Reporting & Intelligence
From fragmented data to insight, at every level
Reporting built on reconciled data rather than on exports. The same numbers roll from an investor-level view down to a single order or cost line, any figure opens to the transactions beneath it, and a question asked in plain language is answered from the ledger rather than from a dashboard somebody maintained by hand.
The problem
Every number agrees until somebody asks where it came from
Most management reporting is assembled from exports. Each system is queried separately, the results are pasted together, adjustments are applied in cells nobody documented, and the pack goes out. It usually looks right. What it cannot do is survive a question: the board number and the business unit number were built on different cuts, the drill-down stops at a summary row, and the person who knew which tab held the reclassification has left. So the reporting cycle is spent rebuilding agreement rather than explaining performance, and the numbers are trusted in inverse proportion to how closely they are examined.
The plain-language answers here are produced by Nabhik AI running against reconciled finance data. If what you need is the agent platform itself — building, deploying and evaluating your own agents across any operational domain — that is Nabhik AI.
Capability
Reconciled before it is reported
Aggregation is the easy half. What makes the numbers defensible is what happens before the roll-up.
Aggregation across systems
Ledgers, billing, order management, payments, procurement, payroll and operational systems are brought together on a common set of dimensions — entity, period, counterparty, product, channel, cost centre — rather than being reported side by side and reconciled by eye.
Reconciliation applied before roll-up
Differences between systems are identified, classified and resolved before anything is summed. A figure only rolls up once the records behind it agree, and where they do not, the exception is visible in the report rather than absorbed into it.
Business rules configured, not coded
Allocations, eliminations, revenue recognition treatment, cost apportionment, currency translation and reclassifications are held as configuration you can read and change, with the version that produced any given figure recorded against it.
One definition, everywhere
A metric is defined once and used by every view that references it, so the investor pack, the business unit review and the operational report are the same number seen at different resolutions rather than three numbers that need explaining.
Capability
Board view to line item, without changing tools
One hierarchy, continuous from the top of the house to a single transaction.
Every level in one structure
Investor and board view, business unit, channel, legal entity, product line, and down to the individual order, revenue item and cost item. Moving between levels is navigation, not a different report built by a different team.
Drill-through to the source transaction
Any figure opens to the records that produced it, and those records open to the documents behind them. The path from a board-level margin to the invoice that moved it is a few clicks rather than a request and a two-day wait.
Scheduled MIS distribution
Packs are produced on a schedule, in the format each audience expects, and delivered to the people who need them — with the underlying data as at a stated point in time, so a pack can be reproduced exactly as it was sent.
Ask Nabhik AI in plain language
Questions are asked in ordinary words and answered from the reconciled ledger, not from a pre-built dashboard. The answer cites the records it came from, so it can be opened, checked and disagreed with — which is what makes it usable in a review rather than merely impressive in a demo.
Why it holds up
The difference between a report and an answer
A dashboard built on exports can tell you what a number is. It cannot tell you why, and it cannot prove it. Because the roll-up here sits on reconciled data, the number in the board pack and the number in the operational review are the same figure at different resolutions, and either can be opened to the transactions underneath. That is also what makes natural-language querying safe: an answer generated from a reconciled ledger with its sources attached can be verified in the meeting, while an answer generated from a warehouse of unreconciled extracts can only be believed.
How it works
From source systems to a number you can defend
- 01
Connect the sources
Finance and operational systems are connected at record level rather than through periodic exports, so the data behind a report is current and traceable to where it lives.
- 02
Map to common dimensions
Entities, periods, counterparties, products, channels and cost centres are mapped once, so the same transaction means the same thing in every view.
- 03
Reconcile
System-to-system and ledger-to-subledger differences are identified and classified, and unresolved items are carried into the report as visible exceptions instead of being netted away.
- 04
Apply the rules
Allocations, eliminations, translation and recognition treatment are applied from configuration, with the rule version recorded against every figure it touched.
- 05
Roll up and distribute
Figures aggregate through the hierarchy to the board view, and packs are produced and delivered on schedule in the formats each audience uses.
- 06
Ask and drill
Questions are asked in plain language through Nabhik AI or by opening a figure directly, and either path lands on the transactions that produced it.
Questions
Frequently asked
- How is this different from a BI tool?
- A BI tool visualises whatever data it is given. If that data is a set of unreconciled extracts, the chart inherits the problem and hides it behind a clean axis. Here reconciliation happens before aggregation, so the roll-up is built on records that agree, and every figure retains the path back to its source transactions. If you already have reconciled data and only need visualisation, keep your BI tool — this is the layer beneath it.
- Do we have to replace our existing reporting stack?
- No. Most deployments keep existing dashboards and feed them from the reconciled layer instead of from raw extracts. The value is in the reconciliation, the shared definitions and the drill-through, not in owning the pixels.
- What does 'ask Nabhik AI' actually mean in practice?
- Nabhik AI is our agent system, and here it is pointed at the reconciled finance data with your rules and permissions applied. You ask a question the way you would ask a colleague — why a cost line moved, which channel carried a margin change, what a counterparty has cost across entities this year — and it answers with the records it used attached, so the answer can be opened rather than taken on trust.
- Can it answer questions it should not be allowed to answer?
- It answers within the same permissions the person already has. Entity, business unit and role-level access apply to the query and to the drill-through, so a question cannot be used to reach data a report would not have shown.
- How far down does the drill-through go?
- To the individual order, revenue item and cost item, and from there to the source document where one exists — the invoice, the receipt, the contract clause. The point of the hierarchy is that it does not stop at a summary level that happens to be convenient.
- How long before the first pack is running?
- We scope this per deployment, since it depends on how many source systems are in scope and how much dimension mapping already exists. The onboarding stages and their exit criteria are set out on the VapusFin overview page.
Bring us the pack you least enjoy producing
Show us the month-end MIS that takes a week and the questions it always provokes. We will show you the same view built on reconciled data, with the drill-through working and the questions answered from the ledger.
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