The platforms, tools and engineering practices we use to build, test and understand modern data, software and AI systems.
Our toolkit spans data engineering, AI and LLM assurance, performance, cloud and observability. We choose technologies around your architecture, delivery model and operational needs rather than forcing a fixed stack.
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Lakehouse engineering for batch and streaming workloads, Delta-based data products, governance, analytics and ML/AI delivery on a shared.
Lakehouse & Data PlatformsIntegrated data engineering and analytics using OneLake, pipelines, notebooks, warehouses and Power BI for Microsoft-centric estates.
Enterprise AnalyticsScalable transformation pipelines, reusable data models, automated testing and controlled promotion of analytical datasets between.
Transformation & QualityEvent-driven integration, high-throughput streaming, partitioning strategies, consumer scaling and operational monitoring for real-time.
Real-time DataPractical engineering for ingestion, transformation, orchestration, data quality checks and automation across cloud and hybrid environments.
Pipelines & AutomationReliable lakehouse storage, governed access and business-facing analytics with lineage, controlled permissions and well-defined data.
Governance & AnalyticsEvaluation of retrieval-augmented generation systems across retrieval quality, groundedness, relevance and answer quality using repeatable.
RAG EvaluationLLM regression and quality testing with CI-friendly test suites, configurable metrics and model-agnostic evaluation for production AI.
LLM QualityPrompt, model and configuration comparison alongside adversarial testing for prompt injection, unsafe behaviour and common LLM security.
AI Security & Red TeamExperiment tracking, model lifecycle management, tracing and evaluation workflows that connect engineering evidence with repeatable AI.
Tracking & EvaluationTracing, debugging and production visibility for LLM applications, including prompt and response inspection, latency analysis and quality.
AI ObservabilityLoad, scalability and resilience testing for APIs, data services and AI workloads, with evidence focused on response time, throughput and.
Performance EngineeringCloud-native delivery, container platforms, deployment automation and environment engineering across data, software and AI workloads.
Platform EngineeringTell us about your LLM deployment and we'll identify your three highest-risk areas within two working days — no cost, no obligation, NDA first.