AI & GenAI
We take AI from proof of concept to production — grounding models in your enterprise knowledge, orchestrating agents that act within guardrails, and keeping people in the loop where it matters.
Knowledge
Retrieval
Reasoning
Control
Action
Capabilities
LLM-powered applications designed around real business workflows.
Answers grounded in your documents and data, with citations.
Semantic retrieval pipelines with chunking, embedding and re-ranking.
Connected entities and relationships that give AI structured context.
Unified, permission-aware search across enterprise content.
Task-focused agents that use tools, APIs and data to get work done.
Multi-agent orchestration for complex, multi-step business processes.
Review, approval and escalation steps designed into every workflow.
Intelligent automation of document, service and back-office processes.
Predictive models for forecasting, propensity, risk and optimisation.
Natural-language access to governed data and metrics.
Quality evaluation, safety guardrails and observability for AI systems.
Use cases
Give employees cited answers across policies, procedures and technical documentation.
Orchestrate agents that triage, research and draft — with humans approving key decisions.
Let business users ask questions of governed data in plain language.
Engagement pattern
A representative engagement pattern for this solution area.
AI & GenAI
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Modern, governed data platforms on the cloud — engineered for scale, reliability and AI readiness.
Data science, machine learning, model training and LLM fine-tuning — from experiment to monitored production model.
From business intelligence to decision intelligence — analytics that changes what people do next.
Customer data platforms, identity resolution and activation that turn data into personalised experiences.
FAQ
RAG is a pattern where a large language model answers using documents and data retrieved from your own knowledge sources at question time. It grounds answers in trusted enterprise content, supports citations and respects permissions, reducing hallucinations compared with a model answering from its training data alone.
Agentic AI uses one or more AI agents that plan and take multi-step actions — calling tools, APIs and data sources — to complete a task. In enterprise settings we design agents with guardrails, audit trails and human-in-the-loop approval for decisions that matter.
Production readiness adds systematic evaluation of answer quality, permission-aware retrieval, guardrails, observability, cost controls and LLMOps for versioning and monitoring. We treat these as engineering requirements from the start rather than steps added after a demo.
We are model-agnostic and select models per use case based on quality, latency, cost, data residency and security requirements, using commercial APIs or open models hosted in your cloud.
Let's explore what you can build with your data.
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