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Querio

AI Data Analyst · NL2SQL · Data Visualization · June 2026

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Our Take

Querio is strongest when the user wants a full analyst-style answer from one plain-English question. It does not only return a table; it can run multiple SQL queries, show the SQL, generate charts, and add business-style insights in the same workflow.

The biggest strength is the amount of work Querio does automatically. In the customer acquisition test, it created multiple tables, generated visual comparisons, and added a Key Insights section without needing a separate follow-up prompt.

The main limitation is readability in some follow-up outputs. In the best-customer workflow, Querio kept context correctly, but some follow-up results relied heavily on customer IDs instead of readable customer names. That makes the output accurate, but slightly less friendly for non-technical business users.

Download video: Demo video
Hands-on walkthrough of Querio converting natural language business questions into SQL-backed analysis, showing generated SQL, ecommerce result tables, auto-generated charts, key insights, follow-up handling, CSV/image export, and integration-related options.

In-Depth Review

Our detailed analysis of Querio — features, performance, and real-world testing.

AG
Ayush Ghosh
AI Demos Team
Verified Review

Feature-by-Feature Breakdown

NL2SQL Generation
Strong — Querio converts plain-English business questions into SQL-backed outputs without requiring the user to write SQL.
8.5/10
▾
Test Summary
Feature tested: NL2SQL Generation
Result: Passed (8.5/10) — Strong — Querio converts plain-English business questions into SQL-backed outputs without requiring the user to write SQL.

Feature tested: NL2SQL Generation

Result: Passed (8.5/10)

Verdict: Strong — Querio converts plain-English business questions into SQL-backed outputs without requiring the user to write SQL.

Expected behavior: Querio accepts natural language database questions and generates SQL-backed result tables with readable titles, tables, and supporting analysis.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio accepted the plain-English question and generated a customer acquisition analysis. It returned: * a list of customers created in the last 90 days * a — querio-querio-customer-acquisition-query-output.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio accepted the plain-English question and generated a customer acquisition analysis. It returned: * a list of customers created in the last 90 days * a — querio-querio-customer-acquisition-query-output.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshot is the key proof here. Check whether the natural-language question, SQL-backed customer list, period comparison, and generated acquisition analysis appear together in the same workflow.

Querio accepts natural language database questions and generates SQL-backed result tables with readable titles, tables, and supporting analysis.

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "NL2SQL Generation" test: Querio accepted the plain-English question and generated a customer acquisition analysis. It returned: * a list of customers created in the last 90 days * a, querio-querio-customer-acquisition-query-output.png

Querio accepted the plain-English question and generated a customer acquisition analysis. It returned: * a list of customers created in the last 90 days * a period comparison table * a weekly trend table * visual charts for acquisition comparison * a Key Insights section explaining the business meaning

Bottom Line
The screenshot is the key proof here. Check whether the natural-language question, SQL-backed customer list, period comparison, and generated acquisition analysis appear together in the same workflow.
SQL Visibility
Excellent — Querio shows the SQL it runs, making the output easier to verify.
9/10
▾
Test Summary
Feature tested: SQL Visibility
Result: Passed (9/10) — Excellent — Querio shows the SQL it runs, making the output easier to verify.

Feature tested: SQL Visibility

Result: Passed (9/10)

Verdict: Excellent — Querio shows the SQL it runs, making the output easier to verify.

Expected behavior: Querio displays generated SQL blocks in the chat/result workflow, with copy controls available around the SQL output.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio ran multiple SQL queries for the customer acquisition workflow. The SQL was visible for the user to inspect, including separate logic for the customer li — querio-querio-customer-acquisition-sql-visibility.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio ran multiple SQL queries for the customer acquisition workflow. The SQL was visible for the user to inspect, including separate logic for the customer li — querio-querio-customer-acquisition-sql-visibility.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshot is needed to verify the exact SQL visibility. Check whether Querio exposes the generated SQL blocks directly inside the workflow instead of only showing the final answer.

Querio displays generated SQL blocks in the chat/result workflow, with copy controls available around the SQL output.

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "SQL Visibility" test: Querio ran multiple SQL queries for the customer acquisition workflow. The SQL was visible for the user to inspect, including separate logic for the customer li, querio-querio-customer-acquisition-sql-visibility.png

Querio ran multiple SQL queries for the customer acquisition workflow. The SQL was visible for the user to inspect, including separate logic for the customer list, current-period count, previous-period count, and supporting chart/table data.

Bottom Line
The screenshot is needed to verify the exact SQL visibility. Check whether Querio exposes the generated SQL blocks directly inside the workflow instead of only showing the final answer.
Parallel Query Execution
Strong — Querio can break one compound question into multiple SQL-backed outputs.
9/10
▾
Test Summary
Feature tested: Parallel Query Execution
Result: Passed (9/10) — Strong — Querio can break one compound question into multiple SQL-backed outputs.

