We design, build, and deploy LLM-powered applications and agentic AI workflows that automate complex reasoning, generate high-value content, and orchestrate multi-step business processes with enterprise-grade reliability and safety.
Most enterprises are stuck in proof-of-concept purgatory. They have experimented with chatbots and summarisation tools, but have not yet achieved the transformative business outcomes that generative AI promises. The gap is not ambition; it is architecture, governance, integration, and operational maturity. SurreyTech closes that gap.
We build enterprise-grade generative AI systems that go far beyond simple prompt-and-response interfaces. Our engineers design multi-agent architectures where specialised AI agents collaborate to solve complex business problems, RAG pipelines that ground model outputs in your proprietary knowledge, and orchestration layers that integrate generative AI into existing business workflows with full auditability and human oversight.
We are model-agnostic and commercially pragmatic. We work across Anthropic Claude, OpenAI GPT-4, Google Gemini, Meta Llama, Mistral, and other open-source models, selecting the right foundation model for each use case based on capability, cost, latency, data residency, and regulatory requirements.
Custom-built applications that leverage large language models for document analysis, contract review, regulatory interpretation, customer communication generation, code assistance, and knowledge synthesis. Every application includes safety guardrails, output validation, and integration with enterprise systems of record.
Design and deploy autonomous AI agents that plan, reason, use tools, and execute multi-step workflows with minimal human intervention. Our agentic architectures include planning agents, execution agents, verification agents, and supervisor agents that collaborate to solve complex problems while maintaining human oversight at critical decision points.
Build retrieval-augmented generation pipelines that ground model outputs in your proprietary data. We design embedding strategies, chunking algorithms, vector database architectures, hybrid search implementations, and re-ranking pipelines that deliver accurate, cited responses from your internal knowledge base with measurable retrieval precision.
Systematic prompt engineering methodologies that maximise model performance for your specific use cases. When prompting reaches its limits, we design fine-tuning pipelines using LoRA, QLoRA, and full fine-tuning approaches with rigorous evaluation frameworks that measure task-specific performance against production benchmarks.
Enterprise-grade safety frameworks that address hallucination mitigation, output filtering, PII protection, bias detection, adversarial attack resistance, and regulatory compliance. We implement monitoring systems that track model behaviour in production and alert on drift, safety violations, or quality degradation.
Applications that combine text, image, audio, and video understanding for use cases including visual inspection, document digitisation, meeting intelligence, and multimedia content generation. We architect multi-modal pipelines that route inputs to specialised models and synthesise outputs into coherent business workflows.
Agentic AI represents the next evolution beyond simple generative AI. Instead of single-turn interactions, agentic systems decompose complex objectives into sub-tasks, select and use appropriate tools, gather information from multiple sources, and iteratively refine their approach until the objective is achieved.
Our agentic AI architecture follows a principled design pattern: a planning layer that decomposes objectives, an execution layer that performs actions using tools and APIs, a memory layer that maintains context across sessions, and a governance layer that enforces safety boundaries and escalation rules.
We implement tool-use frameworks that give agents access to databases, APIs, file systems, and external services while maintaining strict access controls and audit trails. Every agent action is logged, every decision is explainable, and every workflow includes configurable human-in-the-loop checkpoints for high-stakes decisions.
Whether you need an LLM-powered application, an agentic workflow system, or a comprehensive RAG architecture, our generative AI engineers can take you from concept to production with enterprise-grade reliability.