Connecting CRMs, ERPs, payment processors, and custom platforms into unified workflows. Enterprise systems integration, AI-powered integration solutions, data integration. The unglamorous engineering that turns a collection of systems into something your business actually runs on.
Our expertise
CRM, ERP, payment, custom integrations.
Most businesses do not have one system. They have a graph of them. Integration engineering is the work of making that graph behave like a coherent system, not a constellation of silos.
01 · CRM integrations
Salesforce, HubSpot, Pipedrive, Zoho.
Bidirectional sync between your operational systems and your CRM. Lead routing, opportunity tracking, custom object models. Integration that respects the CRM's data model rather than fighting it.
02 · ERP integrations
NetSuite, SAP, Microsoft Dynamics, custom.
Order management, inventory, financial sync. ERP integrations that scale to enterprise data volumes. Custom field mapping, audit trails, error handling.
03 · Payment integrations
Stripe, custom processors, multi-currency.
Payment processor integration including custom processors when off-the-shelf does not fit. Multi-currency, multi-region, settlement reconciliation, dispute handling.
04 · AI-powered integrations
Intelligent routing, automated mapping.
AI to handle the messy parts of integration: data mapping suggestions, anomaly detection, intelligent retry logic. Tools that learn from past integrations, not just rule-based plumbing.
Capabilities
Patterns, observability, error handling, scale.
Integration is mostly about handling failure modes. The patterns that work at scale and the observability that lets you sleep at night.
Integration patterns
Event-driven, batch, real-time, hybrid.
Event-driven where freshness matters. Batch where volume matters. Real-time when both. Hybrid when reality demands it. Pattern chosen for the use case, not for fashion.
Per-integration health dashboards. Error tracking with payload context. Retry visibility so you know which jobs are stuck. Alerting that fires on real failures, not noise.
Idempotency & retries
At-least-once delivery, exactly-once processing.
Idempotent receivers so duplicate deliveries do not corrupt data. Retry policies with exponential backoff. Dead-letter queues for messages that cannot be processed.
Audit & compliance
Tamper-resistant audit logs, change tracking.
Audit logs of every data change across systems. Change tracking for compliance frameworks. Reconciliation reports for finance teams.
How we work
Four phases. Same team across all four.
The phases that apply to every engagement, not just systems integration. The team that scopes does the building, and the operating.
Phase 01 · 2–4 weeks
Discovery and scope.
Stakeholder interviews, technical review of existing systems, risk register, written scope with milestones and exit criteria.
Phase 02 · 3–12 months
Build and iterate.
Two-week sprints with working demos. Senior leads on every sprint review. Code reviewed, accessibility checked.
Phase 03 · 2–6 weeks
Cutover and stabilization.
Parallel run with rollback path. On-call coverage during the launch window. Stabilization continues until incident rate trends to zero.
Phase 04 · ongoing
Operate and evolve.
Multi-year retainer with the same team that built the product. Monthly check-ins, quarterly business reviews.
Common questions on systems integration engagements.
What integration patterns do you use?
Event-driven (Kafka, EventBridge, custom message buses) when freshness matters. Batch (nightly ETL) when volume dominates. Real-time API calls when both. We pick the pattern for the use case, not the fashion.
How do you handle integration failures?
Idempotent receivers, exponential backoff retries, dead-letter queues for failures we cannot process automatically, alerting that fires on real failures (not noise). Failure handling is most of the integration work.
Can you integrate with custom or legacy systems?
Yes. Most enterprise integrations include at least one legacy or custom system. Mainframe, ColdFusion, custom APIs without documentation. We do the code archeology to understand them before integrating.
What about observability?
Per-integration health dashboards, error rate tracking, retry visibility, payload-context error capture. You should know which integrations are healthy and which are degraded without paging engineers.
Do you handle data migration during integration projects?
Yes. Most integration engagements include backfill or initial data migration alongside ongoing sync. We design the backfill, the cutover, and the steady-state pattern as one engagement, not three.
Ready to build?
Pick a path forward.
Multiple ways to start: schedule a discovery call, run our cost calculator for a budget bracket, or use the contact form for a written response.