API and System Integration for Business-Critical Data Flows
Integrations fail quietly until they fail loudly—at month-end, during promotions, or when finance discovers numbers that do not match the warehouse. My work is to make data movement boringly reliable: explicit contracts, error handling, retries, reconciliation and visibility when something drifts. That is the bar for business-critical platforms, not weekend scripts.
Who this is for
Organisations where CRM, ERP, commerce and logistics must agree—growing SMEs through to enterprises with legacy constraints. Stakeholders are typically COOs, CTOs and heads of digital who cannot afford revenue leakage or compliance gaps. Engagements match integration depth: structured discovery and delivery, scaling with how many systems and failure modes are in scope.
Problems I solve
- Duplicate and conflicting records across systems—customers, orders and stock telling different stories.
- Brittle point-to-point scripts owned by one person; nobody dares change them.
- No monitoring: failures discovered by customers, not dashboards.
- Weak governance: scattered secrets, unclear ownership of master data, no audit trail when something breaks.
How I work
System map first: sources of truth, sync direction, latency tolerance and failure modes. Then patterns—events, batches, APIs—with idempotency and dead-letter discipline. Implementation ships with tests where they matter and observability everywhere money or operations touch the pipe.
Typical results
- Fewer manual reconciliations and faster confidence at close.
- Safer releases: you know when a connector degrades before it hits revenue.
- Documentation and runbooks so internal teams are not hostage to opaque glue code.
Integration architecture under pressure
Peak traffic and batch windows expose naive designs. I design for partial failure: retries with backoff, circuit breakers where appropriate, and reconciliation jobs that repair drift instead of hiding it. “Exactly-once” is treated pragmatically—often achieved by business keys and idempotent writes rather than slogans.
CRM, ERP and commerce in real operations
Orders, stock, invoicing and customer records must follow one coherent narrative. B2B scenarios add price lists, thresholds and payment terms—rules that belong in code and configuration, not in spreadsheets. For marketing stacks (HubSpot and peers), mapping is GDPR-aware: properties, lifecycle stages and consent land where sales and operations can trust them.
Legacy systems without magical thinking
Legacy does not disappear because a slide says “digital transformation”. I respect constraints: phased migrations, strangler patterns where useful, and clear interfaces so modern services do not multiply hidden dependencies. The goal is reduced operational risk, not a big-bang rewrite your business cannot absorb.
Low-code versus code—chosen on risk
Make, Zapier and similar tools are excellent for fast experiments and non-critical workflows. When volume, cardinality or financial impact grows, critical flows move to services you can test, monitor and version. The decision is always explicit: speed versus control, documented with you—not a default.
What the service includes
- System and data mapping: master entities, sync rules, conflict resolution
- API connectors toward CRM, ERP, commerce and logistics stacks
- Async processing, retries, dead-letter queues and structured logging
- Workflow automation where low-code fits; extraction to code when risk demands it
- Monitoring hooks and operational dashboards for integration health
- Documentation and handover for internal IT or partners
Stack and technologies
Why Marco Chirico
Twenty years and 150+ projects include integrations that “worked on Monday” and broke under Black Friday load. I prioritise stability and observability before feature sprawl. If you need API and system integration without surprises, bring your stack and failure stories—discovery starts from reality.
FAQ
Low-code tools or custom services?
Both, chosen by risk and volume. Non-critical paths can stay in low-code; revenue-critical flows get code, tests and monitoring.
How do you handle SAP or complex ERPs?
Depends on exposed modules and APIs. Discovery defines phases and rollback—incremental delivery, not guesswork.
What project scale do you support?
From focused integration initiatives to broader multi-system programmes—scoped after discovery, with phases and governance matched to your stack and risk.
How is data quality enforced?
Stable keys, merge rules, cross-checks and anomaly dashboards—so drift becomes visible before it becomes a board issue.
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