Architecture first. Pipes second.
Most integration work fails not because the technology is hard, but because nobody owns the architecture. We design, build, and run the data and integration layer so your systems work as one, not as a collection of point-to-point patches.
Engineers who own the architecture, not just the pipes.
Three things that set our Data & Integrations practice apart.
“Integrations look like plumbing until the day a vendor changes their API contract and three downstream systems go down at once. We design for that day before it shows up.”
Salesforce ↔ everything else is the day job
We own the Salesforce-to-rest-of-stack work most consultancies fumble. ERP, finance, product telemetry, support tools, identity, industry-specific stacks. Ten years of getting that boundary right. See Custom Solution Development for the wider platform work that often lives alongside.
Multi-cloud, by default
AWS, Azure, and GCP under the same pod. We pick the right tool for the workload, not the one your last vendor knew. No procurement gymnastics. Same engineers, multiple clouds.
We run it in production
We don't just design the architecture. We build it, ship it, and operate it. SLA-backed sustaining, observability baked in, on-call rotations for the pipelines that can't fail at 3am. Architecture decisions hold up because we're the ones living with them.
Multi-cloud, by default.
Salesforce is the application and agent layer. AWS, Azure, and GCP are the infrastructure underneath. We work across all of them.
A multi-tenant application hyperscaler platform stack with Core, Data Cloud, Agentforce, MuleSoft, Tableau, Slack, Commerce, and the Industry Clouds. The strategic layer: system of record, system of engagement, and system of intelligence.
Lambda, Step Functions, S3, Redshift, Glue, EventBridge, and the full serverless data stack.
Azure Functions, Data Factory, Synapse, Event Hubs, Cosmos DB, and Power Platform connectors.
BigQuery, Dataflow, Pub/Sub, Cloud Functions, Vertex AI, and Looker analytics.
Where most integration projects die. Unless someone owns the arc.
We connect Salesforce to ERP, finance, product telemetry, support, identity, and industry stacks for a living. Five stages from discovery to sustain. We run the whole arc or join wherever you need us.
Discover
Stakeholder interviews, system inventory, data flow mapping, integration audit. What flows where, what's broken, what's missing.
- Stakeholder interviews and source-of-truth mapping
- System inventory across Salesforce, ERP, finance, support, telemetry
- Flow-by-flow integration audit
- Data quality and readiness assessment
- Quick-win identification
Architect
Domain models, service boundaries, event topology, identity, security. The shape settled before anyone picks an iPaaS.
- Domain modeling and canonical schemas
- Event topology and sync patterns (real-time, batch, CDC)
- Identity, access, and security models
- iPaaS / ESB / native-API selection
- Reference architecture and decision records
Build
Pipelines, connectors, event-driven backbones. AI-augmented engineering with automated tests on the flows the business depends on.
- Pipeline and connector implementation
- AI-augmented agile delivery
- Automated test coverage on critical flows
- Observability and error tracking baked in
- Contract testing across system boundaries
Cutover
Data migration, customer-zero rehearsals, rollback paths, change management. Sequenced so the business keeps shipping.
- Data migration and backfill
- Cutover rehearsals and dry runs
- Rollback paths and reconciliation
- Change management and user training
- Phased rollout across regions or teams
Sustain
SLA-backed sustaining, observability, incident response. Pipelines stay healthy through every Salesforce release and every system upgrade.
- SLA-backed Tier 3 sustaining
- Release-cycle regression coverage
- On-call rotations and incident response
- Performance, cost, and throughput optimization
- Clean handoff to your team when it's time
Six capability areas. One engineering bar.
The data and integration layer covers more than the Salesforce boundary. Six areas with the same depth: architecture, engineering, AI, protection, continuity, and the Salesforce connections everything else depends on.
Integration architecture
API design, event-driven patterns, iPaaS orchestration, and reusable integration assets. The patterns that keep systems talking to each other when something upstream changes.
RESTful and GraphQL API design, versioning strategy, contract testing, and documentation.
Pub/sub, event sourcing, CQRS patterns, and asynchronous processing architectures.
MuleSoft, Workato, Boomi, and legacy ESB modernization to cloud-native patterns.
API-led connectivity layers, shared libraries, schema registries, and integration templates.
Data engineering & analytics
Streaming pipelines, lakehouse architecture, data warehousing, and semantic layers. We turn raw data into something your business can act on.
Kafka, Kinesis, Pub/Sub, and Change Data Capture for real-time data movement and enrichment.
Delta Lake, Iceberg, and unified storage layers that combine warehouse performance with lake flexibility.
Snowflake, Redshift, BigQuery, and Synapse: schema design, ETL/ELT, and query optimization.
Metrics layers, reverse ETL, data products, and activation pipelines to operational systems.
AI & agent infrastructure
Retrieval-augmented generation, vector databases, evaluation frameworks, and model gateway patterns. The plumbing that makes AI agents reliable in production. Customer-facing agents shipped as products live on Product Development; internal agents pointed at your own team live on Custom Solution Development.
Embedding pipelines, vector stores (Pinecone, Weaviate, pgvector), and chunking strategies.
LLM evaluation harnesses, drift detection, cost tracking, and prompt versioning.
Multi-model routing, fallback chains, rate limiting, and provider abstraction layers.
Tool-use patterns, function calling schemas, sandboxed execution, and human-in-the-loop triggers.
Data protection
Classification, lineage, encryption, access governance, and privacy compliance. Data your teams can use because they trust how it's protected. Application-level controls and security review prep live on Application Security.
Automated data classification, lineage mapping, impact analysis, and data catalog management.
At-rest and in-transit encryption, KMS integration, key rotation, and secrets management.
Role-based access, attribute-based policies, data masking, and audit trail implementation.
GDPR, CCPA, HIPAA data handling, consent management, and right-to-deletion workflows.
Business continuity & DR
Backup, disaster recovery architecture, runbooks, and failover automation. When things go wrong, recovery should be a process, not a panic.
Automated backup schedules, point-in-time recovery, cross-region replication, and validation testing.
Active-passive, active-active, and pilot light patterns across cloud regions and providers.
Documented recovery procedures, tabletop exercises, and scheduled failover drills.
Health checks, automated failover triggers, DNS switching, and recovery time validation.
Salesforce ↔ everything else
The integration patterns that connect Salesforce to ERP, product telemetry, support tools, and industry-specific systems. This is where most integration projects stall, and where we live.
NetSuite, SAP, Oracle: order sync, invoice reconciliation, and master data harmonization.
Usage data from your product into Salesforce for health scoring, expansion signals, and churn prediction.
Jira, Slack, Zendesk, Confluence: bidirectional sync for case escalation and team coordination.
Industry-specific systems: hospitality (PMS, CRS, POS), restaurant tech, financial services. Plug into the operational stack your customers run on.
Enterprise integrations across industries.
A sample of the integrations and data platforms we've built, modernized, or kept running. We name engagements only with our partners' consent.
The integration layer is where projects die.
Unless somebody owns it. We'll own yours: architecture, build, and the operate phase after.