API Design & Development
APIs treated as products: a considered contract, documentation that matches behaviour, and versioning that does not break consumers.
Interfaces other teams can build against, and connections that hold when things go wrong.
Integration is where most systems actually fail, and usually not in the happy path — it is the timeout, the partial write, the schema that changed without notice. Nextherrion designs APIs as products with a contract worth depending on, and builds integrations that treat failure as an expected condition rather than an exception.
API design and delivery, third-party and enterprise integration, and the middleware, contracts and error handling that keep connected systems honest.
APIs treated as products: a considered contract, documentation that matches behaviour, and versioning that does not break consumers.
Connecting to external services with their rate limits, outages and breaking changes handled deliberately rather than discovered in production.
Moving data between the systems a business runs on, with clear ownership of which one holds the truth when they disagree.
Authentication, rate limiting, routing and usage visibility in one place, instead of reimplemented behind every endpoint.
Publishing and consuming events where systems should react rather than poll, with delivery guarantees stated rather than assumed.
Keeping records consistent across systems, including the harder half — conflict handling, ordering and recovery after an outage.
Reaching systems that predate modern interfaces, through adapters or intermediate services, without rewriting them first.
Documentation generated from the contract, so it stays true, and a place for consumers to find it without asking someone.
Integrations rarely fail in the happy path. What separates a reliable one is how it behaves on the timeout, the duplicate and the partial write.
Driven by the consumers. REST suits most service-to-service work, GraphQL earns its complexity with varied client needs, and events suit reacting to change rather than asking for it.
With retries, backoff, queueing and a defined degraded behaviour. The design question is what your system should do while the other one is down.
Usually, through file exchange, database access or an adapter layer. It is more fragile than a real interface, and that trade is made explicitly.
Versioning and additive change. Breaking changes get a migration path and a deprecation window rather than an announcement.
The most important question in any integration, and one we settle during design. Two systems both believing they own a record is the root of most sync problems.
Monitoring on throughput, error rates and lag — so a failing integration is noticed before a customer reports the consequence.
AI and Generative AI, agent frameworks, cloud platforms, data tooling and modern application stacks — chosen per problem rather than per preference.















Start with a data-flow review. Most sync problems are ownership problems.