Ask a question. Follow the answer all the way down.

The difference between SAVI and a general-purpose AI tool is not how the answer is worded. It is where the number came from.

The four steps

1

You ask

Ask in plain English, “why did EBITDA drop this quarter?” No query language, no report builder.

2

SAVI computes

SAVI queries your actual financial records and calculates the answer. The figure is produced by computation, not by a language model.

3

SAVI explains

The AI turns the computed result into a clear written answer. It describes the numbers, it never invents them.

4

You verify

Click any figure and follow it down: the figure, the formula, the query, the underlying rows, the source record.

The Trace, in Full

Click through each node to see how every number moves from computed figure to originating source record.

1

Figure

→

2

Formula

→

3

Query

→

4

Rows

→

5

Source Record

Figure (Computed Output)

EBITDA (Q2 2026): ₹ 42,850,000

The reported metric is displayed clearly. Clicking the figure opens the exact formula and lineage used to generate it.

Why this matters

A general-purpose AI model produces text that sounds correct. When the subject is language, that is usually good enough. When the subject is a number in a set of accounts, it is not, because a fluent wrong figure is more dangerous than an obvious one. It gets believed, and it gets acted on.

SAVI separates the two jobs. The computation is deterministic and reproducible. The AI writes the explanation. That separation is why a figure from SAVI can be checked, and why the answer to “where did this come from?” is always a record, never a guess.

When SAVI doesn't know

If the underlying data is missing or insufficient, SAVI reports that plainly instead of producing an estimate. An honest gap is more useful than a confident approximation, and considerably safer.

Experience the Trace on your numbers

Book a walkthrough to see SAVI trace financial data end-to-end.

Book a Demo