Scenario in benchmark · Version 1

Customer corrects information given earlier

A later correction supersedes earlier information for the rest of the interaction.

How the tools performed

Every in-scope tool is visible. Outcomes come from current published Results for this scenario and benchmark version.

Publication availability: 1 tool has a current published Result.

No published result does not tell you whether a tool has been tested. Test coverage is shown only for comparable published Results.

ToolPublished outcomesTest coverageResult
Published Results · alphabetical, not ranked
BlazeSQL
1 Pass0 Fail0 Not gradable
1 of 1 test case passed
1 of 1 assessed1 of 1 gradableView Result →
No published result · alphabetical
AI for Database——No published result
Anomaly AI——No published result
AskYourDatabase——No published result
Basedash——No published result
camelAI——No published result
Definite——No published result
Dot——No published result
Draxlr——No published result
FutureSmart Database Agent——No published result
Querio——No published result

Assessed = Pass + Fail + Not gradable. Gradable = Pass + Fail. Both use the published Result’s pinned-test denominator. — means not publicly available.

Test design

Pinned test cases
1
Disclosure
0 public · 1 withheld
Capabilities exercised here
Conversational Interaction

What this scenario evaluates

  • Whether the later correction replaces the earlier detail in later turns.
  • Whether the response reflects only the corrected information, not a mix of old and new details.
  • Whether the agent does not continue reasoning from the superseded detail after the correction.

Exact wording, inputs, fixture state, expected output and detailed grading remain at the test-case level and may be withheld while the benchmark version is active. The scenario and its evaluation intent are public.

How the results are graded

  • Pass: the test-case expectations hold.
  • Fail: an expectation demonstrably does not hold.
  • Not gradable: the evidence cannot establish the outcome.

Version 1 uses test-case expectations; no scenario rubric is pinned.

Benchmark methodology →
Customer corrects information given earlier in AI Database Agents | AI Demos