The problem this solves
The CRM, the ERP, and the billing tool each hold a different version of the customer. Orders are retyped between systems, invoice status questions require logging into finance software, and month-end reconciliation is a recurring archaeology project. Every manual bridge is slow, error-prone, and completely dependent on the person who knows the routine.
How we work
We start with architecture, not connectors: which system owns which fact, an explicit source of truth per object and field, what flows where, in which direction, triggered by what. Skipping this step is why integrations turn into loops where systems overwrite each other, so we put it in writing first.
Then we build with the right tool per connection: native connectors where solid ones exist, Make or n8n for flows that need logic without a codebase, custom Node or Python services where volume or transformation demands them. We know the Polish stack from production work, Symfonia, Comarch, Baselinker, Magento, KSeF, Fakturownia, alongside Stripe and the international layer. On one B2B distribution engagement we kept HubSpot, Magento, and a Polish ERP in sync for a heavily regulated industry, with regulatory fields enforced at the workflow layer.
Everything ships production-grade: idempotency keys on writes, exponential backoff on transient failures, rate limit management, alerting plus a runbook. Integrations that survive, not integrations that demo.
Deliverables
- Integration architecture: source of truth per object and field
- Built connections: native, Make or n8n, or custom services per scope
- Data transformation and mapping with documented rules
- Idempotent writes, retries, and rate limit management
- Monitoring, alerting, and a failure runbook
- Architecture documentation for your team or IT partner
What buyers ask before scoping.
Middleware like Make and n8n, or custom code - which will our integration need?
Middleware covers most mid-volume flows with transformation needs and keeps maintenance accessible to non-developers. Custom Node or Python takes over when volume, complex mapping, or an awkward API makes visual tools fragile. We often mix both in one architecture and document why each connection got its tool.
How do you deal with HubSpot API rate limits in integrations?
We throttle ahead of the limit rather than crash into it, our integrators pace themselves against a share of available request capacity and back off exponentially on transient errors. That practice comes from real migrations where we hit the limits and learned HubSpot's unintuitive counter behavior firsthand, not from reading the docs.
Who maintains the integrations after go-live?
They are built to be maintainable by any competent team: documented architecture, runbooks, alerting that says what broke and where. Your IT can own them, or we keep them under a retainer, which most clients choose, because APIs change, volumes grow, and an integration nobody watches eventually becomes an incident.
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