API Development Services
Build Systems That Scale Without Slowing Down
We design, develop and migrate microservices architectures that give your teams the autonomy to ship independently, scale precisely, and recover fast.
Our Decade long experience, validated in numbers
Enterprise Customers
OVERVIEW
From tightly coupled to independently deployable
Modern SaaS products outgrow monolithic systems faster than most teams expect. Features slow down, teams block each other, and a single deployment touches everything. We help organizations move to microservices architectures where each service owns its domain, communicates through well-defined APIs, and scales on its own terms. Whether you are starting from scratch or breaking apart an existing system, we deliver architectures that match how your teams actually work.
Trusted by Leading Enterprises
WHAT WE DELIVER
Right for your stage?
WHEN MICROSERVICES IS THE RIGHT CALL
Microservices is the right move when:
Multiple teams are blocked by a shared codebase
Different parts of your system have very different scaling needs
Release cycles have slowed because every change requires a full deployment
You need independent reliability across business-critical services
Your product is growing into multiple distinct domains or product lines
It may not be the right move yet when:
The product is still early-stage and domain boundaries are not yet clear
The team is small and the operational overhead outweighs the benefit
Existing deployment and observability tooling is not yet in place
How we work
Domain Mapping
We map your business domains, identify service boundaries, and define ownership before writing a line of code. Good microservices start with team topology, not just technical architecture.
API & Data Design
Each service gets its own data store and a well-defined API contract. We agree on communication patterns (REST/gRPC or asynchronous event-driven via Kafka/RabbitMQ) based on consistency and latency.
Build & Containerize
Services are built independently, containerized with Docker, and deployed through automated CI/CD pipelines. Each service ships on its own cadence without waiting for others.
Observe & Operate
Distributed tracing, centralized logging, and alerting are set up across all services from day one. You get complete visibility into every service boundary before going to production.
tech stack
Everything you need to know
A microservices architecture breaks a system into independently deployable services, each owning its own domain, data store, and API contract, rather than one shared codebase deployed as a single unit. Services communicate through well-defined APIs synchronous (REST, gRPC) or asynchronous event-driven messaging (Kafka, RabbitMQ) and each can be built, scaled, and released on its own cadence without waiting on the others.
Microservices is generally the right move when multiple teams are blocked working in a shared codebase, different parts of the system have very different scaling needs, or every release requires a full deployment even for small changes. It's usually not the right move yet if the product is early-stage with domain boundaries still unclear, the team is small enough that the added operational overhead outweighs the benefit, or deployment and observability tooling isn't in place yet since microservices adds real infrastructure complexity that only pays off once those conditions exist.
A monolith-to-microservices migration is done incrementally rather than as a rewrite: domain boundaries are identified first, then individual services are extracted progressively while the existing monolith stays live and serving traffic throughout. This minimizes disruption because the system keeps running normally at every stage of the migration, rather than requiring a high-risk cutover at the end.
The choice between REST, gRPC, and asynchronous event-driven messaging (Kafka, RabbitMQ) depends on the consistency and latency requirements between services. REST is typically used for simpler request/response APIs, gRPC where low-latency and strongly-typed contracts matter between internal services, and event-driven messaging where services need to stay decoupled and react to events asynchronously rather than waiting on a direct response.
An API gateway is a centralized layer that handles service discovery, load balancing, authentication, rate limiting, and observability across all microservices, so each individual service doesn't have to reimplement that logic separately. Without one, cross-cutting concerns like auth and rate limiting end up duplicated and inconsistently implemented across every service.
A production-ready microservices deployment means every service is packaged with Docker, orchestrated with Kubernetes, and deployed through automated CI/CD pipelines with autoscaling policies and health monitoring configured from the start not added after an incident. It also means distributed tracing, centralized logging, and alerting are set up across every service boundary before go-live, so there's full visibility into how requests move across services in production.
Where these capabilities apply
Edge-to-Cloud AI across our platforms and services.
Ready to break the monolith?
Whether you are designing from scratch or migrating an existing system, we scope and deliver microservices architectures that hold up under real traffic.