Case Study · BuildingMinds
Joined BuildingMinds as a foundational design hire, shaping how design operates across the product — not just what it looks like. Over six years, I led the design of the platform's core intelligence layer, built the design system from scratch, and embedded user-centered thinking into every stage of the build.
"Real estate accounts for 40% of global CO₂ emissions. Most portfolio managers still track sustainability targets in spreadsheets."
The core tension that shaped every design decision
We're reframing sustainability as a design opportunity, not a compliance burden. BuildingMinds builds the intelligence layer for real estate — aggregating performance data across entire portfolios and translating it into clear, actionable benchmarks that asset managers can confidently act on.
I led design on the platform's core ESG modules: portfolio benchmarking, building deep-dives, carbon tracking, and compliance reporting. The product serves portfolio directors, sustainability officers, and asset managers at some of Europe's largest real estate funds.
Every building is different, making it hard to compare performance or set meaningful standards across a portfolio. Sustainability data lived in disconnected systems, reporting was largely manual, and regulatory pressure was accelerating faster than existing tooling could handle.
The compliance gap was growing. EU Taxonomy, SFDR and the GHG Protocol demanded disclosure levels that existing infrastructure couldn't support — turning what should be a strategic advantage into a source of organizational anxiety for finance and sustainability teams alike.
Three connected design challenges, one platform. We unified fractured sustainability data under consistent models with provenance tracking, built role-based views so each stakeholder sees exactly the right level of detail, and turned multi-week compliance reporting cycles into guided, auditable workflows that regulators could trust.
We ran 14 stakeholder interviews across portfolio managers, sustainability officers, and asset directors — supplemented by co-design workshops and competitive analysis across 8 ESG/proptech platforms. Six findings shaped the entire design direction.
With research complete, design work began with the core reporting flows — the workflows that sustainability teams live in daily. Rather than starting with features, we mapped what decisions users actually needed to make and worked backwards to the interface.
Early explorations focused on surface-level clarity: how to present complex regulatory data without overwhelming the user, and how to build enough context that managers could act confidently without needing to be experts in every compliance framework.
Two of the most impactful features on the platform were built around AI — and both required rethinking what AI interaction looks like for enterprise users who need to trust every number they sign off on.
Rather than presenting raw performance scores, the platform uses AI to translate building data into prioritized retrofit recommendations — surfacing which interventions deliver the best carbon reduction relative to cost.
Each suggestion comes with a confidence rating and data provenance, so sustainability officers can trace every recommendation back to the underlying sensor or invoice data.
Utility invoices arrive in hundreds of different formats across hundreds of buildings. AI extraction removes the manual transcription step — automatically identifying service periods, consumption units, and billing line items from unstructured documents.
High-certainty extractions appear pre-filled and quiet. Low-confidence fields are flagged for human review. Every extraction is linked to its source image, creating a full audit trail for regulators.
Energy use and environmental impact become trackable across building portfolios. Consumption pattern analysis reveals inefficiencies and improvement opportunities. With rising energy costs impacting profitability, this clarity enables strategic management that reduces expenses while lowering carbon footprint.
Energy use and environmental impact become trackable across building portfolios. Consumption pattern analysis reveals inefficiencies and improvement opportunities. With rising energy costs impacting profitability, this clarity enables strategic management that reduces expenses while lowering carbon footprint.
Building retrofit planning reveals costs, benefits, and optimal sequencing. Investment decisions are informed by environmental impact and financial return analysis, ensuring upgrade strategies deliver sustainability improvements while maintaining strong economic performance and asset value.
Carbon risk is measured, properties benchmarked against climate targets, and sustainability performance validated transparently. This attracts climate-conscious investors, ensures regulatory compliance, and protects asset values from devaluation as environmental standards shape real estate markets.
It tracks real-time energy, water, and resource usage across properties to detect anomalies, optimize consumption, control costs, and improve operational efficiency.
From Typing to Verifying: Instead of a blank form, users interact with AI-extracted data. The AI does the heavy lifting, identifying service periods and consumption units across diverse invoice layouts.
Confidence-Driven Design: The UI highlights AI certainty. High-confidence data stays quiet, while low-confidence areas are flagged, directing the user's eye only where human intervention is needed.
Audit-Ready Intelligence: The AI creates a persistent digital link between the extracted value and the source image, making the workflow 100% transparent for auditors.
Impact: Moving from manual toil to AI orchestration transformed a 10-minute administrative chore into a 30-second oversight task.
The redesigned platform launched to a cohort of 12 enterprise clients across Germany, the Netherlands, and the UK. The portfolio overview became the primary entry point for 91% of daily sessions within the first month, validating the IA restructure.
Reporting time dropped by 10–50% depending on portfolio complexity. Sustainability officers who previously spent two weeks compiling SFDR disclosures completed the same task in 3–4 days using the new compliance module.
The data provenance feature addressed the trust gap directly. Qualitative feedback from follow-up interviews described the platform as "finally feeling reliable" and "the first tool where we actually trust the output enough to put it in a board deck."
"The hardest design problem wasn't the complexity. It was convincing stakeholders that less information, shown better, would drive more confident decisions."
Personal reflection on the project
