Everything it takes to run AI in production.
Seven integrated practices that cover the full lifecycle: choosing the right use cases, engineering agents and automations, grounding them in trusted data, securing them, and operating them on resilient platforms.
Pick a starting point. We'll connect the rest.
01
Agentic AI Engineering
Design, build and operate AI agents that plan, use tools and complete multi-step work across your systems, with guardrails, evals and human oversight built in.
Autonomous agents · Multi-agent systems · MCP
- Agent architecture & design
- Multi-agent orchestration
- MCP servers & tool integration
- Evals & quality engineering
02
AI Automation & Intelligent Workflows
Replace brittle, manual and RPA-heavy processes with AI-powered workflows that read documents, make decisions and keep humans in control.
Intelligent process automation · Document AI · Voice AI
- Process discovery & ROI
- Intelligent document processing
- AI workflow orchestration
- Voice & conversational AI
03
Forward Deployed Engineering
Senior engineers who embed with your teams, sit with your users and ship AI into real workflows, then hand the capability over to you.
Embedded AI engineers · FDE pods · Build-operate-transfer
- FDE pods
- User-embedded discovery
- Integration engineering
- Rapid prototyping to production
04
Data & AI Platforms
AI is only as good as the context it can reach. We build the governed data foundations, retrieval and knowledge layers that make AI accurate.
RAG · Lakehouse · Vector search · Knowledge graphs
- Enterprise RAG & search
- Knowledge graphs & GraphRAG
- Lakehouse architecture
- Data engineering & pipelines
05
AI Governance, Security & Evals
Adopt AI with confidence: governance frameworks, risk assessments, red-teaming and continuous evaluation aligned to emerging regulation.
EU AI Act · ISO/IEC 42001 · NIST AI RMF · Red-teaming
- AI governance operating model
- Regulatory readiness
- LLM & agent security
- AI red-teaming
06
Cloud & Platform Engineering
Resilient, cost-efficient cloud foundations and internal developer platforms that let teams ship AI and software safely and fast.
Kubernetes · Internal developer platforms · GPU infra · FinOps
- Cloud migration & modernisation
- Internal developer platforms
- AI & GPU infrastructure
- DevSecOps & GitOps
07
AI-Native Product Engineering
Design and build AI-native web and mobile products, from discovery and UX through to scalable full-stack engineering.
Web & mobile · AI UX · Modern full-stack
- Product discovery & strategy
- AI UX & design systems
- Full-stack web engineering
- APIs & microservices
Have a workflow AI should be running? Let's map it together.
Book a 45-minute strategy session with a Vidura principal. You'll leave with a shortlist of high-ROI AI use cases, the risks to manage, and a realistic path to production.