Published on October 7, 2025.

If you're using the NetSuite AI Connector to pull data programmatically, there's a subtle but critical issue you need to understand about running reports that can lead to inconsistent and unpredictable results.

The Issue

When you run a report through the NetSuite AI Connector, you might expect it to run with default filter settings or perhaps "all data" unless you specify otherwise.

However, that's not what happens. When you run a report, it silently inherits filter values from the last time the NetSuite user ran that report manually — regardless of which role they were using at the time.

This means your reports are executing with "sticky" filter states that you cannot see, control, or predict.

How I Discovered This Issue

This problem came to light during a real business use case. I was working on a prompt to optimize vendor bill payment timing—specifically to maximize early-payment discounts while maintaining healthy cash flow across multiple subsidiaries.

The prompt was straightforward: Run the "Open Bills" report, extract all approved bills that are unpaid or partially paid with due dates in the next 45 days, and identify which bills should be paid early to capture discounts.

The agent ran the analysis and provided recommendations. But when I cross-checked against NetSuite manually, something was wrong: Bills that should have been flagged as "Pay Early" were completely missing from the analysis.

These weren't edge cases—they were legitimate bills with early-payment discount terms that the AI never even saw. The discrepancy meant potentially missing out on thousands of dollars in discount opportunities.

After multiple test runs, the pattern became clear: The results kept changing between runs, even though nothing had changed in NetSuite. Sometimes all subsidiaries appeared, sometimes only one. The AI was confidently analyzing incomplete data sets without any indication that anything was wrong.

That's when I discovered the filter inheritance behavior.

A Real Example

Let's say you're building a prompt to analyze open vendor bills. You write a simple prompt: "Give me a list of all open vendor bills."

The AI naturally responds by running the "Open Bills" report.

Here's what happened during my testing:
• Run 1: Returns 15 bills totaling $210,239.27
• Run 2: Returns 15 bills totaling $210,239.27 (same results)
• Run 3: Returns 1 bill totaling $7,242.58
• Run 4: Returns 0 bills
• Run 5: Returns 15 bills totaling $210,239.27

Between each run, in the NetSuite UI, I manually ran the same report with different subsidiary filters. The API silently inherited those filter settings.

Why This Happens

When you run a report through the API, the system has limited information to work with:
• The report you want to run
• Date ranges (when required)

There's no way to specify:
• Subsidiary filtering
• Department, class, or location filters
• Any other filter dimensions

When these filters aren't specified, NetSuite doesn't default to "show all data." Instead, it uses whatever filter values were last set by the user in the NetSuite UI.

NetSuite's documentation about the Report Tools, and specifically the "ns_runReport" function, can be found here: https://docs.oracle.com/en/cloud/saas/netsuite/ns-online-help/article_0905091732.html

The documentation states that "Only date filters are supported when running the reports. Other filters or report footer options available in the UI are currently not supported by the report tools."

What the documentation doesn't mention is that filters that the tool doesn't have access to are inherited from the last time that report was run in the UI.

The Implications

This creates several serious problems:

1. Unpredictable Results
Your analysis might be based on a subset of data without you knowing it. One moment you're analyzing all subsidiaries, the next you're only seeing data from the US subsidiary.

2. Silent Failures
There's no error message, no warning. The API successfully returns data—it's just not the data you think you're getting.

3. Inconsistent Analysis
If you're building reports, dashboards, or AI agents that make business decisions based on this data, your conclusions could be completely wrong depending on when the report was last run manually and with what filters.

4. Difficult Debugging
When results don't match expectations, it's nearly impossible to debug because you can't see what filters are actually being applied.

The Solution: Use SuiteQL Queries or Saved Searches

To get reliable, predictable results, avoid running reports for data analysis. Instead, use:

Option 1: SuiteQL Queries (Recommended)
Query the data directly with explicit control over all filtering:

SELECT 
    t.tranid AS bill_number,
    v.entityid AS vendor,
    t.trandate AS bill_date,
    t.duedate AS due_date,
    t.fxamountremaining AS amount_due,
    s.name AS subsidiary
FROM 
    transaction t
    INNER JOIN vendor v ON t.entity = v.id
    LEFT JOIN subsidiary s ON t.subsidiary = s.id
WHERE 
    t.type = 'VendBill'
    AND t.status IN ('VendBill:A', 'VendBill:B') -- Open statuses
    AND t.fxamountremaining > 0
ORDER BY 
    t.duedate

Benefits:
• You control exactly what data is returned
• Filters are explicit and visible in your code
• Results are consistent and reproducible
• You can filter by subsidiary, date ranges, or any other criteria programmatically

Option 2: Saved Searches
Create a saved search with the filters you need, then specify it in the prompt.

Benefits:
• Filters are defined in the saved search configuration
• More consistent than reports
• Can still leverage NetSuite's reporting engine

Best Practices

When requesting data, write the prompt in a way that suggests that a query be used. For example:
• "Query all open vendor bills across all subsidiaries"
• "Use a SuiteQL query to show me bills due in the next 30 days"
• "Pull the data directly from the transaction table"

Be specific about scope:
• "Show me open bills for ALL subsidiaries"
• "Only include data from the US subsidiary"
• "I need data across all entities"

Ask for transparency:
• "What query are you using to get this data?"
• "Are you querying all subsidiaries or just one?"
• "Show me the filters being applied"

Ask ChatGPT or Claude to check its work:
• "Can you verify this includes all subsidiaries?"
• "Are there any filters that might exclude some bills?"
• "Pull this data again using a direct query to confirm"

If ChatGPT or Claude suggests running a report:
Ask: "Can you query this data directly instead of using a report?"
Or: "Use SuiteQL to make sure we're getting all the data"

• There are still valid use cases for reports:
• When you specifically want to see results matching the user's last filter settings
• When you're explicitly asking to "run the [Report Name] as configured"
• For reports that don't have problematic filters (like financial statements with fixed date ranges)

However: Always document and communicate that the report will use the last-applied filter settings.

Back to Square One?

While the workaround is clear — avoid reports and stick with SuiteQL or saved searches — it’s worth acknowledging what this means in practice.

One of the big promises of the MCP Standard Tools SuiteApp (and the NetSuite AI Connector update that came with it) was to make report access easy for LLMs. Tools like Claude and ChatGPT could finally run built-in NetSuite reports directly, without the developer first hand-crafting SQL or setting up saved searches. That was a huge step forward in speed and accessibility.

But this filter inheritance issue undermines that advantage. If we can’t trust report outputs to be complete and consistent, we’re effectively pushed back to the “pre-update” era — writing SuiteQL queries and saved searches ourselves to ensure accuracy.

That doesn’t mean the Connector has no value; it’s still useful for other automation and data retrieval tasks. But if your use case demands reliable, auditable data (and most AI-driven use cases do), you’re back to explicit querying and search design — the very thing the new tools were meant to simplify.

Wrapping Up

Report filter inheritance in the NetSuite AI Connector is subtle but critical — and if you’re building AI-driven tools or integrations, it can quietly break your analysis. The API will happily return data that’s filtered in ways you didn’t ask for and can’t see, leaving your reports incomplete and your recommendations wrong.

The safest path is to skip reports for programmatic analysis and rely on SuiteQL or saved searches, where you control exactly what’s included and can verify your filters. Once you know about this behavior, avoiding it is straightforward — but ignoring it risks silent, hard-to-trace data gaps.