If There Is No Connector, We Build One.
The Integration Gap That Standard Platforms Don't Fill
Every managed integration platform — Apigee X, Google Cloud Application Integration, Kong — ships with a library of pre-built connectors. Those connectors cover the most common enterprise applications. They don't cover the ERP system that was customized so heavily it no longer resembles the vendor's standard API. They don't cover the legacy application that communicates via flat files dropped to an SFTP server. They don't cover the vendor portal that has a web interface but no documented API. They don't cover the mainframe system that exposes data through a proprietary binary protocol.
These are integration gaps — and they exist in every enterprise system landscape. Custom integration work fills the gaps that standard platforms can't reach.
What We Build
Custom REST and SOAP Connectors
For systems with documented or discoverable APIs that don't have a managed connector, we build purpose-built connector components: authentication handling, request formatting, response parsing, error classification, and retry logic. These connectors are built to be maintainable — not one-off scripts that only the original developer can read.
Webhook Handlers
Receiving and processing inbound webhooks from third-party systems: payload validation, signature verification (HMAC-SHA256 or platform-specific schemes), idempotency handling, and routing to downstream systems or queues. Deployed on Cloud Run or Cloud Functions for serverless operation.
File-Based Integration Pipelines
For systems that still exchange data via flat files — CSV, XML, fixed-width, EDI — we build automated pipelines: SFTP polling, file format validation, transformation and mapping, loading to target systems (database, API, BigQuery), and archival with audit trail. These are common in finance, logistics, and manufacturing integrations.
Event Bridge Components
Connecting event-producing systems to event-consuming systems when there is no native event channel between them: polling-based change detection, database trigger-based CDC (Change Data Capture), or API-polling with deduplication — forwarding events to Pub/Sub, a message queue, or directly to consuming services.
Database Integration
Direct database-level integration for systems that expose no API: read-only query-based extraction with scheduled refresh, or CDC-based streaming integration using database transaction logs. Used for reporting integrations, data warehouse pipelines, and legacy application monitoring scenarios.
- Custom REST connector development with auth, error handling, and retry logic
- SOAP/WSDL adapter development for legacy enterprise systems
- Webhook handler development: payload validation, signature verification, idempotency
- SFTP-based file pipeline: polling, validation, transformation, loading
- CSV, XML, and fixed-width file format parsing and transformation
- Database-level CDC integration using transaction logs
- Event bridge components: polling-based change detection and event forwarding
- Pub/Sub integration for event-driven pipeline delivery
- Cloud Run and Cloud Functions deployment for serverless connector hosting
- Integration audit trail and monitoring for custom connector operations
How we deliver this service.
System Discovery
We document the target system's integration surface: what API or data access methods exist, what authentication it supports, what the data model looks like, and what the volume and frequency requirements are. No design begins without this.
Connector Architecture
Design document for the custom connector: authentication flow, request/response structure, error classification scheme, retry policy, and the hosting model (Cloud Run, Cloud Functions, or embedded in the integration platform).
Development and Unit Testing
Connector built against the architecture document. Unit tests for authentication, happy-path data flow, and all documented error scenarios — including network timeouts, authentication failures, and malformed responses from the source system.
Integration Testing
End-to-end testing against the actual source system in a non-production environment. Volume testing to confirm the connector performs correctly at the expected throughput and frequency.
Production Deployment and Handover
Production deployment with monitoring configured, runbook written, and source code handed over to the team responsible for ongoing maintenance. Documentation covers the connector's design decisions — not just its operation.