Tomoro went from an AI startup in London & Edinburgh to the founding acquisition of The OpenAI Deployment Company in about two and a half years, growing past 100 people on the way.Co-founder Albert Phelps shares what they got right: the hiring bar they set from day one, why they ran Tomoro as a people business rather than a technology one, and what stops most companies scaling AI once the pilot has worked. Albert was last on A Class Act in April, when Tomoro was still independent. He now works on deployments and go-to-market across Asia-Pacific for the OpenAI Deployment Company, from Singapore. This time Michael Young asks him how the deal came about, what OpenAI saw in Tomoro, and what he'd build into an AI startup if he were starting again today.What you'll discover:What  it takes to build an AI company OpenAI wants to buyWhere Albert was when the OpenAI deal was signed offHow  starting with a large founding team gave Tomoro a senior leadership team from day oneWhy "be helpful, not clever" became the rule for a company full of AI obsessivesWhat OpenAI saw in TomoroHow client work has moved from 12-week use cases to reinventing whole businessesThe four things a company needs in place to scale AI, starting with leaders who use it every dayThe two culture mistakes he sees mostReal examples: AI for sales teams, Codex in advanced manufacturing, continuous model retraining, and Virgin Atlantic's AI travel conciergeWhy cyber security is now the number one AI conversation with his financial services clientsWhat he would build into a company from day one if he were starting again todayAbout Albert PhelpsAlbert Phelps is co-founder of Tomoro, the applied AI company founded in London & Edinburgh in 2023 that became the founding acquisition of The OpenAI Deployment Company in 2026. He works on deployments and go-to-market across Asia-Pacific for the OpenAI Deployment Company, based in Singapore, where he built Tomoro's Singapore team from scratch after moving from the UK in 2025.He came across GPT-3 while working in retail banking, when fewer than a thousand people were using the OpenAI API, and before Tomoro held roles at Deloitte, Capgemini, Nationwide and Accenture. This is his second appearance on A Class Act, after "Inside Tomoro AI: Getting Enterprise AI Into Production" in April 2026.Connect with Albert on LinkedIn: linkedin.com/in/albert-p-189ba2201About Michael YoungMichael Young is the Founder & CEO of MBN Solutions and host of A Class Act. With nearly two decades of experience helping organisations build high-performing data, analytics and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Connect with MBN SolutionsIf you are building a deployment or forward deployed engineering team, or hiring the people who will take AI from pilot to production, MBN partners with organisations to build data and AI teams that deliver.Email: [email protected]  ·  Website: www.mbnsolutions.comFollow the showSeason 3 is under way. Follow A Class Act wherever you get your podcasts and leave a review to help more listeners find these conversations.The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.

Emma Rattray picked chemical engineering at seventeen because she liked maths and physics. She’s now an AI engineer in Stockholm, working on a product thousands of people use every day.How she got from one to the other is the interesting part. Michael Young asks her how each of those steps actually happened. What the master’s demanded that neither her degree nor her job had. And what she’s learned about getting AI into production now she does it full time.What you’ll hear:✔️How a LinkedIn post about visiting Stockholm turned into a job she was not looking for✔️The small project she is proudest of, and why it was one of the simplest things she built✔️The question from her Lagora interview that has stayed with her, and why it had nothing to do with AI✔️Why she says the fundamentals still decide everything, however new the technology is✔️Why choosing chemical engineering at seventeen was not a mistake, and what it still gives her✔️What went into winning a Google DeepMind scholarship✔️What the master’s demanded that neither her degree nor her job had✔️The three things she would ask anyone describing a project they have built✔️What a day actually looks like as the only engineer on a product used every day✔️What moving fast looks like at a startup compared with JP MorganGuest InformationEmma Rattray is a member of the technical staff at Lagora in Stockholm, where she builds and ships AI products into production. She studied chemical engineering at the University of Edinburgh, moved into software engineering at JP Morgan, and returned to Edinburgh for a master’s in AI as a Google DeepMind scholar.Connect with Emma Rattray on LinkedIn: https://www.linkedin.com/in/emma-rattray-bb026b143/Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.About Your HostMichael Young is the Founder & CEO of MBN Solutions and host of A Class Act. With nearly two decades of experience helping organisations build high-performing data, analytics and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Connect with MBN SolutionsIf you are hiring AI engineers, building an early-career pipeline, or trying to work out what to actually look for in people coming into the field now, MBN partners with organisations to build data and AI teams that deliver.MBN Solutions on LinkedIn — industry updates, projects, and the latest in data, AI and analytics talent. Visit the company page here: https://www.linkedin.com/company/520643For questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions at www.mbnsolutions.comhow to get into AI, AI career, AI engineer, AI engineering career, career change into AI, machine learning career, AI jobs, getting into tech, Google DeepMind scholarship, masters in AI, University of Edinburgh, JP Morgan, software engineering, building in public, AI portfolio projects, early career AI, graduate AI jobs, AI startup, Stockholm tech, Lagora, Emma Rattray, Michael Young, MBN Solutions, A Class Act podcast, AI talent, hiring AI engineers

