RIB BI+ is an innovative Construction Analytics Software: ✓ Visualize & track construction data with professional dashboards ✓ Avoid projects delays
Each model independently rates RIB BI+ (ex datapine) on a 1–5 star scale.
RIB BI+ (formerly datapine) is a Berlin-based BI and construction analytics platform now part of RIB Software/Schneider Electric. Backed by a major parent company, it has reasonable credibility in a niche market, though independent reviews and public presence are limited.
RIB BI+ (ex datapine) offers construction analytics software with professional dashboards. Limited public information affects scoring.
RIB BI+ (formerly datapine) offers construction analytics software. As information regarding its trust, regulation, trading, support, and reputation in a financial context is limited, scores are set at a neutral baseline.
RIB BI+ (ex datapine) is a BI/analytics tool focused on construction. Formerly a well-reviewed BI SaaS (datapine) and associated with RIB Software. No major controversies; typical SaaS compliance (e.g., GDPR). Strong product reputation; support and transparency solid but standard.
Limited public information available on RIB BI+ (ex datapine). Scores set to neutral 50 due to insufficient data on reputation, compliance, product reviews and user feedback.
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RIB BI+ (ex datapine) is rated 2.8 out of 5 (“Poor”) on TrustRating, based on 5 independent AI model assessments. The TrustScore combines real customer reviews with AI models that independently assess trust, regulation, support and reputation signals. Always do your own research before making a purchase or investment.
TrustRating doesn't issue scam verdicts — we publish the data instead: RIB BI+ (ex datapine) scores 2.8 out of 5 (“Poor”) based on 5 independent AI model assessments. Every review passes TrustGuard, our fraud-screening system that blocks fake and paid reviews, so the score reflects genuine customer experience. Read the most recent reviews below before you decide.
RIB BI+ (ex datapine) currently has a TrustScore of 2.8 out of 5 (“Poor”). The score blends verified customer reviews with assessments from multiple independent AI models, and it updates automatically as new reviews and scans come in. You can read exactly how scores are computed on our methodology page.
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