Not another dashboard. A system that turns your sell-in, sell-out and market data into answers — and an AI analyst that explains why the numbers moved and what to do, every claim cited back to the figures.
Swissmed's commercial picture lives in a sprawling Excel workbook that takes an analyst days to wrangle — and still can't answer the question that matters: why?
what a naive sum of the real workbook reports
over-counted — because subtotals are mixed into detail rows. This is the #1 correctness risk, and we've already mapped it.
Three layers working together: clean your data once, see everything on live dashboards, and ask an AI analyst anything — grounded in your own figures.
Upload your Excel as-is. The engine parses the 636-column mess, strips subtotals and errors, and resolves dirty SKU strings into brands, dosages and units — with a human review step. The number is right, every time.
Sell-in vs sell-out, market share, geography, channel stock and the brand-growth waterfall — all the views in your requirements doc, in packs and value, across every time grain.
The differentiator. Ask “why did Nakom decline?” in plain language and get a cited answer. It also surfaces risks and opportunities before you ask — grounded in your data, never invented.
Every view your team asked for — filtered live by year, area, business unit and period.
KPI strip + brand-growth waterfall + SI-vs-SO at a glance.
TGT, ACT, vs-target and vs-PY by brand, in packs and value.
Share by brand and its movement vs prior year, in points.
Azerbaijan → Baku → regions → districts drill-down.
Channel inventory, months of cover and auto-detected buy-ins.
Every feed with freshness & coverage — what's live, what's next.
The engine doesn't just show the headline. It connects sell-in, sell-out and stock into one narrative.
Ferrum Lek carried the year — +$1.9M sell-out and +2.1pp share, strongest in Sumgait & Sheki-Zaqatala. Dermazin and Diclac added another $1.3M. Real OTC demand, not just stocking.
Nakom is the one to worry about — the only declining line, off $0.4M and −1.4pp share, concentrated in Baku. Meanwhile sell-in ran $2.6M ahead of sell-out — stock is building.
Ask in plain language. Every number traces back to a source — if it can't be grounded, it says so rather than inventing a figure.
Stock building faster than it sells. SI $2.6M ahead of SO, mostly a Sep buy-in. Slowing Ferrum Lek SI next quarter avoids a write-down.
Nakom is the brand to worry about. SO −$0.4M YoY, −1.4pp share — the only declining line, weak in Baku.
Ferrum Lek carried the year. +$1.9M and +2.1pp share, strongest in the regions — OTC pull, not stocking.
A repeatable pipeline. Re-uploading a file never double-counts — nothing reaches the dashboards until a person confirms the mappings.
Drop the Excel/CSV in. Stored securely, isolated per tenant.
Detect the two-row header, unpivot 636 columns, drop subtotals, coerce errors.
AI suggests brand/dosage/pack from each dirty SKU; an analyst confirms once.
Clean facts into a warehouse — idempotent, fully traceable to source.
Dashboards refresh; the analyst re-sweeps for new risks & opportunities.
Today the file shows sell-out only — about three-quarters of the picture. Each feed we connect widens what the engine can see.
of national sell-out visible today
Connecting the pharmacy panel and a market subscription lifts visibility toward full-market share & competitor view — the part the current Excel simply can't show.
You see working software early — dashboards on your real data before the analyst, the analyst before connectors.
Accounts, roles, and strict data isolation — your data is provably yours alone.
Upload → clean → review → load; Overview, SI/SO, Geography and the waterfall on real data.
Ask anything, get cited answers; nightly sweep surfaces risks and opportunities.
Add the market panel, ingest reports for the analyst to cite, auto-flag channel loading.
Replace uploads with live feeds; same engine, no rebuild.
The hard parts — the ones that make pharma BI fail — are designed for, not glossed over.
A dashboard shows you what happened. Swissmed Intelligence tells you why — and what to do next.