LogixLoops
And nothing outside them. Every practice below has its own reference architecture and standard stack. Scroll to bring the grid home, then pick the one closest to your problem.
Each with its own reference architecture and standard stack. Most engagements draw on two or three at once, and the discovery call is where we work out which.
Custom enterprise platforms and legacy modernisation. Monoliths broken into microservices without taking the business offline.
MicroservicesKubernetesJava.NETAI development that reaches production: RAG over your own documents, predictive models, and the data pipelines underneath them.
RAGLLM OpsPyTorchVector DBWeb application development in Next.js and React. Typed end to end, fast on a mid-range phone, and yours at handover.
Next.jsReactTypeScriptNode.jsiOS and Android apps in React Native, Swift and Kotlin. Offline-first, hardware-aware, and shipped through both stores.
React NativeSwiftKotlinOffline-firstCloud infrastructure as code and CI/CD pipelines on AWS or GCP, with progressive rollout and a rollback that is one pipeline run.
AWSKubernetesTerraformCI/CDMulti-tenant SaaS architecture with tenant isolation, billing and role-based access designed in from the first commit.
Multi-tenantStripeRBACPostgreSQLWorkflow automation and RPA that connects the systems already running your business, so nobody is retyping data between them.
RPAPythonn8nEvent-drivenProduct design and design systems for dense interfaces. Built as tokens and components, tested against real data volumes.
FigmaDesign SystemsPrototypingResearchPick the practice closest to your primary constraint and let the discovery call sort out the rest. Most engagements draw on two or three at once: a SaaS build almost always pulls in cloud infrastructure and UI/UX, and an AI integration is a data pipeline problem long before it is a model problem.
Yes, and on a Dedicated Squad engagement that is the default. We work in your Jira or Linear instance, attend your standups and live in your Slack or Teams channels. Nothing gets copied into a private tracker and summarised back to you.
Both, and legacy modernisation is the larger share. Our standard approach is the Strangler Fig pattern: route traffic through a gateway, replace monolithic endpoints with new services one at a time, and keep the old path live until the new one has carried real load. The business never stops trading during the migration.
React and Next.js on the front, Node.js or Go behind them, PostgreSQL for data, and AWS or GCP for infrastructure. Everything is open source or a standard managed service, deliberately, so the next team to touch the repository recognises all of it.
See how we run delivery, the stack behind every build, or what this looks like in production.