Stuart is Chief AI Officer at Sabio Group, a CX consulting and technology firm that has spent two decades helping large organisations run their contact centres. He was working on speech recognition and natural language when it was still called speech technology, long before ChatGPT made any of it mainstream, so he has watched several waves of this arrive and seen which ones actually changed anything.In the second episode of season 3, Michael Young asks him what genuinely changed after ChatGPT, why the predicted wave of job losses has not materialised, and what separates the organisations getting real value from AI from the ones putting staff through a morning of Copilot training and calling it transformation.If you run a contact centre, own CX, or are trying to work out what AI is genuinely worth in a service organisation, this one is for you.What you’ll discover:What Sabio was doing with speech recognition and natural language back in 2004, and whether today feels revolutionary or like the technology finally caught upThe moment AI stopped being something Sabio sold to clients and started changing Sabio itselfWhy the Silicon Valley prediction that customer service would be first for job disruption has not played out the way it was soldWhy he sees AI as an expansive rather than a reductive technologyThe argument that the organisations who win are not the ones handling the most interactions, but the ones serving far more customersWhat he would do differently if he were building Sabio from scratch today as an AI-native companyWhy the barrier is no longer access to the technology but whether your organisation is culturally set up to use itWhy testing, tuning and optimising an AI deployment is now often a bigger job than building itWhere agentic AI is genuinely useful today in customer service, and where explainability and regulation start to biteGuest InformationStuart Dorman is Chief AI Officer at Sabio Group, where he leads the company’s AI strategy and its advanced technology portfolio across contact centre, AI, data and data analytics. He has spent close to three decades working where technology meets customer experience, starting with speech applications and natural language long before generative AI made the field mainstream.Sabio is a CX consulting and technology firm specialising in AI-powered customer experience, working with technology partners including Amazon Connect, Salesforce, Genesys and Google Cloud, and with clients including British Airways, Vodafone, Marks & Spencer and DHL Express. Stuart is responsible for developing those strategic partner relationships, and is a regular speaker across the global CX circuit.He is a strong advocate for treating AI as an expansive technology rather than a cost-reduction exercise, for experimentation over long roadmaps, and for the view that the constraint on most organisations is cultural rather than technical.Connect with Stuart Dorman on LinkedIn:https://www.linkedin.com/in/stuartdorman/Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.About Your HostMichael Young is the Founder & CEO of MBN Solutions and host of A Class Act. With nearly two decades of experience helping organisations build high-performing data, analytics and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Connect with MBN SolutionsIf you are building the AI capability inside a service organisation, or working out what skills your teams actually need to make it pay, MBN partners with organisations to build data and AI teams that deliver.MBN Solutions on LinkedIn — industry updates, projects, and the latest in data, AI and analytics talent. Visit the company page here: linkedin.com/company/mbn-recruitment-solutionsFor questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions at www.mbnsolutions.comSubscribe & FollowSeason 3 is under way. Follow A Class Act wherever you get your podcasts and leave a review to help more listeners find these conversations.

