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Leadership teams can move forward knowing the AI systems we deliver are auditable, compliant and designed to perform reliably within the regulatory and operational environments your organisation operates in.\n","We combine strategic AI expertise with production engineering, governance and operational insight, helping organisations move beyond experiments and deliver intelligent systems that are reliable, responsible and ready to scale.\n","How we approach AI","From AI strategy and prototyping, to production AI, agentic systems, cloud AI platforms and data science, we help organisations design, build and deploy AI solutions that deliver measurable value in complex, real-world environments.\n",{},true,"\u002Fservice-overviews\u002Fai",[344,356,368,380],{"id":345,"path":346,"title":347,"projectName":348,"smallCoverImage":323,"largeCoverImage":349,"coverImageColour":323,"clientLogo":350,"about":351,"meta":352},"projects\u002Fprojects\u002Fclimate-risk-analytics-provider.md","\u002Fprojects\u002Fclimate-risk-analytics-provider","Climate risk analytics provider","Improving enterprise reporting for data-driven decision making","\u002Fimg\u002Fscreens\u002Friskreporting.avif","\u002Fimg\u002Fclient-logos\u002Fclimate-risk.png","A leading climate risk analytics organisation providing data-driven solutions to help organisations understand, quantify, and mitigate climate-related risks.",{"statBlock":353},{"title":354,"text":355},"Climate Risk","Data Reporting",{"id":357,"path":358,"title":359,"projectName":360,"smallCoverImage":323,"largeCoverImage":361,"coverImageColour":323,"clientLogo":362,"about":363,"meta":364},"projects\u002Fprojects\u002Fthe-national-institute-for-health-research-nihr.md","\u002Fprojects\u002Fthe-national-institute-for-health-research-nihr","The National Institute for Health Research (NIHR)","A platform to manage £317m funding allocation each year","\u002Fimg\u002Fscreens\u002Fnihr-healthcare-worker.jpg","\u002Fimg\u002Fclient-logos\u002Fnihr.png","The National Institute for Health Research (NIHR) is the nation’s largest funder of health and care research, with a mission to improve the health and wealth of the nation, transforming people’s lives, promoting economic growth and advancing science.",{"statBlock":365},{"title":366,"text":367},"£317 million","Funding allocation managed each year for the nation’s largest funder of health and care research",{"id":369,"path":370,"title":371,"projectName":372,"smallCoverImage":323,"largeCoverImage":373,"coverImageColour":323,"clientLogo":374,"about":375,"meta":376},"projects\u002Fprojects\u002Faesseal-quotation-platform.md","\u002Fprojects\u002Faesseal-quotation-platform","AESSEAL - Quotation Platform","Generating over 38,000 complex bespoke engineering quotations for global sites ","https:\u002F\u002Fimages.unsplash.com\u002Fphoto-1581092580497-e0d23cbdf1dc?q=80&w=3270&auto=format&fit=crop&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D","\u002Fimg\u002Fclient-logos\u002Faesseal.png","AESSEAL is the fourth largest mechanical seal manufacturer in the world, hitting a record of £170 million turnover last year, with offices in 104 countries, with their focus on customer service and quality seeing them grow year on year since they were established in 1979.",{"statBlock":377,"hideFromSidebar":341},{"title":378,"text":379},"38,000 +","Complex bespoke engineering quotations generated for global sites for leading manufacturer ",{"id":381,"path":382,"title":383,"projectName":384,"smallCoverImage":323,"largeCoverImage":385,"coverImageColour":323,"clientLogo":386,"about":387,"meta":388},"projects\u002Fprojects\u002Finnovative-trials.md","\u002Fprojects\u002Finnovative-trials","Innovative Trials","Improving global visibility and reporting with one centralised portal","\u002Fimg\u002Fscreens\u002Fbannerimage_innovativetrials.jpg","\u002Fimg\u002Fclient-logos\u002Finnovative-trials.png","Innovative Trials specialises in the delivery of accelerated patient recruitment. Innovative Trials works with study teams to deliver professional tailor-made solutions to help clinical trials deliver on time, within budget and to the required standard.\n",{"statBlock":389},{"title":390,"text":391},"Improving global visibility and reporting","Through one centralised portal.",{"title":173,"description":324},"service-overviews\u002Fai","swNS68WwSMwgN76G2MxYdomjI9FLzmJ1y85olVYe5iM",[396,403,410,416],{"path":397,"title":398,"author":399,"date":400,"image":401,"customExcerpt":402,"excerpt":323},"\u002Fblog\u002Ffabric-iq-and-ontology","Fabric IQ and Ontology: Giving Data a Shared Business Meaning","Chris Bentley ","2026-07-08T15:50:59.637Z","\u002Fimg\u002Fblog\u002Fmicrosoft-fabric-iq-and-ontology.png","AI agents need a fixed, shared meaning for business data before they can be trusted to reason over it. This piece looks at what Fabric IQ and Ontology actually are, how they differ from a semantic model, what preparing your data for them involves, and where the platform trade-offs sit against alternatives from Databricks and Snowflake.",{"path":404,"title":405,"author":406,"date":407,"image":408,"customExcerpt":409,"excerpt":323},"\u002Fblog\u002Ftesting-in-legacy-modernisation","A Testing Strategy for Legacy Modernisation","Richard Brown","2026-07-08T15:42:18.390Z","\u002Fimg\u002Fblog\u002Fsoftware-testing-in-legacy-modernisation.png","Legacy systems often don't come with a specification, with their behaviour living in code nobody documented and workarounds nobody wrote down. This piece looks at why conventional testing breaks down in modernisation projects, how characterisation testing captures undocumented behaviour before it's changed, and how to measure whether your testing strategy is actually working.",{"path":411,"title":412,"author":406,"date":413,"image":414,"customExcerpt":415,"excerpt":323},"\u002Fblog\u002Ffrom-proof-of-concept-to-production-what-ai-projects-actually-require","From Proof of Concept to Production: What AI Projects Actually Require ","2026-07-06T08:40:10.465Z","\u002Fimg\u002Fblog\u002Fai-poc-to-production-ts-episode-1.png","The gap between a proof of concept and a production system is where a significant proportion of AI initiatives fail to progress. Understanding what that transition involves, and planning for it from the outset, is one of the more important things a technology leader can do before committing investment. 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