vFunction Ratings (September 2025)
This page breaks down vFunction ratings from all verified review sources to give you a clear, unbiased view of what real users think in September 2025.
We’ve aggregated the latest scores from all major platforms like Trustpilot, G2, Capterra and many more to help you understand vFunction’s overall reputation. This data-driven overview will show you exactly how vFunction is rated - including how it compares to competitors.
vFunction's Overall Rating Summary
- Average Rating:4.7/5
- Total Reviews:3 reviews
- Sources:G2
- Last updated:September 1, 2025
vFunction Ratings by Source
| Platform | Rating | Reviews | Last Update |
|---|---|---|---|
 G2 | 4.7/5 | 3+ reviews | 01.09.25 |
What is vFunction?
vFunction is an AI-driven architectural observability platform that helps understand application architecture, reduce technical debt, and continuously modernize with actionable insights. Key features include architectural discovery and visualization, dependency mapping, technical debt analysis, prioritization and alerting, architectural drift monitoring, remediation and automation, and integration and exporting. The platform aims to increase engineering velocity, scalability, and resiliency by identifying and recommending ways to reduce complexity in applications.
🤔 vFunction vs Competitors: How Do Ratings Compare?
Check out vFunction AlternativesFrequently Asked Questions
How trustworthy is vFunction?
According to G2 review site vFunction holds rating of 4.7/5, indicating a strong level of trust and satisfaction among users as of September 2025.
How many stars is vFunction rated?
vFunction has an average star rating of 4.7 out of 5 stars based on average of 3 reviews as of September 2025.
Where does the rating data come from?
The ratings are pulled from vFunction public reviews pages on platforms: G2. We update these ratings monthly to ensure they reflect the most current customer feedback.
How overall average rating for vFunction is calculated?
The overall average rating is calculated by taking the weighted average of all ratings, using the total reviews count from each platform as the weight.