Industries we serve
Secure, compliant platforms for banking, fintech, and wealth management where downtime is not an option.
Revenue intelligence, booking systems, and high-touch digital experiences for premium travel brands.
Adaptive learning platforms, LMS infrastructure, and AI-powered content operations for global institutions.
Smart property platforms, resident applications, and ESG reporting tools for the built environment.
ERP modernization, process automation, and data platforms that enable large organizations to operate with speed, control, and global scale.
Environmental impact tracking, ESG reporting infrastructure, and compliance platforms for responsible organizations.
Content platforms, streaming infrastructure, and monetization systems built to scale audience engagement and performance.
AI TECHNOLOGIES
A focused set of models, frameworks, and protocols we use to build agentic systems—from single agents that call tools to multi‑agent workflows that power products end‑to‑end.
Every technology on this page is battle‑tested in real client work, not just lab demos. We use it where it makes sense, and design the stack around your security, data, and compliance needs.
Specialised roles for support, ops, and commerce.
Standard layer for tools, data, and actions.
LangChain + vector stores for grounded answers.
Protocols so agents can coordinate safely.
Multi‑agent patterns for complex workflows.
Monitoring, safety checks, and governance.
Design of autonomous, tool‑using AI agents that execute real workflows with human‑in‑the‑loop guardrails.
Agent‑to‑agent protocols for structured collaboration, negotiation, and delegation between specialised agents.
Model Context Protocol for safely exposing tools, APIs, and data sources to agents through a unified layer.
Patterns for agent‑driven discovery, pricing, and ordering experiences in modern commerce flows.
Open models, transformers, and inference tooling for NLP and multimodal use cases.
Framework for retrieval‑augmented generation pipelines, tool‑calling agents, and evaluation loops.
Multi‑agent crews with clear roles and coordination patterns for complex, multi‑step tasks.
Orchestration of agents, tools, and protocols with monitoring, safety checks, and governance in production.
The best AI stack is the one that fits your data, risk profile, and product roadmap. We prioritise reliability and maintainability over chasing every new framework.
We start from the workflow and user journey, then map technologies like LangChain, MCP, and agent crews where they add real leverage—not the other way around.
Protocols such as A2A and MCP let us enforce permissions, observability, and human approvals so agents stay within well‑defined boundaries.
We plan for monitoring, evaluation, and iteration from day one, so your AI stack can evolve as models and business needs change.
Answers to common questions about how we design and deploy this AI stack inside real products and organisations.
Agentic AI systems can plan, call tools, and update systems on your behalf. They are designed around specific roles and guardrails, not general chat. We focus on narrow, high‑value workflows rather than unconstrained autonomy.
Not at all. Most projects start with a small subset—often an agent built with LangChain, MCP for tools, and one or two protocols. We add additional components only when they solve a real problem such as coordination or governance.
Yes. We work with OpenAI, Anthropic, open‑source models via Hugging Face, and enterprise platforms. The stack is designed to be model‑agnostic so you can switch providers as the landscape evolves.
For a well‑scoped workflow, we typically move from design to a production‑ready pilot in weeks, not months—starting with one agent and a small set of tools, then iterating based on real usage and evaluation data.