Scenario in benchmark · Version 1

The agent offers what to ask next

After an answer, the product suggests follow-up questions grounded in the just-completed analysis.

How the tools performed

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

Publication availability: 5 tools have 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
Anomaly AI
1 Pass0 Fail0 Not gradable
1 of 1 test case passed
1 of 1 assessed1 of 1 gradableView Result →
AskYourDatabase
0 Pass1 Fail0 Not gradable
1 of 1 test case failed
1 of 1 assessed1 of 1 gradableView Result →
Basedash
0 Pass1 Fail0 Not gradable
1 of 1 test case failed
1 of 1 assessed1 of 1 gradableView Result →
BlazeSQL
1 Pass0 Fail0 Not gradable
1 of 1 test case passed
1 of 1 assessed1 of 1 gradableView Result →
FutureSmart Database Agent
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
camelAI——No published result
Definite——No published result
Dot——No published result
Draxlr——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 it offers follow-up questions after answering.
  • Whether the suggestions are grounded in the answer just given and the analysis behind it.
  • Whether the follow-up suggestions are specific to the conversation rather than generic prompts.

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 →
The agent offers what to ask next in AI Database Agents | AI Demos