Evidence · first-party tested/Query Live Databases Using Plain English with AI

Can auto-generate a correct chart for a simple month-over-month comparison, showing Last Month at 11 pending-paid orders versus Current Month at 20.

✓ Worked🧾 artifact-verifiedinput + output shownTest date not recordedDraxlr →

What was measured

Chart / Visualization Support

Does it generate charts automatically or allow useful visual views?

capability

What was given, what came back

Test input: Order pipeline breakdown with paid-pending edge case and last-month comparison · text · group: ecommerce-nl2sql-benchmark

Input — what we sent

The exact prompt

How many orders do we have at each stage right now?

Follow-up 1: What percentage of our orders were successfully delivered vs cancelled?

Follow-up 2: Are there any orders that are pending but already paid?

Follow-up 3: Compare that to last month — same breakdown, I want to see if things have improved or got worse.

A deeper operational analysis of current order stages, delivery-versus-cancellation rates, pending-but-paid edge cases, and a month-over-month comparison of the same breakdown.

Why this input is hard

· Order pipeline analysis
· Percentage calculation
· Edge-case detection
· Payment/order status joins
· Multi-turn context retention
· Month-over-month comparison
· Ambiguity handling for 'same breakdown'

Output — unretouched

Also checked on this input — same tool, 2 other criteria

Ambiguity Handling⚠ StruggledWhen a follow-up phrase could refer either to the full order-stage breakdown or to the immediately preceding pending-paid subresult, it did not ask for clarification and instead chose the narrower pending-paid interpretation.Business Insight✓ WorkedCan turn numeric results into plain-English takeaways; the delivered-vs-cancelled follow-up automatically summarized the split and framed delivered orders as more common than cancelled orders.

Provenance

Observation: 72e4330d-0ffc-4f08-8d78-f5942daa6a4f
Evidence run: db2bb5d5-0e0e-4cb3-8d76-3555c45c23cd
Study: Query Live Databases Using Plain English with AI
Research task: 86b9y6c99
Tested at: not recorded
Source: first-party
Evidence state: verified
Proof shown: input + output shown
Cost / latency: not captured
Repeat run: not captured
Tester: not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this

get_evidence({
  tool: "draxlr",
  scenario: "ecommerce-nl2sql-benchmark"
})

MCP · mcp.aidemos.com/api/mcp

JSON · ai.aidemos.com/v1/observations/72e4330d-0ffc-4f08-8d78-f5942daa6a4f

Free with attribution.

Same input, same check — 3 other tools

measured on Chart / Visualization Support

AskYourDatabase✗ FailedVisualization was not automatic; the report says the tool only produced a visual after an explicit follow-up prompt, so charts were not auto-generated on the initial answers.Definite◐ MixedCharts were not generated automatically in the chat; the report says an extra prompt was needed before Definite created a separate dashboard/doc, and the dashboard view shows an 'Orders By Stage' summary with a donut chart.Querio✓ WorkedAutomatically generates chart views for the order-stage breakdown and the delivered-vs-cancelled comparison, including the month-over-month share chart.

This evidence is published in

Query Live Databases Using Plain English with AI →

From the same study (page rebuilt from a later run)

Best AI Tools to Query Live Databases Using Plain English →

Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com