Case Studies
Real engagements across enterprise AI, analytics, and automation — each anchored in a business problem and closed with quantified impact.
Problem: Enterprise sales teams lacked a standardized, defensible way to quantify solution value.
Approach: Designed standardized ROI frameworks (TCO, NPV, IRR) with parameterized industry benchmarking, sensitivity analysis, and governance controls.
Outcome: Reusable value-engineering assets deployed across multiple enterprise engagements with 40% fewer recalculation errors.
Impact: +20% estimate accuracy · +10% average deal size.
Problem: Enterprise buyers needed AI integrated into existing BI environments without disrupting Tableau and Power BI workflows.
Approach: Consultative discovery across 7 strategic deals, architecting LLM-driven intelligence over existing analytics stacks with fault-tolerant runbooks.
Outcome: Reduced solution turnaround by ~40% and workflow downtime by 80%.
Impact: +25% customer time-to-value · 3x engagement capacity.
Problem: Product and GTM leaders needed data-backed clarity on user challenges hidden inside large-scale behavioral datasets.
Approach: Led consultative research initiatives, translating diagnostics into executive-ready narratives and KPI frameworks.
Outcome: Influenced 25 product roadmap and GTM decisions; reporting cycles shortened by 35%.
Impact: 25 roadmap decisions · 35% faster reporting.
Problem: Manual financial close consumed dozens of hours monthly and produced recurring errors.
Approach: Built financial models, ROI frameworks, and automated forecasting with variance analysis and QA controls.
Outcome: 27 hours/month reclaimed; 60% fewer reporting errors.
Impact: $120K annual cost reduction · 18% forecasting efficiency gain.
6+ Years · 100+ Engagements · 40% Faster Delivery · 95% Client Satisfaction.
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