AI TECHNOLOGIES
AI & Agentic Technology Stack
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.
Agentic AI
Design of autonomous, tool‑using AI agents that execute real workflows with human‑in‑the‑loop guardrails.
A2A Protocol
Agent‑to‑agent protocols for structured collaboration, negotiation, and delegation between specialised agents.
MCP
Model Context Protocol for safely exposing tools, APIs, and data sources to agents through a unified layer.
Agentic Commerce Protocol
Patterns for agent‑driven discovery, pricing, and ordering experiences in modern commerce flows.
Hugging Face
Open models, transformers, and inference tooling for NLP and multimodal use cases.
LangChain
Framework for retrieval‑augmented generation pipelines, tool‑calling agents, and evaluation loops.
CrewAI
Multi‑agent crews with clear roles and coordination patterns for complex, multi‑step tasks.
Agent Orchestration
Orchestration of agents, tools, and protocols with monitoring, safety checks, and governance in production.
How We Choose the Right AI Technologies
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.
Use‑Case First
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.
Safety & Governance
Protocols such as A2A and MCP let us enforce permissions, observability, and human approvals so agents stay within well‑defined boundaries.
Production Ready
We plan for monitoring, evaluation, and iteration from day one, so your AI stack can evolve as models and business needs change.
AI & Agentic Technologies FAQs
Answers to common questions about how we design and deploy this AI stack inside real products and organisations.
What do you mean by agentic AI?
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.
Do we need every technology listed here?
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.
Can you integrate with our current LLM provider?
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.
How long does it take to launch a first agent?
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.