Service Pillar 04 of 06

Cloud architectures and CRM integrations that ship — without the multi-year migration scar tissue.

GCP-native systems, large-scale Salesforce integrations, multi-region migrations. We've moved petabyte-class data warehouses without an outage, integrated Salesforce with billing and core systems at telecom scale, and stood up greenfield GCP landing zones for regulated industries.

What we do

Cloud and CRM aren't separate problems — they meet at integrations, identity, and data. We work the seam.

GCP-native architectures

Landing zones, organization-policy hierarchies, VPC Service Controls, Workload Identity Federation. Built for regulated industries — HIPAA workloads, PCI-scope segmentation, audit logging from day one.

Salesforce integrations

API-led integrations with core banking, billing, ERP, EHR. Apex / LWC where it earns its keep, MuleSoft / Workato when it doesn't. Identity federation, SSO, governance models that survive a re-org.

Cloud migrations

Lift-and-shift, re-platform, re-architect. We pick the right strategy per workload — not a one-size-fits-all corporate decree. Wave planning, parallel run, instant rollback at every step.

Data platform engineering

BigQuery / Snowflake warehouse design. dbt for transformations. Airflow / Dagster for orchestration. Streaming via Pub/Sub or Kafka. Cost-aware partitioning that doesn't surprise you on the next bill.

FinOps & cloud cost engineering

Tagging discipline, commitment / savings-plan strategy, idle-resource hunting, rightsizing automation. Most large clouds have 20-40% wasted spend; we find it and recover it without slowing the team.

Multi-cloud where it earns its keep

AWS for compute breadth, GCP for data, Azure for Microsoft estate. We don't push multi-cloud as a default — but we do design for portability where regulatory or commercial concerns demand it.

How an engagement runs

Four phases. Migrations are where good projects go to die — we run them so they don't.

PHASE 01

Assess

Workload inventory, dependency mapping, cost baseline, regulatory perimeter. We tell you which workloads should move, which should stay, and which should be retired.

PHASE 02

Design

Target architecture per workload type. Wave plan with rollback at every step. Cost projections grounded in actual usage data, not vendor calculator screenshots.

PHASE 03

Migrate

Wave-by-wave execution with parallel run on every cutover. Your team in the room. We don't black-box the migration — your engineers learn the new platform by doing the work.

PHASE 04

Operate

30/60/90-day operate-with. FinOps practice in place. Cost dashboards, SLO definitions, on-call rotations. By day 91 your team owns it.

Technologies in our daily kit

The cloud and CRM stack we ship to regulated production every week.

GCP
AWS
Azure
BigQuery
Snowflake
Databricks
Pub/Sub
Kafka
Kinesis
Cloud Run
GKE
Cloud Functions
Salesforce
Apex / LWC
MuleSoft
Workato
Airflow
Dagster
dbt
Terraform
Pulumi
Anthos
Identity-Aware Proxy

Selected work

Three representative engagements. Names anonymized.

FinanceGCPMulti-region

On-prem-to-GCP data warehouse migration — global asset manager

Problem
12 PB Teradata warehouse approaching end-of-life support. Quarterly close jobs running 18+ hours. Three regional clones with diverging schemas — analytics teams spent more time reconciling than analyzing.
Approach
BigQuery target with consolidated multi-region dataset. dbt transformations replacing legacy stored procedures. Wave plan: lowest-risk reporting first, then analytics, finally operational reads. Parallel run for 90 days per wave with bit-exact result validation.
Outcome
Quarterly close 18hr → 3hr. Cost down 41% on equivalent compute. Schema convergence eliminated 60% of analyst reconciliation time. Migration completed without a single rollback.
HealthcareSalesforceEHR

Salesforce ↔ EHR integration — multi-state hospital network

Problem
Patient experience team running on Salesforce; clinical operations on Epic. No reliable integration. Patient outreach campaigns going to deceased patients, missed appointment risk-scoring blind to upcoming procedures.
Approach
MuleSoft as the integration spine. Bi-directional sync with conflict resolution rules vetted by clinical leads. PHI flow restricted via tokenization at the boundary. SSO via Workload Identity Federation. Audit logging on every patient-record touch.
Outcome
Outreach errors 4.2% → 0.1%. Risk-scoring now factors EHR-side data. HIPAA audit cleared with the integration as a documented control. Salesforce data quality is now the source of truth for cross-functional reporting.
TelecomCRMFinOps

Salesforce-driven contract lifecycle for B2B telecom — Tier-1 carrier

Problem
Enterprise sales cycle averaging 9 months. Quote-to-cash flow involved 7 systems and 3 spreadsheets. Custom Salesforce build had grown into 1.2M lines of Apex with no test coverage. Cloud spend on integration servers untracked.
Approach
Refactor strategy: replace mid-tier Apex with platform events + lightweight integration services. CPQ + DocuSign integration for quote generation. Cost tagging across the integration estate. Test pyramid established with 1,200+ Apex tests written before any refactor began.
Outcome
Sales cycle 9mo → 6mo. Quote-to-signature dropped from 12 days to 36 hours for standard configurations. Apex codebase down 38%. Annual integration cloud spend reduced by $2.4M after FinOps pass.

Cloud or CRM project that's stalled?

30-minute call with a senior architect. We'll tell you what's actually salvageable, what should be rebuilt, and which path is cheapest.