We help mid-market leaders transform with Agentic AI strategy.

Generative AI produces text, images, or code in response to a prompt. Agentic AI goes further — it combines generative AI with the ability to plan, make decisions, use tools, and take actions autonomously over multiple steps. Where gen AI answers a question, agentic AI executes a workflow. We build production-grade agentic systems that act, not just respond.

We have shipped production systems across conversion optimisation, clinical content validation, design automation, geospatial data analysis, e-commerce product management, claims processing, and more. Every use case we take on has a clear business case and a measurable outcome. We do not build proofs of concept that never reach production — 100% of our projects have shipped to live environments.

We are technology-stack agnostic and select the right AI tools for each client's context. We are a strategic partner of Pydantic.dev and the first tech consultancy accepted by the Agentic AI Foundation. Our engineers work across leading LLM providers, vector databases, observability platforms, and open-source agentic frameworks. We also publish open-source tools used by thousands of developers worldwide.

Our work is designed for mid-market business leaders — challengers and category leaders who want to use AI to compound their competitive advantage. If you manage a team, a business function, a full company, or a portfolio of companies, agentic AI transformation is within reach. You do not need to be a technology company — some of our most impactful engagements have been in healthcare, manufacturing, logistics, and professional services.

Business transformation through agentic AI means redesigning how work gets done — not just layering ai tools on top of existing processes. It involves identifying where artificial intelligence creates the highest operational leverage, rebuilding workflows around autonomous agents, and measuring the financial impact at each step. For Mixam it meant a 2× conversion increase in 30 days; for Synera, a 3-hour task reduced to 3 minutes.

Yes — portfolio transformation is one of our dedicated tracks. We can guide a coordinated agentic AI transformation across multiple companies, business units, or institutions. This includes building shared governance frameworks, adapting them to each entity's context, and sequencing the rollout to maximise knowledge transfer between organisations.

Our AI strategy work starts with your business model, not with technology. We run executive workshops to understand your competitive position and operational constraints, then identify use cases where agentic AI creates measurable ROI. We build a prioritised roadmap with long term value modelling for each initiative — so you know what you are investing in before engineering begins.

AI adoption is one of the most underestimated challenges in transformation programmes — culture, skills, and change management are where most ai initiatives stall. We embed change management into every engagement from day one, upskill teams on agentic AI capabilities, and design rollout plans that build confidence rather than resistance. Whether you are running a top-down or bottom-up transformation, we adapt to your organisation's actual decision-making structure.

Absolutely — for many organisations this is the smartest path. Our focused single department implementation track lets you apply agentic AI to one business function of your choice, observe the results within that silo, and assess the impact before committing to a wider rollout. This reduces risk, generates internal proof points, and builds the internal AI capabilities your team needs to scale confidently.

Integration is a core part of our engineering practice — agentic systems need to connect to your CRMs, ERPs, databases, and APIs to be useful. Our architecture work maps your existing technology stack and designs integration points that connect rather than disrupt your operations. Security, compliance, and EU AI Act alignment are built into the architecture from the start, not added as an afterthought.

Reliability engineering is central to what we do. For Schmitt-Thompson Clinical Content we built a dual-validation architecture that achieved 0% hallucinations in a healthcare context. We combine retrieval-augmented generation, structured outputs, validation layers, and ongoing observability to keep every system accountable. Every system we ship is designed to fail safely and to surface uncertainty rather than mask it.

Three things: depth, accountability, and a genuine long term orientation. Our team includes PhD engineers, AI researchers, and senior consultants who have built and shipped real agentic systems — not just advised on them. We take accountability for outcomes, not just deliverables, and we design every engagement around your long term competitive position.

Book a short call with PhD engineers and consultants from our team — no commitment, just a real conversation about your business and where agentic AI creates the most leverage. We work with a limited number of clients at any time to maintain quality, so early conversations are valuable for both sides.