API Automation & Integration Services
We build industrial-grade middleware and data pipelines that connect your favorite platforms. Zero manual work, 100% precision.
We build industrial-grade middleware and data pipelines that connect your favorite platforms. Zero manual work, 100% precision.
Bridge the gap between incompatible legacy systems and modern SaaS APIs with bespoke translation layers.
High-frequency data extraction, transformation, and loading (ETL) between your production databases and analytics tools.
Event-driven architecture that listens for triggers from Stripe, Shopify, or GitHub to execute immediate business logic.
Deployment of a single endpoint fetch or basic data post script.
Recurring synchronization with advanced logging, error handling, and auto-retries.
Multi-platform ecosystem with OAuth2 flow, filtering logic, and custom alerts.
Modern businesses operate across dozens of disconnected SaaS platforms. Layerbit engineers custom middleware solutions designed to eliminate manual data entry, reduce human error, and synchronize your data ecosystems in real-time using robust REST and GraphQL protocols.
Automatically synchronize inventory levels, order statuses, and customer data across Shopify, WooCommerce, ERP systems, and CRM platforms like Salesforce or HubSpot without manual CSV uploads.
Capture secure webhook payloads from payment gateways like Stripe or PayPal. We build custom listener endpoints that validate cryptographic signatures before triggering automated invoicing or subscription provisioning.
Consolidate error logs and system health metrics from scattered cloud infrastructure into a unified dashboard, or route critical system failures directly to automated Slack or Microsoft Teams alert channels.
Our automation pipelines are built with resilience in mind. We implement intelligent request queuing, token bucket algorithms to respect external rate limits (like 429 Too Many Requests), and exponential backoff protocols. If a third-party server goes down, your data is held safely in a dead-letter queue until the connection is restored.
We engineer integrations using industry-standard security protocols. Depending on the external API requirements, we can implement OAuth 2.0 flows, secure JWT (JSON Web Token) generation, rotating Bearer tokens, API key header injection, or Mutual TLS (mTLS) for high-security financial endpoints.
Layerbit utilizes a "pass-through" middleware architecture for standard integrations. This means we ingest, transform, and forward your payload in memory without permanently storing your sensitive database records on our servers, ensuring strict compliance with data privacy standards.
Connecting two systems is usually a day's work. Keeping them connected for two years is the actual engineering, and almost all of it is about what happens when something fails halfway. These are the properties we build in from the start, because retrofitting them means reprocessing history.
Every retry must be safe to repeat. If a request times out after the remote system committed it, a naive retry creates a duplicate order or a second charge. Idempotency keys — a stable client-generated identifier the receiver deduplicates on — are the difference between "retry safely" and "reconcile manually".
Retrying immediately turns a brief outage into a self-inflicted denial of service. Exponential backoff with jitter spreads the load, and a circuit breaker stops hammering a system that is clearly down. A dead-letter queue keeps the messages that exhausted their attempts, so nothing is lost silently.
Webhooks are efficient and arrive out of order, more than once, and sometimes not at all. Polling is wasteful and predictable. Most robust designs use webhooks for latency plus a periodic reconciliation sweep to catch what was missed — because assuming delivery is how gaps appear.
Limits shape the architecture, not just the error handling. A nightly sync of 50,000 records against a 100-requests-per-minute endpoint takes over eight hours — which either needs batching, a different endpoint, or a different schedule. Better to discover that during design than during the first month-end.
Credentials belong in a secrets manager with a documented rotation path, never in source, environment files committed by accident, or a CI variable nobody can audit. OAuth refresh flows need to handle expiry without human intervention, because they will expire at an inconvenient hour.
"The sync is broken" should be answerable in a minute. That needs structured logs with a correlation identifier flowing through every hop, a record of what was processed and when, and an alert on the condition that matters — a queue that stopped draining, not merely an error rate.
In our experience the failures cluster in a few predictable places, and none of them are the API call itself:
To scope work accurately we need to know: which systems, and whether you have working API credentials for each; the direction and frequency of the flow; the volume, both typical and at peak; what "correct" looks like, so we can verify it; and what should happen when the remote system is unavailable — queue and retry, or fail loudly. If any of those are undecided, that is fine and worth saying — the answers usually shape the design more than the technology does.