Feature tested: Parallel Query Execution

Result: Passed (9/10)

Verdict: Strong — Querio can break one compound question into multiple SQL-backed outputs.

Expected behavior: Querio can run multiple SQL queries from a single compound business question and combine the outputs into one analysis flow.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio split the request into multiple outputs: * customer list for the last 90 days * count for the last 90 days * count for the previous 90 days * per — querio-querio-customer-acquisition-multiple-sql-outputs.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio split the request into multiple outputs: * customer list for the last 90 days * count for the last 90 days * count for the previous 90 days * per — querio-querio-customer-acquisition-multiple-sql-outputs.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshot is needed because the capability is only clear when the workflow is inspected. Check whether the single prompt produces multiple SQL-backed tables and charts instead of one flat answer.

Querio can run multiple SQL queries from a single compound business question and combine the outputs into one analysis flow.

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "Parallel Query Execution" test: Querio split the request into multiple outputs: * customer list for the last 90 days * count for the last 90 days * count for the previous 90 days * per, querio-querio-customer-acquisition-multiple-sql-outputs.png

Querio split the request into multiple outputs: * customer list for the last 90 days * count for the last 90 days * count for the previous 90 days * period comparison table * weekly trend output * acquisition charts

Bottom Line
The screenshot is needed because the capability is only clear when the workflow is inspected. Check whether the single prompt produces multiple SQL-backed tables and charts instead of one flat answer.
Auto-Generated Charts
Strong — Querio generated charts automatically for analytical queries.
8.5/10
▾
Test Summary
Feature tested: Auto-Generated Charts
Result: Passed (8.5/10) — Strong — Querio generated charts automatically for analytical queries.

Feature tested: Auto-Generated Charts

Result: Passed (8.5/10)

Verdict: Strong — Querio generated charts automatically for analytical queries.

Expected behavior: Querio can generate visual outputs from query results without requiring the user to ask separately for visualization.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a period comparison chart for Last 90 Days vs Prior 90 Days — querio-image.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a period comparison chart for Last 90 Days vs Prior 90 Days — querio-image.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a weekly trend chart showing acquisition activity over time — querio-querio-customer-acquisition-weekly-trend-chart.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a weekly trend chart showing acquisition activity over time — querio-querio-customer-acquisition-weekly-trend-chart.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshot is the only place to verify the chart behavior. Check whether the comparison chart and weekly trend chart appear automatically as part of the same analysis flow.

Querio can generate visual outputs from query results without requiring the user to ask separately for visualization.

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "Auto-Generated Charts" test: Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a period comparison chart for Last 90 Days vs Prior 90 Days, querio-image.png

Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a period comparison chart for Last 90 Days vs Prior 90 Days

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "Auto-Generated Charts" test: Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a weekly trend chart showing acquisition activity over time, querio-querio-customer-acquisition-weekly-trend-chart.png

Querio generated visual outputs for the customer acquisition workflow. The chart set included: * a weekly trend chart showing acquisition activity over time

Bottom Line
The screenshot is the only place to verify the chart behavior. Check whether the comparison chart and weekly trend chart appear automatically as part of the same analysis flow.
Automatic Insight Generation
Excellent — Querio adds business-style interpretation instead of only returning raw tables.
9/10
▾
Test Summary
Feature tested: Automatic Insight Generation
Result: Passed (9/10) — Excellent — Querio adds business-style interpretation instead of only returning raw tables.

Feature tested: Automatic Insight Generation

Result: Passed (9/10)

Verdict: Excellent — Querio adds business-style interpretation instead of only returning raw tables.

Expected behavior: Querio can generate a Key Insights section that explains what the result means in plain English.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio generated a Key Insights section for the customer acquisition result. The insights explained that: * recent acquisition was lower than the previous 90- — querio-querio-customer-acquisition-key-insights.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio generated a Key Insights section for the customer acquisition result. The insights explained that: * recent acquisition was lower than the previous 90- — querio-querio-customer-acquisition-key-insights.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshot is needed to verify the insight layer. Check whether Querio explains the business meaning of the acquisition drop instead of only showing tables and charts.

Querio can generate a Key Insights section that explains what the result means in plain English.

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "Automatic Insight Generation" test: Querio generated a Key Insights section for the customer acquisition result. The insights explained that: * recent acquisition was lower than the previous 90-, querio-querio-customer-acquisition-key-insights.png

Querio generated a Key Insights section for the customer acquisition result. The insights explained that: * recent acquisition was lower than the previous 90-day period * most recent sign-ups were concentrated in a smaller number of weeks * there was a gap in acquisition activity worth investigating * the previous period had more consistent weekly acquisition activity

Bottom Line
The screenshot is needed to verify the insight layer. Check whether Querio explains the business meaning of the acquisition drop instead of only showing tables and charts.
Multi-Turn Query Context
Good — Querio maintained context across the tested best-customer follow-ups.
8/10
▾
Test Summary
Feature tested: Multi-Turn Query Context
Result: Partial (8/10) — Good — Querio maintained context across the tested best-customer follow-ups.

