Vestberry, a fintech startup focused on managing VC and PE fund portfolios, faced a challenge with non-standardized reports from portfolio companies. The diversity of inputs made manual data transcription time-consuming and hindered efficient use of BI dashboards.
The platform depends on regular reporting of performance metrics from portfolio companies. The challenges included:
Each company used its own report formats (varying structures and languages)
KPIs were labeled inconsistently, lacking standardization
No unified format existed to streamline data processing for BI tools
Manual data entry was labor-intensive, slow, and prone to errors
As a result, onboarding of portfolio reports was slow, required manual intervention, and limited the scalability of the solution.
We delivered an AI solution for KPI data extraction and transformation that:
Automatically analyzes uploaded reports in any format or structure
Detects over 100 key KPIs (e.g., ARR, EBITDA, Cash Burn, MRR, Gross Margin…)
Recognizes the time context and data frequency (e.g., quarterly vs. monthly reporting)
Outputs a standardized data structure that Vestberry’s platform can directly use for BI dashboards
„The solution from Insynaps removed the biggest barrier in working with KPI data from our portfolio companies. Instead of manual adjustments, we can now work with clean, unified data almost instantly.“
Vestberry
- Automatic processing of reports in any structure, with no need for manual data entry.
- Faster data onboarding – processing takes minutes instead of hours of manual cleanup.
- Greater KPI consistency, enabling better analytics and comparability across the portfolio.
- Reduced error rate and increased trust in BI outputs.
- Improved user satisfaction, especially among VC managers and reporting companies.