Every AI company seems to want a forward deployed engineer. Yet very few can explain what they’re actually hiring for.Tom McLaughlin was doing the job before it became one of the hottest titles in AI. He went from software engineering at JP Morgan to Tomoro, the applied AI firm OpenAI acquired in May 2026, and he’s now a forward deployed engineer at The OpenAI Deployment Company, working inside enterprise clients across the UK, Europe and the US.In this conversation, he chats to host Michael about where the FDE role came from, what a customer is really paying for when they hire one, and why so much of the value has moved from writing code to judgment, context and ownership. If you’re building an AI team, hiring into one, or still working out whether you need forward deployed engineers at all, start here.What you’ll hear:The restaurant story Palantir used to explain the whole idea and the one line the entire model rests onWhy Tom thinks most companies hiring internal FDEs are answering a different question from the one they think they’re askingWhat the customer is actually paying for and whether one person should be carrying all threeWhen forward deployed engineer and forward deployed strategist should be two separate jobsCan one exceptional FDE with a swarm of agents replace a team of five?Why making code cheap doesn’t remove the bottleneckThe line between FDE and plain consultancyWhat is left for the human once agents do the implementationTom’s picture of 2030What to look for when hiring an FDEThe one hiring mistake to avoidGuest InformationTom McLaughlin is a founding forward deployed engineer at The OpenAI Deployment Company, based in Scotland and working with enterprise clients across the UK, Europe and the US. He started out as a software engineer at JP Morgan before joining Tomoro, the applied AI consulting and engineering firm OpenAI acquired in May 2026 as the founding piece of its Deployment Company.Connect with Tom McLaughlin on LinkedIn:https://www.linkedin.com/in/aibuilder/Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.About Your HostMichael Young is the Founder & CEO of MBN Solutions and host of A Class Act. With nearly two decades of experience helping organisations build high-performing data, analytics and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Connect with MBN SolutionsIf you’re hiring forward deployed engineers, building an AI delivery team, or rethinking what your technical hiring process is actually screening for, MBN partners with organisations to build data and AI teams that deliver.MBN Solutions on LinkedIn — industry updates, projects, and the latest in data, AI and analytics talent. Visit the company page here: https://www.linkedin.com/company/mbn-recruitment-solutionsFor questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions at www.mbnsolutions.com

Season 3 of A Class Act is here.Every breakthrough in AI begins as an idea almost nobody believes in yet. But brilliant technology doesn't change anything until it survives contact with the real world.So why do some AI products transform entire organisations while others never make it past the demo? And who are the people capable of closing that gap?This season, host Michael Young sits down with the category-defining founders, the scientists moving the field forward, and the forward deployed engineers turning breakthroughs into real-world outcomes. The decisions, the failures, the talent, and the human judgment shaping what comes next.Season 3 opens on Wednesday 16 September with Tom McLaughlin, a founding forward deployed engineer at The OpenAI Deployment Company, on the role every AI company is hiring for.Follow A Class Act wherever you get your podcasts so you don't miss an episode.A Class Act is hosted by Michael Young, Founder & CEO of MBN Solutions.Email: [email protected] Website: www.mbnsolutions.com

Most organisations adopting AI are bolting agentic AI onto the same old processes, then wondering why nothing actually changes.In this season 2 finale of A Class Act, Michael Young sits down with Stuart Bell, Head of AI & Innovation M&G who went from Java developer to shaping how some of the biggest regulated financial-services firms adopt agentic AI at enterprise scale. It’s a straight-talking, practical conversation about why the gap between a slick demo and real production is a strategy gap, why you should treat AI agents as products rather than one-off projects, and the question Stuart says every leader should be asking, and almost nobody is.What you’ll discover⬇️☑️Why starting from your existing process only ever gives you incremental AI☑️Why the demo-to-production gap is really a strategy gap (and the three reasons slick demos die)☑️What changes when you treat AI agents as products, not one-off projects☑️How to reframe guardrails from risk controls into UX metrics your teams actually want to hit☑️How to decide what to actually build when every business unit swears their use case comes first☑️The value-vs-complexity and risk-vs-reuse framework Stuart uses ☑️Why experimenting up front and benchmarking models protects you when the model underneath changes☑️What “responsible AI” really looks like when it’s working☑️Why governance done right lets you move faster, not slower☑️Stuart’s closing advice for any leader who wants to build agentic AI capabilityGuest Information⬇️Stuart Bell is Head of AI & Innovation at M&G, a senior AI leader shaping how large, regulated financial-services organisations adopt agentic AI at enterprise scale. He began his career as a Java developer before moving through software architecture into CTO positions across private-equity-backed and venture-backed businesses as well as large corporates, including a spell at Sky over a decade ago.Today he focuses on getting agentic AI out of the demo and into production, safely, inside a regulated environment.Connect with Stuart Bell on LinkedIn⬇️https://www.linkedin.com/in/stuart-bell-a355283/Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.About Your Host ⬇️Michael Young is the Founder & CEO of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Connect with MBN SolutionsIf you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.MBN Solutions on LinkedIn ⬇️ Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here: https://www.linkedin.com/company/mbn-recruitment-solutions/For questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions website at www.mbnsolutions.comSubscribe & Follow⬇️Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