Feature tested: Multi-Turn Query Context

Result: Partial (8/10)

Verdict: Good — Querio maintained context across the tested best-customer follow-ups.

Expected behavior: Querio can continue analysis across follow-up questions by using the previous result context.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio used the top-customer context from the previous result and checked unpaid orders for the selected customers. The output identified unpaid-order status fo — querio-querio-top3-unpaid-order-context.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio used the top-customer context from the previous result and checked unpaid orders for the selected customers. The output identified unpaid-order status fo — querio-querio-top3-unpaid-order-context.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio continued from the same top-customer context and returned payment method usage for the selected customers. — querio-querio-top3-payment-method-context.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio continued from the same top-customer context and returned payment method usage for the selected customers. — querio-querio-top3-payment-method-context.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The proof depends on comparing the follow-up screenshots. Check whether Querio keeps the “top 3” customer context across the unpaid-order and payment-method follow-ups.

Querio can continue analysis across follow-up questions by using the previous result context.

QUERY
For the top 3 from that list — do any of them have unpaid orders?
↓
OUTPUT
Output artifact for "Multi-Turn Query Context" test: Querio used the top-customer context from the previous result and checked unpaid orders for the selected customers. The output identified unpaid-order status fo, querio-querio-top3-unpaid-order-context.png

Querio used the top-customer context from the previous result and checked unpaid orders for the selected customers. The output identified unpaid-order status for the top customers and continued the workflow without requiring the user to restate the full customer list.

QUERY
What payment methods do these top 3 usually use?
↓
OUTPUT
Output artifact for "Multi-Turn Query Context" test: Querio continued from the same top-customer context and returned payment method usage for the selected customers., querio-querio-top3-payment-method-context.png

Querio continued from the same top-customer context and returned payment method usage for the selected customers.

Bottom Line
The proof depends on comparing the follow-up screenshots. Check whether Querio keeps the “top 3” customer context across the unpaid-order and payment-method follow-ups.
Data Export
Strong — Querio supports reusable output through downloadable data and chart exports.
8/10
▾
Test Summary
Feature tested: Data Export
Result: Passed (8/10) — Strong — Querio supports reusable output through downloadable data and chart exports.

Feature tested: Data Export

Result: Passed (8/10)

Verdict: Strong — Querio supports reusable output through downloadable data and chart exports.

Expected behavior: Querio allows generated data and charts to be reused outside the chat/report workflow through export options.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy — querio-querio-export-csv.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy — querio-querio-export-csv.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy — querio-querio-export-chart-image.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy — querio-querio-export-chart-image.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshot is needed to verify where export appears. Check whether the data and chart outputs expose reusable export actions rather than staying only inside the generated analysis page.

Querio allows generated data and charts to be reused outside the chat/report workflow through export options.

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "Data Export" test: Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy, querio-querio-export-csv.png

Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy controls * print option

QUERY
Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days?
↓
OUTPUT
Output artifact for "Data Export" test: Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy, querio-querio-export-chart-image.png

Querio provided downloadable data and chart export options. Observed export behavior included: * CSV download for data * chart export as image * SQL copy controls * print option

Bottom Line
The screenshot is needed to verify where export appears. Check whether the data and chart outputs expose reusable export actions rather than staying only inside the generated analysis page.
Follow-up Context Selection
Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately previous question.
▾
Test Summary
Feature tested: Follow-up Context Selection
Result: Failed — Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately previous question.

Feature tested: Follow-up Context Selection

Result: Failed

Verdict: Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately previous question.

Expected behavior: This is a real failure case because the phrase “same breakdown” should refer to the immediately previous pending-but-paid question. Instead, Querio reused the earlier delivered-vs-cancelled context, which can mislead the user in a multi-turn analysis flow.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): In Screenshot 1, highlight the previous question: “Are there any orders that are pending but already paid?” — querio-querio-pending-paid-followup-context.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): In Screenshot 1, highlight the previous question: “Are there any orders that are pending but already paid?” — querio-querio-pending-paid-followup-context.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Input

Observed output: Output artifact (Image): Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately pr — querio-querio-same-breakdown-wrong-context.png

Input artifact: Input artifact (Text prompt): Input

Output artifact: Output artifact (Image): Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately pr — querio-querio-same-breakdown-wrong-context.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The screenshots are required because the failure is only visible when both turns are compared together. Screenshot 1 shows the pending-but-paid context, while Screenshot 2 shows that the follow-up comparison moved to a different breakdown.

