Data analysis
VROF normalizes and aggregates scattered data to a consistent standard and delivers it as tables and dashboards for decision-making.
8 public cases · 2025–2026
Key data analysis cases.
Each case presents the situation before adoption, the result, and screens recreated with mock data. Academic cases, such as comment analysis for research, are included.
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SETI · Email document OCR auto-entry
It watches the inbox, reads the text in attached PDFs and images, and uses AI to sort that text into fields exported to Excel. You decide the output format.
Service status Launched 2026.01 from Pilot service · free of charge to
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Automated settlement-to-invoice ledger
Every morning it reads the settlement statements that 26 partners send by email and builds a ledger of who to invoice and for how much. Opening each email, downloading files and copying amounts by hand is gone. The only step left for staff is the issue button.
From reviewing settlements to the tax invoice ledger One person, a full day from 1 hour to
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Unified online-store sales dashboard
Order data that staff downloaded store by store is now collected automatically from three platforms, totaled on one set of rules and shown on a single screen.
Checking sales 3 platforms · each store separately from One screen · collected automatically to
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Comment topic and sentiment analyzer
Video comments collected by search term are grouped by topic and shown with their positive and negative distribution. Researchers set the number of topics on screen and can adjust the criteria and rerun the analysis themselves.
Comment topic analysis Skimmed by eye and judged by feel from Distributions by topic and sentiment to
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ELS disclosure comparison table builder
ELS and ELB product data is collected automatically from each securities firm. Product structures written as text are split into columns for maturity, observation interval, and early redemption terms, all in a single table.
Product comparison Checked firm by firm from Compared by term in one table to
Common questions on this topic
- News monitoring automation: get articles that mention your company as soon as they are published In short: a system that collects keyword news and sends alerts automatically is straightforward to build. There are three options to choose from and four things to decide.
- Copying data into Excel by hand can be automated: 3 criteria to check In short: any task that follows fixed rules and repeats can be automated. Work that seems too specific usually just has rules that have not been written down yet.
VROF aggregates data to a consistent standard.
In one case, consolidation that took more than 4 hours by hand was reduced to under 1 minute. Beyond saving time, the aggregation criteria that varied from person to person were unified into one.
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Defining aggregation criteria
To align item names and units that differ by platform, we first define what counts as the same item and document those rules.
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Scoring only measurable items
Scores and grades are calculated only from items that can be counted. Factors that cannot be measured are left out of the score.
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Itemizing text-based information
Information written as text, such as product descriptions and disclosures, is broken into items like maturity, frequency, and conditions so it can be compared in a single table.
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Source data tracing
Each result can be traced back to the source data, so the cause of any error can be found right away.
Measurement principles
We do not turn what we have not measured into numbers. Items without a basis are not scored, and the lack of a basis is stated as is.
If data needs to be collected before analysis, you can also use our Web data collection or App crawling service.
Talk to VROF about data analysis.
Tell us what data you are comparing and the criteria you use, and we will check whether it can be aggregated to a single standard.
Reply within 1 business day