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Platform Implementations

Implementations led by engineers who built these platforms.

Manifesto

Most enterprise platform implementations are done by certified consultants who learned the platform from a training course. The work passes the first wave of requirements, then breaks on the second wave: the integration the platform officially doesn't support, the data model that needs to bend without snapping, the audit log the off-the-shelf module doesn't produce.

We staff implementations with engineers whose CV includes the platform itself, or systems at the same architectural class. Salesforce engineers who shipped on the App Cloud team. Snowflake people who understood the query optimizer, not just the SQL surface. ServiceNow engineers who could navigate the underlying Glide stack, not only the Form Designer. HANA people from the in-memory engine itself.

The first wave any certified consultant can deliver. The second wave is what justifies a studio. That second wave is the only line of work we take on here.

The pillars
/ 01

Salesforce

Sales Cloud, Service Cloud, custom Apex. Implementation work that respects the platform's declarative-first design while reaching into Apex for what the declarative tools genuinely cannot do. Governor-limit-aware batch jobs, async patterns done correctly, scoped namespaces that don't poison the org.

  • Apex
  • LWC
  • SOQL
  • Async patterns
/ 02

Snowflake

Warehouse architecture that respects micro-partitioning, virtual-warehouse sizing that doesn't burn credits, role hierarchies that pass governance audits, row-level security that actually scales. Data sharing without the leak surface that usually comes with it.

  • dbt
  • Snowpipe
  • RBAC
  • Dynamic masking
/ 03

ServiceNow

Workflow implementations that survive process drift. Scoped applications that don't pollute the global namespace. Integrations through IntegrationHub that don't break on platform upgrades. Automated test framework that actually runs in CI, not as theatre before quarterly release.

  • Flow Designer
  • Scoped apps
  • IntegrationHub
  • ATF
/ 04

SAP HANA

Data models that exploit columnar storage where it helps and don't fight it where it doesn't. Calculation views that perform under enterprise load. SQLScript that is auditable, testable, and source-controlled rather than buried in transport layers.

  • Calculation views
  • CDS
  • SQLScript
  • XSA
/ 05

Cross-platform integration

Most engagements are not single-platform. Salesforce talking to Snowflake, ServiceNow consuming SAP master data, HANA feeding analytics back into Salesforce dashboards. The integration layer is where most implementations leak; we treat it as a first-class engineering surface, not connector glue.

  • MuleSoft
  • Kafka
  • iPaaS
  • Reverse ETL

What we ship

  • Salesforce, sales cloud, service cloud, custom apex
  • Snowflake, data platform, warehousing, governance
  • ServiceNow, ITSM, case management workflows
  • SAP HANA, in-memory data and analytics

Stack

Salesforce · Snowflake
ServiceNow · SAP HANA

Posture

41
Implementations · across 23 enterprises
12
Principals · platform-author backgrounds
100%
Audit-pass · regulated-vertical engagements
0
Governor-limit failures · Salesforce work
Monitoring active

Certifications · on bench

  • Salesforce Certified System Architect
  • SnowPro Advanced Architect
  • ServiceNow CSA + CAS
  • SAP HANA Solution Architect
  • MuleSoft Integration Architect
  • AWS Solutions Architect (Pro)

Implementation domains

  • Financial services · SOX, SEC, FINRA
  • Healthcare · HIPAA, HITRUST
  • Public sector · FedRAMP, StateRAMP
  • Telecom · CALEA, lawful intercept
  • Critical infrastructure · NERC CIP
Engagement · redacted sample

Engagement with Global fintech, full Sales Cloud migration from legacy Oracle CRM across 14 markets. 1,200 sales seats, 7 international entities, zero data loss; quote-to-cash cycle compressed by 38%.

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