End-to-end design and implementation of intelligent systems — from data pipelines and vector search to LLM orchestration and autonomous agents — built for production, not prototypes.
AI infrastructure is the complete technical stack that allows intelligent capabilities to operate at scale in production environments. It's not a chatbot feature — it's the system that powers it.
Most organisations encounter AI at the surface: a widget, a demo, a proof of concept. What separates that from genuine business value is the infrastructure underneath — reliable data ingestion, properly indexed knowledge bases, orchestrated model calls, fallback logic, monitoring, and cost management.
We design and build that entire stack. From the first data architecture decision to the last deployment configuration, we treat AI as engineering discipline — not magic, not buzzwords.
The result is AI that works the way your business actually operates: reliably, transparently, and with room to grow.
Retrieval-Augmented Generation systems that connect LLMs to your proprietary data. Document ingestion, chunking strategies, embedding generation, vector storage, and retrieval tuning — all engineered for accuracy and latency.
Multi-step AI workflows with tool use, function calling, and model routing. We build the logic layer that turns a raw LLM call into a reliable, multi-step business process — with fallbacks, retries, and cost controls.
Autonomous AI systems that plan and execute multi-step tasks — browsing, writing, calling APIs, managing data. We design agent architectures with appropriate guardrails and human-in-the-loop checkpoints.
Structured knowledge bases, entity graphs, and semantic search systems. We turn scattered documents, PDFs, emails, and databases into a queryable, AI-navigable knowledge layer for your organisation.
Backend APIs designed for AI consumption — structured outputs, streaming responses, tool schemas, and semantic endpoints. Infrastructure that AI agents and LLM apps can reliably call and integrate with.
LLM tracing, cost dashboards, quality evaluation pipelines, and regression testing for AI systems. Because production AI without monitoring is just an expensive liability waiting to surface.
RAG-powered systems trained on property knowledge, local recommendations, and booking logic. Pre-stay, in-stay, and post-stay AI that personalizes every interaction without losing the human touch.
Turn years of documentation, SOPs, contracts, and emails into a searchable, AI-queryable system. Reduce onboarding time, accelerate decision-making, and surface institutional knowledge on demand.
Semantic product search, AI-driven recommendations, and conversational shopping assistants. Systems that understand intent, not just keywords — increasing conversion and reducing support load.
AI systems for contract analysis, compliance checking, report generation, and research automation. Replace hours of manual document work with accurate, auditable AI processes.
Before any model call or API key, we map your data landscape, define retrieval strategies, and design the system architecture. Getting this right determines everything downstream — speed, cost, accuracy.
We clean, structure, and embed your data into vector stores with appropriate chunking strategies. Most AI projects fail here — poorly prepared data produces confidently wrong answers. We treat this phase with engineering rigour.
RAG pipelines, orchestration layers, API design, and integration work — all built iteratively with regular evaluation checkpoints. Quality gates at every stage, not just at the end.
Systematic testing of retrieval accuracy, response quality, and latency. We measure before we ship, and we document the metrics so you can hold future improvements to the same standard.
Containerized deployment with monitoring, alerting, and cost controls. We don't hand off a zip file — we deploy, observe, and stay engaged through the critical early-production period.
Tell us what you're working toward. We'll tell you what's realistic, what it takes, and whether we're the right team for it.