a saved record of each custom tool run’s inputs and results. Decide where that history would live and who maintains it.

Automation and controls

Scheduled and event-driven automation

Beye

Capability:Coming soon Evidence:Beye reported

Event-driven, scheduled and manually triggered agents are coming soon on the same foundation. They are not available today.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Available Evidence:Vendor documented

Claude Code documents cloud scheduled tasks and CI runs through GitHub Actions or GitLab. Power BI schedules model refreshes.

Sources: Claude Code overview: editing, commands, Git, CI and scheduled tasks,Power BI scheduled refresh: limits and failures

Execution controls

Beye

Capability:Available Evidence:Beye reported

Python runs in sandboxes, work stays inspectable, and controls are audited under SOC 2 Type II.

Sources: Beye Fabric, tools and collective history

Claude Code or Codex + Power BI

Capability:Available Evidence:Vendor documented

Claude Code offers permission modes and sandboxing. Codex uses an OS-enforced local sandbox or isolated cloud containers, with an approval policy for when it must ask first.

Sources: Claude Code security: permissions, sandboxing and user responsibility,Codex agent approvals and security

004 / Trade-offs

Strengths and trade-offs

Beye

Strengths

Limitations

Claude Code or Codex + Power BI

Strengths

Limitations

005 / Bottom line

Bottom line

Choose Beye if

you want current data, analysis, Python and reusable tools with history, without staffing the operations around a coding agent and a BI platform. Automated agents are coming soon. Sources: Beye Fabric, tools and collective history

Consider Claude Code or Codex + Power BI if

you already have a BI platform team and engineers who want to own an agent-built stack, or you need scheduled automation today. Sources: Power BI implementation planning: data gateways,Claude Code overview: editing, commands, Git, CI and scheduled tasks

Questions to test with your team

  1. How many weeks until the first report runs on live data from every source in scope, and who does each step?
  2. When a business user asks a follow-up the report cannot answer, who picks it up, and how long until they have an answer?
  3. What replaces Q&A for your users after February 2027, and does your capacity support Copilot?
  4. Who installs, patches and monitors the gateway, and who covers for them on holiday?
  5. When Power BI turns off a refresh schedule after repeated failures, who is notified and who fixes it?
  6. Who reviews each change a coding agent makes to models, measures and code, and how many hours a week does that take?
  7. Where does Python run for business users, and who operates that runtime?
  8. Has security reviewed the MCP server, the agent client and the model provider, and what data leaves your tenant?
  9. If the person who built the tool leaves, can someone else rerun it, change it and explain a past result?
  10. For Beye: which sources and update cadence are agreed, who is told when a connection fails, and what support is included?

006 / Sources

Sources and method

Beye wrote this page and reviewed each source on the date shown. “Not verified” means the public sources we read do not settle a point. It is not a “No”. Labels are defined in the legend above the comparison table. The cited examples illustrate this category; Beye has not independently tested them or surveyed every product or configuration.

Documented example: learn.microsoft.com. Spot something out of date or unfair? Tell us and we will check it.

007 / Your next step

Compare on your data.Bring one real workflow.

Pick a question, calculation or spreadsheet process your team depends on. Let’s explore how Beye’s Fabric, conversational analytics and reusable tools could fit the work.

Book a demo Explore the other comparisons →

The spreadsheet with all the tabs? That one. 😉