API development and integration services for reliable system interoperability.
Integration work is where good architecture becomes visible. The next team should be able to change one side without guessing about the other.
- Shared API contract
- One
- When retries happen
- No duplicates
- Every error
- Tracked
- Safe updates
- Versioned
Overview
What API Development & Integration has to solve.
A system handoff that fails silently or requires manual reconciliation. The useful questions are about ownership, failure paths, and what the team can operate after launch.
What good looks like
Every write is idempotent Failures are observable and retryable Consumers upgrade without a rewrite Contracts are tested on both sides Authentication and rate limits are explicit
The contract is the product
An API is finished when the errors are predictable, the writes are safe to retry, the authentication model is clear, and the consumer knows how to upgrade.
We start with consumers and failure modes. The contract is written and reviewed before implementation, and the same contract drives tests on both sides. That is what stops a small change on one team from becoming an outage on another.
- Explicit error semantics
- Idempotency for writes that matter
- Versioning and deprecation policy
- Consumer-driven contract tests
If it fails, you should know
Integration failures are rarely dramatic. A payload changes, a retry duplicates a record, or a partner rate limit starts returning 429. The system keeps running and the data quietly drifts.
We instrument the integration path end to end: request volume, latency, error rate, retry count, reconciliation gaps, and the age of the oldest queued item. Alerts are tied to the business outcome and to the health of the process.
- Tracing across systems
- Retry and dead-letter visibility
- Reconciliation dashboards
- Alerts tied to data freshness
What a useful integration brief should settle
An API or integration brief should name the consumers, the data they need, and the operations they must perform. It should also identify which existing systems are authoritative and which can only be read.
Authentication, rate limits, retries, idempotency, versioning, and error behaviour belong in the contract. Without them, every consumer invents a different recovery path.
- Consumers, operations, and expected access patterns
- Authentication, authorisation, and rate limits
- Retry, idempotency, and failure semantics
- Versioning and deprecation expectations
Why teams call us
What usually goes wrong.
These are the recurring problems behind a api development & integration brief. Naming them early changes the architecture, the estimate, and the launch plan.
The integration is a script
A cron job copies data between systems. It fails silently, duplicates records, and nobody knows until a customer complains.
Nobody owns the contract
One team changes a payload and another team breaks. The contract lacks a schema, a version history, and a consumer test.
Retries create duplicates
A timeout triggers a retry, and the downstream system treats it as a new write. The reconciliation is manual.
The failure is invisible
There are logs, but no one can answer which requests failed, what was retried, or whether the data arrived.
Scope
What the project includes.
Every api development & integration project is scoped around a working system and the decisions that keep it healthy.
API design and contracts
Resource model, schema, error semantics, pagination, versioning, and an OpenAPI or GraphQL contract consumers can trust.
Authentication and limiting
OAuth, API keys, scopes, rate limits, and the operational controls needed for partner and internal consumers.
Integration implementation
Third-party connections, webhooks, queues, transformations, and the retry model for each failure mode.
Idempotency and reconciliation
Idempotency keys, deduplication, replay-safe writes, and reconciliation reports for the data that matters.
Contract tests and monitoring
Consumer-driven tests, synthetic checks, tracing, and alerts tied to the integration path.
Developer documentation
Examples, sandbox access, error guides, and a changelog that helps consumers upgrade safely.
Use cases
Where this service helps most.
The same service looks different in each company. These are the situations where it matters most.
CRM and ERP disagree
Customer, order, and invoice data are copied by hand. Each system has a different source of truth and a different definition.
One owner per entity with observable sync
A partner API is becoming a product
External developers need documentation, sandbox access, rate limits, and a stable versioning policy.
A documented, versioned API with developer support
A migration needs a bridge
Two systems must run in parallel during a phased cutover.
A reconciliation layer that can be retired cleanly
Process
Four stages. Working software at every review.
Discovery leads to an architecture decision, a build with visible increments, and an operating model that stays after we leave.
What stays constant
One accountable lead, a working demo at each review, and documentation from the first release. Scope and risk set the plan, and we will say when a smaller project is the better answer.
- 01
Map consumers
Identify every consumer, the data it needs, and the failure it can tolerate. Agree the source of truth per entity.
Output: Consumer map, entity ownership, contract draft
- 02
Design contract
Define the schema, errors, auth, versioning, idempotency, and retry behavior before the first integration.
Output: API contract, auth model, test plan
- 03
Build and test
Implement the API and integrations with contract tests, failure injection, and monitoring.
Output: Production integration, tests, dashboards
- 04
Operate
Watch volume, latency, failures, and reconciliation. Version changes and communicate them to consumers.
Output: SLOs, changelog, support runbook
Stack & standards
Chosen for durability.
Fewer moving parts, clear ownership, and a handover your engineers can defend. The stack follows the constraint.
OpenAPI
Explicit REST contracts
GraphQL
Consumer-shaped queries where appropriate
Node.js
API and integration services
Redis
Rate limits, queues, and idempotency keys
OpenTelemetry
Tracing and failure visibility
Playwright
Contract and integration regression tests
How we choose
REST versus GraphQL
REST is usually simpler for stable resources and public APIs. GraphQL can be better when many consumers need different views of the same graph. We choose based on consumer needs.
Synchronous versus event-driven
Synchronous calls are easier to reason about but couple availability. Events are better for long-running or multi-consumer workflows. The failure model decides.
Point-to-point versus integration layer
A few integrations can be direct. As the number grows, an explicit integration layer with contracts and observability is usually cheaper to operate.
Measured outcomes
“They rebuilt the core without downtime. The close now runs from one reconciled ledger.”
FAQ
Questions we hear often.
The questions buyers ask before a api development & integration project. If yours is not here, ask it directly.
Ask an engineer01 Should we build a REST or GraphQL API?
REST is usually simpler for stable resources, public APIs, and teams that value predictable caching. GraphQL is useful when many consumers need different shapes of the same graph. We decide based on consumers and operational constraints.
02 How do you prevent duplicate records on retries?
Writes use idempotency keys or natural deduplication rules, and the downstream system is designed to treat a repeated request as the same operation. We test the retry path explicitly.
03 Can you integrate with a legacy system that has no API?
Often. We can use a database bridge, a file exchange, a message queue, or an anti-corruption layer. The constraint is documented and isolated so it does not leak into the rest of the system.
04 How do you handle authentication and authorisation?
We design the identity model before the endpoints: which clients act, which scopes they receive, and which operations require delegated or user consent. Tokens, rate limits, and audit records are part of the contract.
05 How do you version an API without breaking consumers?
We define a versioning and deprecation policy, keep additive changes backward compatible, and give consumers a migration window with docs and tests.
Next step
Which integration is failing quietly?
Tell us which systems have to agree and what happens when they do not. A senior engineer will reply with a contract and failure plan.
Contact us