Enterprise · Wolters Kluwer
Weeks of Annual Reporting, Gone — 45 Branded Decks in Under 10 Minutes
Every year, Wolters Kluwer's marketing team hand-built 45 branded journal presentations from five separate systems — weeks of copy-paste. Now it's one click: 45 finished, fully editable decks in under 10 minutes, with every chart automatically verified against its source data.
Weeks → 10 min
Per annual reporting cycle
45
Branded decks per run
~95%
Of the team's time given back
35/35
Charts verified against source
What this means for you
Any report your team rebuilds on a schedule — monthly, quarterly, yearly — is a candidate for this. You keep the exact branded output you have today. You stop paying weeks of skilled time to produce it.
The Problem
Wolters Kluwer's legal publishing division produces 45 academic law journals. Every year, the marketing team builds a branded partnership overview presentation for each journal — subscriber trends, usage analytics, geographic reach, citation rankings, page counts.
The data lives in 5 separate systems: Tableau (subscribers, geography, segments), SIQ (platform usage, top articles), HeinOnline (visit statistics), Scopus/Clarivate/Google Scholar (rankings), and internal spreadsheets (page counts per issue).
The old process: manually copy-paste data from each source into a 16-slide PowerPoint template, recreate charts, cross-reference journal names across systems (which don't agree on naming), and repeat 45 times. This took multiple weeks every year and was error-prone — the same journal might appear as "b-Arbitra | Belgian Review of Arbitration" in Tableau and "b-Arbitra: Belgian Review of Arbitration" in SIQ.
The Solution
A full-stack web application that automates the entire pipeline from raw data to finished, auditable presentations.
Upload Dashboard
Drag files or click to upload
Tableau
12 files
SIQ
8 files
HeinOnline
3 files
Rankings
4 files
Page Counts
2 files
Marketing
6 files
The Result
- ✓ 45 branded journal presentations generated from a single button click
- ✓ Under 10 minutes for the full run — a process that used to take multiple weeks, every year
- ✓ Every chart automatically checked against its source data — 35/35 pass, so nobody re-verifies by eye
- ✓ Output is ordinary PowerPoint — the team can still open and tweak any deck
- ✓ Repeatable — when the data updates, regenerate everything in minutes instead of restarting the copy-paste
How It Works — In Plain Terms
The team drops their export files onto the dashboard — the system recognizes which source each file came from, no sorting required. It reconciles the five systems' conflicting journal names automatically, builds three-year trend charts, and fills the team's own 16-slide branded template. Live progress streams per journal, so during a run you can see exactly where the pipeline is.
Missing data is handled the way a careful human would handle it: if a journal has no usage statistics, that slide is removed cleanly rather than shipped with an empty chart. And because a partner-facing deck lives or dies on trust, a built-in audit reads every finished presentation back and checks each chart against the source row it came from.
Data Upload
Auto-Processing
PPTX Generation
Audit & Validate
Download
The Hard Parts — Honestly
Two things made this genuinely difficult — and both are why the "just record a macro" version of this project fails.
PowerPoint files corrupt silently. Three separate ways of producing a deck that looks fine until someone opens it were found and fixed — the kind of failure that, left unhandled, destroys a team's trust in automation after the first bad file. It's also exactly why the audit engine exists: the system proves each deck is right instead of assuming it.
The five systems don't agree on names. The same journal appears under different titles, abbreviations, and even invisible character variants across sources. A multi-strategy matcher resolves all 45 journals across every source with zero manual mapping — the step that used to make this a job only one experienced person could do.
Validation
0/35
charts validated against source data
Tech Stack
| Layer | Technology |
|---|---|
| Frontend | React 19, TypeScript, Vite, Tailwind CSS, shadcn/ui, Recharts |
| Backend | FastAPI, Python 3.13, pandas, openpyxl |
| Real-time | WebSocket (native FastAPI) |
| PPTX Engine | Direct XML manipulation (ElementTree) |
| Integrations | Tableau REST API, Google Scholar scraper |
| Validation | Custom audit engine (PPTX XML ↔ source data) |
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