More than 70% of AI projects fail to deliver their intended value. The problem is rarely the model. It is the operating model around the model. We identify the highest-value use cases, build them to production grade, and govern the outcome against the business case. From first use case to live deployment, in weeks rather than quarters.
We do not build AI for the sake of AI. Every engagement starts with a structured mapping of where the highest EBIT-impact opportunities sit, then prioritises the build sequence against investment, risk, and delivery feasibility.
Use cases are scored against our PAVCS value creation framework before any development begins. The highest-impact opportunities go first. The build runs through a five-stage flow: identify, design, build, validate, embed. Agentic AI handles data ingestion, prompt engineering, code generation, and integration scaffolding. Senior consultants run the design reviews, quality gates, and production sign-off.
Every release ships with a benefits hypothesis, with value tracked from day one, not retrospectively justified once the project is closed. If the outcome is not showing up on the P&L, it is surfaced before it becomes a write-off.
The results speak to the model. A £750m construction company live with invoice automation in under a month, 99%+ first-time accuracy, £25k investment recovered in eight weeks. A £100m+ insurance broker saving £3.2m annually with its renewals cycle compressed from six weeks to ten days. A PE-backed e-commerce group cutting product creation time by 80% and halving staffing costs.
We work across the full spectrum of AI and automation capability, selecting the right approach for each use case rather than defaulting to a single technology or vendor.
Forecasting, classification, anomaly detection, demand prediction, and churn modelling. Built into core operating systems rather than bolted on as dashboards that nobody revisits. We identify the decision points where predictive insight changes an operational outcome, and we build the model around that decision, not around the data that happens to be available.
Document generation, customer-facing content, internal knowledge retrieval, and workflow-embedded GenAI. Domain-tuned models grounded on your proprietary data and governed by senior human review at every output stage. We work with Microsoft Copilot, OpenAI, and custom model architectures, selecting the deployment approach that fits the use case and the organisation’s data governance posture.
Multi-step autonomous workflows that ingest, decide, act, and escalate. The most operationally valuable category and the one where most pilots stall. We build production-grade agentic systems using UiPath, Microsoft Power Automate, and bespoke orchestration layers, with human-in-the-loop controls designed in from the architecture stage rather than retrofitted after launch.
Most AI projects fail at the same three points. We have built our delivery model to address all three directly.
Technology-first AI projects build solutions in search of a problem. We map use cases against business outcomes using PAVCS before any development begins. The highest EBIT-impact opportunities go first. Every build has a defined success metric before the first line of code is written, so the team knows what production looks like before they start.
Pilot-grade AI and production-grade AI are built differently. Ours is designed for the operating environment from the outset: real data volumes, real integration constraints, real governance requirements, real users. The five-stage build flow includes a challenge stage where senior consultants stress-test the model against edge cases and operational realities before sign-off.
Most AI value evaporates after launch because there is no accountability structure to track it. We track benefits realisation from the start of every engagement through the post-deployment period. Value is measured against the business case on a defined cadence. If it is not showing up, we know before the investor does.
We can run a two-week diagnostic on a stranded pilot or an identified use case and give you a quantified path to production, with benefits realisation tracked from day one.