Twelve capabilities that cut across all five practices. Each one links to the practice that owns it, so you can see who would do the work as well as what it is.
Enterprise application development and custom platform builds, from an MVP that has to exist in three months to a card management system that has to pass PCI-DSS. API-driven microservices, cloud-agnostic by default.
Product Engineering →Strangler-pattern migrations, framework porting, architecture and database modernisation, containerisation and legacy-to-cloud paths. Modernising a system you cannot switch off is most of this work.
Product Engineering →API enablement and system integration across enterprise estates — messaging hubs, partner platforms, ecosystem and LTI integration, and the connectors that make one system’s data usable in another.
Product Engineering →AWS, Azure, GCP and private cloud. Infrastructure modernisation, Kubernetes and OpenShift, provisioning and virtualisation, and cloud cost engineering where the saving is measurable rather than asserted.
Platform Delivery & Operations →CI/CD, infrastructure automation, deployment paths and the internal platforms delivery teams use every day. DevOps enablement for teams that have the tools and not yet the habits.
Platform Delivery & Operations →Elastic-centred observability estates: one telemetry pipeline serving both the operations team and the security team, rather than two that disagree. Capacity planning, reliability engineering, incident response and IT operations management.
Platform Delivery & Operations →i3QA™ testing services: functional and regression, exploratory, UAT and release certification. Automation across Selenium, CodeCept, Postman and Newman and Tricentis Tosca, plus mobile application and device testing.
Quality Engineering →Optimisation across the application, architecture, database, infrastructure and network layers rather than at one of them. Load and capacity work for platforms whose traffic is not evenly distributed.
Quality Engineering →API and security testing with intercepted and manipulated payloads rather than a scanner report, compliance readiness, SecOps alongside observability, and OWASP GenAI/LLM Top 10 alignment for AI systems.
Quality Engineering →Enterprise search and conversational AI, workflow automation agents, document intelligence for invoices, receipts and contracts, biometrics, and robotic process automation where the process is stable and the volume is high.
TurfAI →Batch and streaming pipelines from source ingestion through to delivery, lake and warehouse design for analytical and AI workloads, and the governance underneath — schema management, lineage, quality monitoring and access control.
Platform Delivery & Operations →Evaluation harnesses, guardrail testing, regression under non-determinism, drift detection and audit trails. This sits alongside i3QA™ rather than inside it, and deliberately does not carry that label.
Quality Engineering →Grouped the way we staff it. Where a platform also carries a formal partnership, it is on the Partners page as well.
The short list of platforms we deploy, tune and run under a partner agreement lives on its own page.
