Decades of legacy logic. Extracted, modernized, and made AI-ready - without stopping the business.
Most enterprise systems were built for stability within known boundaries. That design has held-until now. Growth today depends on how quickly systems can adapt to new channels, partners, and increasingly, machine-driven decisioning. We help enterprises extract, preserve, and transform decades of legacy logic into cloud-native, AI-ready systems making it safe to evolve without disruption.
What We Deliver
Six capabilities driving the modern cloud estate
Assess
Cloud Strategy & Readiness
Cloud readiness assessment across applications, infrastructure, data, and security
Application dependency mapping, technical debt assessment, and modernization prioritization
Workload classification and migration-wave planning based on business criticality
Target architecture design across public, private, hybrid, and multi-cloud environments
Cloud adoption roadmaps aligned to business priorities, cost considerations, risk, and investment plans
AI-ready cloud environments for deploying AI models, agents, and AI-powered applications
Secure integration of AI applications and agents with enterprise APIs, applications, data, and services
Agentic AI orchestration to automate defined, multi-step workflows across enterprise systems
Controlled agent access to enterprise tools and services through APIs and MCP, with human approvals and escalation
AI governance covering identity, security, data protection, evaluation, and human oversight
AI-Ready CloudAgentic AI OrchestrationMCP & API IntegrationEnterprise AI Governance
Proof, Not Promises
Cloud transformation highlights from our journey
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Travel & Hospitality
Retiring 200+ End-of-Life APIs Without a Single Booking Failure
A travel and hospitality company needed to migrate over 200 production APIs off end-of-life infrastructure onto Apigee X, with live guest bookings and scheduling running through every one of them. We mapped the full API inventory and dependency matrix first, then moved traffic through a progressive routing model across a multi-cloud target - GCP for API management, AWS for backend workloads - rather than a single cutover event.
100% of production APIs migrated to supported cloud environments
Zero booking or transaction interruptions
Board-approved multi-year decommissioning program secured
Originally delivered for a travel & hospitality corporation - the same pattern applies to any organization retiring end-of-life API infrastructure under live load.
Global Fintech
Migrating $3B+ in Annual Volume Off the Mainframe
As part of a $300M+ modernization program, a global fintech firm needed its mainframe revenue systems - powering over $3B in annual volume - moved to a cloud-native data fabric without breaking sub-second latency or global regulatory compliance. We built the target platform on GCP Composer, Dataflow, Spanner, BigQuery, and Pub/Sub, then sequenced the rollout across data fabric development, mainframe decommissioning, and regional expansion over a multi-year horizon.
$60M+ in cloud services delivered over 4+ years of continuous engineering
Sub-second B2B API response times, beyond legacy mainframe limits
Zero customer incidents across all production launches
Originally delivered for a global fintech leader - the same pattern applies to any organization retiring mainframe systems under strict latency and compliance constraints.
Energy
Building an AI-Ready IoT Platform for Real-Time Field Sensors
A major US energy corporation's on-premises infrastructure lacked the scale and GPU capacity to process real-time operational technology sensor streams at volume. We built GPU-accelerated GCP landing zones purpose-built for machine learning inference, deployed Vertex AI to ingest streaming machinery data, and engineered a secure integration layer bridging physical field assets to the cloud.
30% reduction in equipment downtime via predictive anomaly alerts
$10M+ in Google PSF funding secured to offset migration cost
Asset failure warnings 20–30 minutes ahead of field incidents
Originally delivered for a major US energy corporation - the same pattern applies to any organization building real-time OT-to-cloud pipelines for AI inference.
Global Fintech
Reverse-Engineering an Undocumented AS400 Estate Under an M&A Clock
A global fintech enterprise needed four mission-critical AS400 credit applications - with an undocumented RPG/COBOL codebase - moved to GCP under a compressed M&A and regulatory timeline. We reverse-engineered every system dependency through a structured matrix and sequence diagrams, converted the logic to Java, and built the target stack on Dataproc, BigQuery, and AlloyDB, running continuous engineering cycles across three time zones.
All 4 mission-critical applications migrated with zero downtime
99.99% field-level data match against the legacy AS400 base
Regulatory milestones hit on schedule despite late-stage scope increases
Originally delivered for a global fintech leader - the same pattern applies to any undocumented legacy estate moving to cloud under a deal-driven deadline.
