Technauts: Innovation in practice

TransAlta lost $24 million from a single copy-paste error in a spreadsheet. More than 20 years of research shows that 88–94% of operational spreadsheets contain similar errors — baked into the structure and invisible to the people who built them.Excel is usually the first tool you reach for when you need to calculate, compare, or track something. The problem starts when it becomes your company's operating system: processes that were meant to live in a spreadsheet temporarily end up staying for years, and the whole thing depends on one person who knows it inside out.This episode looks at what really goes into the cost of running on Excel, what risks it creates, why companies wait so long to change, and how to figure out which processes to move first.Get the free AI assistant for process inventory.If you want to go deeper into a specific process, reach out. A 30-minute conversation is where we start — enough to understand your situation and figure out the next steps.

Most IT teams have good practices. The problem is they stick to them when there's time — and deadline pressure does the rest.In this episode, we talk about how we built Polaris at Inwedo — an internal quality standard for software delivery.Polaris came out of an uncomfortable finding during our ISO certification audit: our results depended more on who was on the project than on how we worked as a company. So we built a framework that doesn't impose a process — it gives teams a way to assess where they actually stand and decide what to change.If you manage IT projects or build technical teams, you'll find a concrete starting point here — not another theory about quality culture.📥 Free ebook with the full framework, audit guide, and real project examples 👉 https://inwedo.com/ebook-polaris-it-quality-standard/

How do you connect AI to the business systems already running in your organization — in a way that's stable, scalable and independent of which model you choose? So that each new AI initiative can launch faster, cost less and work with your existing processes. Is that even possible?Yes. Model Context Protocol is an open standard that does exactly this — it connects AI models to your existing systems through a single integration layer you can build on over time.In this episode we cover:what MCP actually is and how it works as a shared "conversation layer" between AI and business systemswhere MCP delivers the most value in practice — we walk through use cases across manufacturing, logistics, construction, IoT security and retailwhy point-to-point integrations slow down future projects — and how MCP changes thatwhat groundwork (especially around data) needs to happen first so integration is predictable and securewhat MCP implementation looks like step by step, without restructuring your entire IT architectureLearn more:➡️ Explore BridgeAI™ — the approach we use to implement MCP.➡️ If you want to assess whether your data and environment are ready for MCP, you can book a free Polaris audit. We offer two each month, and you'll receive a report with a prioritized action map within two weeks — no obligations.Book a free Polaris audit.

How can AI work with legacy systems—without costly overhauls?In this episode, we break down Model Context Protocol (MCP): a communication layer that connects AI with your existing systems. You’ll hear not only what MCP can do, but also where its limits are and how to prepare your data before connecting it.You’ll learn:Why most AI projects stall at proof of concept—and how MCP helps break that deadlock.What Model Context Protocol actually is and how it functions as a hub between AI and legacy systems.The limitations of MCP and what it cannot solve on its own.The business benefits of this integration model—from lower costs and risks to stronger data control.How rollout times shrink from weeks to days when MCP replaces brittle point-to-point integrations.Three practical ways to break data out of silos before plugging MCP in.MCP transforms legacy systems from dead weight into an active resource—accessible, consistent, and ready for AI.👉 Want to explore how this could work in your organization? Get in touch: inwedo.com/contact

Legacy applications still power the business—but their hidden costs and complexity block innovation. In this episode, we lay out a practical modernization playbook—from tactical quick wins through strategic re-platforming to full rebuilds—helping you weigh risk, cost, and impact while keeping day-to-day operations on track.✔ You’ll learn:why modernising can’t wait—even when “everything still works”how to frame a board-ready business case that shifts spend from upkeep to growththree modernisation routes—incremental tweaks, strategic re-platforming, or a full rebuild—and how to decide which fits best ways to weave security in from day one, not bolt it on later clear signals for when to lean on an external technology partner If you’re running systems that can’t go offline—but can’t stay stuck in the past—this episode is for you.Want a closer look at phased modernisation in your own environment? Explore Inwedo Continuum™ approach:https://inwedo.com/services/legacy-application-modernization/