Findings

Two decades of operational data for a portfolio of major venues sat siloed across disconnected legacy systems. Leadership had no cross-venue view of P&L, budget, or attendance — every report was assembled by hand.

Recommendation

Consolidated the full historical dataset into a governed Microsoft Fabric Lakehouse, built automated ETL pipelines to structure it, then layered Power BI dashboards on top with a data-governance model for long-term auditability.

Findings

Flight schedules, passenger loads, cargo, fuel, and revenue lived in disconnected systems. Pricing and routing decisions were made reactively from stale summaries, and different teams reported conflicting numbers.

Recommendation

Built a purpose-made predictive analytics platform: unified every data source into one reporting layer, trained ML forecasting models for demand and revenue by route, and shipped dynamic-pricing tools plus real-time executive dashboards.

Findings

Borrowers, brokers, and administrators each needed a fundamentally different workflow. Without a shared platform, every handoff between them was manual, pricing models were static, and compliance oversight didn't scale.

Recommendation

Architected a single AI-powered SaaS platform with role-specific experiences for all three user types, plus an ML-driven pricing engine for dynamic loan recommendations — built on React, Node.js, Python, and Azure.

Findings

No existing technology foundation, in a price-sensitive market where real-time pricing decisions determine profitability — and no way to track inventory across events and channels in one place.

Recommendation

Delivered a complete full-stack platform from scratch: responsive web app, native iOS and Android apps, an ML pricing-inference engine reading live market signals, and a back-office portal for inventory and reporting.

Findings

Legacy listing tools were fragmented and slow, with no unified way to manage listings, buyer inquiries, and agent workflows — and search wasn't tuned to how local buyers actually look for property.

Recommendation

Built a full-stack web platform with geo-filtered search, an agent portal for listings and lead tracking, and buyer-facing tools for comparison and saved searches — mobile-first, with local market data integrated in.

Findings

A group of companies under one umbrella ran on outdated, inconsistent websites — different CMS platforms, different code stacks, no shared design system, so every update meant duplicated effort across teams.

Recommendation

Built one shared design system and component library, then rebuilt each company site on a unified modern stack with a CMS non-technical staff could update directly — coordinating delivery across every brand in parallel.

Findings

Class booking ran entirely on phone and email — causing double-bookings and heavy administrative load — with no self-service way for members to view schedules, book classes, or manage their accounts.

Recommendation

Built a member-facing booking portal with real-time schedules and instant confirmation, an instructor dashboard for rosters and attendance, a studio admin panel for class and waitlist management, and integrated payments for packs and memberships.