In this episode of A Class Act, Michael Young sits down with Stuart McMeechan, EMEA Deployment Engineering Leader at OpenAI. Stuart leads the team that OpenAI sends into the biggest enterprises in Europe to help them get AI into production and he’s seen first-hand why most never make it past the pilot.In this conversation, they get into👇☑️ What OpenAI’s AI deployment engineering team actually does and the two objectives behind every project☑️ The three types of customer OpenAI works with☑️ The difference between organisations actually scaling enterprise AI versus those staying stuck in experimentation☑️ What’s really blocking the move from pilot to production (most of it isn’t technical)☑️ What separates organisations genuinely ready for AI from those just experimenting☑️ The culture changes required to make AI implementation actually work and how to find the “wizards” already driving AI inside your teams☑️ Where humans stay irreplaceable, and how roles are already being redrawn☑️ Is AI moving faster than organisations can adapt?☑️ Why OpenAI’s release cadence went from 15 months to six weeks and what that means for planningGuest Information👇Stuart McMeechan is EMEA Deployment Engineering Leader at OpenAI, where he leads a team of AI architects and engineers helping Europe’s largest enterprises adopt AI at scale. His team works directly with organisations to define AI strategy, design target architectures, build implementation approaches, and develop evaluation frameworks - turning OpenAI’s capabilities into real business impact.Connect with Stuart McMeechan on LinkedIn:https://www.linkedin.com/in/stuartmcmeechan/Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.About Your Host👇Michael Young is the Founder & CEO of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Connect with MBN Solutions👇If you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver. Visit MBN Solutions website at www.mbnsolutions.comMBN Solutions on LinkedIn – Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here: linkedin.com/company/mbn-recruitment-solutionsFor questions, guest recommendations, or to connect:Email: [email protected] & Follow👇Enjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.

In this episode of A Class Act, Michael sits down with Andy McMahon, Director of AI & MLOps Engineering at Barclays, Oxford lecturer, and author of Machine Learning Engineering with Python. Andy went from a physics PhD at Imperial College to leading AI engineering at one of the world’s largest banks, and he’s got a sharp take on why most AI never makes it out of the demo.In this conversation, they get into⬇️ ✔️Why the gap between AI that demos well and AI that works in production has never been wider✔️The 'trust infrastructure' most teams skip and why Andy calls them zero-regret investments ✔️What changed when AI engineering replaced MLOps as the paradigm and what stayed exactly the same ✔️How to spot genuinely good AI talent✔️Why imposter syndrome is a signal you're in the right place ✔️The shift from data science to AI engineering and what that means for hiring and team structure ✔️Andy's take on what people are getting wrong about AI right now ✔️Responsible AI in practice: how to make it real and not a tick-box exercise ✔️Building a career portfolio that outlasts any single role Guest InformationAndy McMahon is Director of AI & MLOps Engineering at Barclays, where he leads teams building production-grade AI systems across the bank. He holds a PhD in theoretical physics from Imperial College London and is the author of Machine Learning Engineering with Python (Packt), now writing the third edition — a rewrite shifting focus from MLOps to AI engineering. Andy lectures at the University of Oxford, has been named one of Computing Magazine's Top 100 Leaders in IT (2026), and co-writes Forward Deploy, a Substack on practical AI engineering with Matthew Higgs.Connect with Andy McMahon on LinkedIn:https://www.linkedin.com/in/andy-mcmahon/Read Forward Deploy on Substack:Forward Deploy SubstackPaper mentioned: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6843118 Podcast - https://linktr.ee/airightpodcastPlease note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.About Your HostMichael Young is the Managing Director of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Subscribe & FollowEnjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.Connect with MBN SolutionsIf you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.MBN Solutions on LinkedIn – Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Visit the company page here: linkedin.com/company/mbn-recruitment-solutionsFor questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions website at www.mbnsolutions.com

