Verifiable AI data science

The AI data scientist that shows its work.

Upload a dataset and ask a question in natural language. DSA runs statistics, SQL, machine learning, and visualization — then preserves the evidence behind every supported finding.

The sample data and this question ship with the demo; the example report was run by this instance when it started. Nothing was written for this page.

Evidence chain

Claimsupported finding
Evidenceconfidence 0.92
Tool callsql · stats · ml
Dataset hashsha256 pinned

Analyses

Runs in this environment

Datasets

Uploaded files

Evidence coverage

—

Computed per run · see Evaluation

01 · Ask

Start with the business question

Use a CSV, Parquet, JSON, or Excel file and describe what you actually want to learn.

02 · Analyze

Let tools do the computation

DSA plans and executes data-science tools instead of inventing numerical results in prose.

03 · Verify

Inspect where each claim came from

Review the agent trace, claim-level evidence, validation checks, and reproducible artifacts.

Why DSA

Most AI analysis tools give you an answer. DSA gives you the answer and the evidence behind it.

That makes generated analysis easier to inspect, challenge, reproduce, and trust.

Start with Step 2 · Ask

Claim
 └── Evidence
      └── Tool call
           └── Computation
                └── Dataset hash

Step 3 · Proof, not promises

Recent analyses

Latest runs in this environment. Open one to inspect its evidence chain.

Summarize the sales dataset: rows, columns, missing values and duplicates.Completed