Integration & API Services
The same record in both systems
An order, a customer, or an invoice is the same record on both sides. A repeat of the same update does not create a second record. You see a mismatch before the close, while it can still be fixed.
Examples
The engineering problem, in a few shapes. A retry, and a close that has to match.
- Sync pipelines between ERP, CRM, and spreadsheets. Idempotent writes, so retries never duplicate records and the two sides stay in agreement even after a failure.
- Data pipelines with observability built in. Pull from one system, apply the transformations you need, push to another, and see logs at every step so you know what went through and what failed.
- Scheduled reconciliation jobs. They catch drift between systems before month-end and either fix it automatically or flag it for someone to review.
Technologies
Integration work lives or dies on observability and retry semantics. The stack we reach for reflects that: transport that has been tested in production, clear authentication, and databases that match your actual data shape.
- APIs. REST and GraphQL for most work, plus gRPC when latency matters.
- Authentication. OAuth2 for user-context access, and JWT for service tokens.
- Orchestration. Zapier and Make when the volume is low and the logic is simple, custom middleware when it is not.
- Databases. PostgreSQL, MySQL, MongoDB, and Redis, chosen based on your data model rather than on preference.
How we'd work on this
A technical situation
A retry writes a second order. The two systems disagree, and the close is the first time anyone sees it.
How we'd approach it
We map the fields that have to match, build a one-way sync that does not duplicate rows, and add a log and an alert before the close. The fix ships in 1 to 3 weeks.
What you'd get
You leave with that sync running on your orders, the code in a repo you own.
Questions about integrations and APIs
Every sync uses idempotent writes. Each record has a stable key on both sides, so the same event applied twice produces the same result. Network retries become noise, not duplicates.
Per-step observability. Structured logs at every transformation, success and failure metrics per endpoint, alerts when the error rate drifts. Without that, an integration is a black box that seems fine until the day it is not.
The usual platforms: Salesforce, HubSpot, SAP, Oracle NetSuite, Microsoft Dynamics, Jira, Zendesk, Shopify, Stripe, QuickBooks, Google Workspace, Microsoft 365, and most ERPs and CRMs that expose an API. Where a REST or SOAP API exists, we use it. Where no API is exposed, we fall back to file extraction, SFTP drops, or browser automation.
What you get
- A working fix on your data
- You keep the code
- 2 to 5 weeks when the owner and the files are available
Let's talk about your case
Talk to the Lab
Tell us the problem in a few lines. What the team does today, and where it breaks. We reply the same business day.
What happens next
- We reply the same business day
- Diagnostic in 3-5 days
- Working fix in 1-3 weeks. Technical plan in the last days, with the work done.
Start here