This is a real failure case because the phrase “same breakdown” should refer to the immediately previous pending-but-paid question. Instead, Querio reused the earlier delivered-vs-cancelled context, which can mislead the user in a multi-turn analysis flow.

QUERY
Are there any orders that are pending but already paid?
↓
OUTPUT
Output artifact for "Follow-up Context Selection" test: In Screenshot 1, highlight the previous question: “Are there any orders that are pending but already paid?”, querio-querio-pending-paid-followup-context.png

In Screenshot 1, highlight the previous question: “Are there any orders that are pending but already paid?”

QUERY
Compare that to last month — same breakdown, I want to see if things have improved or got worse.
↓
OUTPUT
Output artifact for "Follow-up Context Selection" test: Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately pr, querio-querio-same-breakdown-wrong-context.png

Querio answered the follow-up, but it compared the delivered-vs-cancelled breakdown instead of continuing the pending-but-paid breakdown from the immediately previous question. The tool generated a month comparison, but the context selection shifted from Follow-up 2 back to the earlier delivered-vs-cancelled analysis.

In Screenshot 2, highlight the follow-up question: “Compare that to last month — same breakdown…”

Bottom Line
The screenshots are required because the failure is only visible when both turns are compared together. Screenshot 1 shows the pending-but-paid context, while Screenshot 2 shows that the follow-up comparison moved to a different breakdown.

Pricing & Access

Plans as of June 2026

TESTED
14 Days Free Trail
$0
Tested using the free 14-day trial. Access required a business email. This plan was used for creating the demo video, testing the core workflow, collecting artifacts, and preparing the tool page.
Startup
Billed $5,000/year
Includes 1 data connection, 10 users, Querio context layer, Slack bot, automatic model choice, standard compute, standard credits, and standard support.
Core
Billed $20,400/year
Includes 3 data connections, unlimited users, SSH/VPN, guided onboarding and training, choose your own model, higher compute, extended credits, and premium support.
Enterprise
Custom / Let’s talk
Includes 5 connections, cross-datasource querying, dedicated compute, migration/ETL support, self-hosting/GovCloud options, lower usage cost, GovCloud support, and priority support.

Pricing checked: June 2026. Recheck quarterly before publishing. Querio’s pricing should be verified again before publishing because plan names, billing amounts, and included limits can change. Querio is positioned more like a serious team/enterprise analytics platform than a lightweight personal SQL assistant. The tested value is strongest when teams need visible SQL, charts, insights, Slack support, and embedded analytics options in one workflow.

Is This Right For You?

A side-by-side guide based on our hands-on testing.

✓ Use This If
●You want plain-English questions converted into SQL-backed analysis.
●You need the generated SQL to be visible and inspectable.
●You want charts and business insights generated automatically.
●You need export options for charts or query data.
●You want Slack or embedded analytics support around your data workflow.
✕ Skip This If
●You want a very lightweight personal SQL chatbot.
●You need the cheapest NL2SQL tool for small experiments.
●You want every answer to be a single simple table only.
●You do not want multi-query outputs or analyst-style breakdowns.
●You need follow-up outputs to always prioritize business names over technical IDs.

Use Case Track Record

Query Live Databases Using Plain English with AI
ProductivityAI Workspaces & AssistantstextMarketingFounders
Yes. In testing, Querio showed generated SQL in the workflow, and the SQL could be inspected directly.
Yes. In the customer acquisition test, Querio generated comparison and weekly trend charts without needing a separate “visualize this” follow-up.
Yes. Querio generated a Key Insights section during the customer acquisition workflow, explaining the acquisition drop and timeline pattern in plain English.
Yes. Querio maintained the top-customer context across unpaid-order and payment-method follow-ups. The main caution is that some follow-up outputs were more ID-heavy than business-friendly.
Mostly yes. Querio is strong because it generates tables, charts, and insights from plain English. However, some outputs still require comfort with tables, SQL, and occasional customer IDs.
Querio was tested in June 2026 using an ecommerce PostgreSQL-style database across customer acquisition analysis, customer value analysis, and order pipeline analysis.
Yes. In testing, Querio ran multiple SQL queries from a single compound question and combined the outputs into one analysis flow with tables, counts, charts, and supporting analysis.
Yes. Observed export behavior included CSV download for data, chart export as image, SQL copy controls, and a print option.
A tested failure case showed Querio misreading “same breakdown” in a follow-up. It compared the delivered-vs-cancelled breakdown instead of continuing the immediately previous pending-but-paid analysis.
Yes. The review says Querio is positioned more like a serious team/enterprise analytics platform than a lightweight personal SQL assistant.
The public pricing listed in June 2026 showed Startup at billed $5,000/year, Core at billed $20,400/year, and Enterprise as Custom / Let’s talk.

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