If you run a data team, you already know that the hardest part of being a great data leader isn’t always the technology.In this episode of A Class Act, host Michael Young chats with Asia Faulds, Head of Data Science at Booksy. Asia has built data science teams from the ground up at the BBC, Trustpilot, and now Booksy, and she’s seen first-hand why brilliant technical teams still fail when prioritisation breaks down.In this conversation, they get into:Why most data teams don’t fail technicallyWhat it’s actually like building a data science function from zero at BooksyHow Gen AI has expanded the scope of the data science role and what hasn’t changedWhy producing 200 dashboards instead of 2 doesn’t mean your team is more productiveThe difference between activity and progress, and how to tell which one your team is doingWhy sometimes a well-written SQL script beats a neural networkHow to protect your team’s energy and focus as a data leaderThe one thing Asia says every listener should do this weekGuest InformationAsia Faulds is Head of Data Science at Booksy, the two-sided marketplace connecting beauty and wellness providers with consumers. She’s building the company’s first data science and applied AI function from scratch, defining the strategy, hiring the team, and establishing ML infrastructure.Before Booksy, Asia spent five years at Trustpilot, progressing from individual contributor to management across product and go-to-market data science. Before that, she built recommendation engines for BBC Sounds at the BBC. She holds a Master’s in Physics from the University of Edinburgh and writes The Data Pragmatist on Medium.Connect with Asia Faulds on LinkedIn:https://www.linkedin.com/in/asia-data/Read The Data Pragmatist on Medium:medium.com/@thedatapragmatistAbout Your HostMichael Young is the Managing Director of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.Subscribe & FollowEnjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.Connect with MBN SolutionsIf you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.MBN Solutions on LinkedIn – Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here.For questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions website at www.mbnsolutions.com

In this episode of A Class Act, Michael chats with Stu Kennedy, an Edge, Realtime & AI Systems Consultant, core HTMX contributor, and former film composer who worked alongside David Arnold on the Chronicles of Narnia and BBC’s Sherlock. Today, Stu builds real-time voice AI pipelines, contributes to the WebSocket layer in HTMX 4, and has helped companies like Anam and Pyannote push the boundaries of streaming diarisation and video avatars. In this conversation, they get into:✔ How a career in maths, music, and film led to building production voice AI systems✔ Why voice AI is fundamentally an audio problem before it’s an ML one✔ Why platforms like VAPI, OpenAI Realtime, and others break outside demo✔ How Stu cut ASR latency from two seconds to 350 milliseconds ✔ Why a single senior engineer with the right tools can now outship a six-month procurement cycle✔ LLMs and the parallels between constraining a model and constraining an orchestra✔ An experiment where professional composers couldn’t tell a real orchestral recording from a fake one and what that really means for AI adoption✔ A real benchmark for production readinessGuest InformationStu Kennedy is an Edge, Realtime & AI Systems Consultant specialising in Cloudflare-native, real-time, and AI-driven platforms. He has spent 25 years at the intersection of mathematics, music, and software, from a PhD in fluid mechanics and chaos theory to composing for film alongside David Arnold (James Bond, Narnia, Sherlock), to building music technology platforms, and now engineering production voice AI pipelines. He is a core contributor to HTMX, building the WebSocket implementation for HTMX 4, and has worked with companies including Anam (real-time video avatars) and Pyannote (streaming diarization). Stu has also built products including Callwell, a real-time AI sales call assistant, and Medascend, an AI-powered medical training platform built with students from Dundee University. He operates via his Ltd company on scoped, outcome-based engagements.Connect with Stu Kennedy on LinkedIn:https://www.linkedin.com/in/stu-kennedy/Website: https://stukennedy.comAlso built: html.surfAbout Your HostMichael Young is the Managing Director of MBN Solutions and host of A Class Act: Conversations in Data & Leadership. With nearly two decades of experience helping organisations build high-performing data, analytics, and AI teams, he brings frontline insight into what makes exceptional talent and leadership.Please note: The views expressed by the guest in this episode are their own and do not reflect those of their current or former employers.Subscribe & FollowEnjoying the series? Don’t miss an episode. Follow A Class Act wherever you get your podcasts and leave us a review to help more listeners discover these conversations in data and leadership.Connect with MBN SolutionsIf you’re hiring for data or AI leadership roles, scaling AI capability, or rethinking how talent supports your AI strategy, the team at MBN partners with organisations to build data and AI teams that actually deliver.MBN Solutions on LinkedIn – Explore industry updates, groundbreaking projects, and the latest in data and analytics talent. Join the conversation and discover how MBN Solutions is shaping the future of data leadership. Visit the company page here.For questions, guest recommendations, or to connect:Email: [email protected] MBN Solutions website at www.mbnsolutions.com