Technology & Infrastructure Evolution

Provides unified financial visibility and optimization across hybrid environments spanning public cloud, private cloud, colocation, and edge. Normalizes cost models across environments with different billing paradigms.

Models the total cost of ownership for mainframe and legacy system modernization, including migration economics, strangler-fig patterns, and hybrid coexistence strategies. Provides financial justification frameworks for modernization decisions.

Manages the unique financial characteristics of AI/ML workloads - GPU economics, training vs. inference cost profiles, model serving optimization, and LLM token economics. Enables responsible AI adoption with financial guardrails.

Evaluates and redesigns application architectures - serverless, containerized, microservices, event-driven - from a cost-efficiency perspective. Provides architecture decision records (ADRs) that include financial impact analysis.

Integrates carbon accounting, energy efficiency metrics, and sustainability targets into infrastructure financial decisions. Maps spending to carbon footprint and enables cost-carbon co-optimization across the technology estate.

Assesses the financial implications of emerging technologies - quantum computing, edge AI, spatial computing, and blockchain - to prepare cost models and governance frameworks before mainstream adoption.

Optimizes the cost of data platforms - data lakes, warehouses, streaming pipelines, and analytics workloads - balancing storage tiering, compute scaling, and query optimization against data freshness and accessibility requirements.

Manages the financial lifecycle of physical infrastructure - data centers, network equipment, and hardware assets - including depreciation, refresh cycles, capacity planning, and decommissioning economics in hybrid environments.