package main // SpeakingBlock represents a single voiceover segment. type SpeakingBlock struct { Number int Slug string Step string Text string } // Script contains all speaking blocks for the pitch demo. // Rewritten for natural, conversational delivery. var Script = []SpeakingBlock{ // HOOK - Lead with the pain { Number: 1, Slug: "slide1-hook", Step: "Slide 1 Hook", Text: "In 2024, seventy-nine percent of FDA Warning Letters cited data integrity failures. The core issue? Companies couldn't reconstruct who did what, when, or why. The audit trail was missing.", }, { Number: 2, Slug: "slide1-reveal", Step: "Slide 1 Reveal", Text: "And now, with AI making more of the decisions, that audit trail matters more than ever.", }, // PROBLEM - Why this keeps happening { Number: 3, Slug: "slide2a", Step: "Slide 2a", Text: "Here's the thing about your data warehouse. It stores the current answer. But what happens when your sources don't actually agree?", }, { Number: 4, Slug: "slide2b", Step: "Slide 2b", Text: "When a study gets retracted, which decisions did it affect? Can you answer that question today?", }, { Number: 5, Slug: "slide2c", Step: "Slide 2c", Text: "Your AI recommended X. Can you reconstruct why it made that recommendation? For an auditor who's asking tough questions?", }, { Number: 6, Slug: "slide2-key", Step: "Slide 2 Key", Text: "Black box is a documented rejection reason at the FDA. And traditional databases? They overwrite history. Every update erases what came before.", }, // SOLUTION - Introducing StemeDB { Number: 7, Slug: "slide3", Step: "Slide 3", Text: "StemeDB is a knowledge graph that stores claims, not facts. It's append-only. It's auditable. And it's built specifically for regulated industries where the stakes are high.", }, // APPROACH - How it works { Number: 8, Slug: "slide4a", Step: "Slide 4a", Text: "When your sources disagree, you actually see that disagreement. It's not hidden. It's not swept under the rug. It's visible.", }, { Number: 9, Slug: "slide4b", Step: "Slide 4b", Text: "When a source gets retracted, you know exactly what's affected. In seconds. Not days of manual investigation.", }, { Number: 10, Slug: "slide4c", Step: "Slide 4c", Text: "And history is preserved. Nothing gets silently overwritten. Ever.", }, // CAPABILITIES { Number: 11, Slug: "slide5a", Step: "Slide 5a", Text: "Let me walk you through what this enables. First, conflict visibility. You see when sources disagree, with confidence scores that tell you how much.", }, { Number: 12, Slug: "slide5b", Step: "Slide 5b", Text: "Second, cascade invalidation. You retract a source, and instantly see every downstream decision it affected.", }, { Number: 13, Slug: "slide5c", Step: "Slide 5c", Text: "Third, a complete audit trail. Every query is logged with full provenance. Ready to export for regulators.", }, { Number: 14, Slug: "slide5-reveal", Step: "Slide 5 Reveal", Text: "And time-travel queries. You can ask: what did we believe on January first? And get the exact answer from that point in time.", }, // SOCIAL PROOF { Number: 15, Slug: "slide6", Step: "Slide 6", Text: "The FDA has now authorized over twelve hundred AI-enabled devices. Every single one of them requires an audit trail. Let me show you what compliance actually looks like.", }, // DEMO - Conflict Visibility { Number: 16, Slug: "demo1a", Step: "Demo 1a", Text: "I'm querying semaglutide gastroparesis risk. Notice the status says Contested. This immediately tells your analyst there's no clean answer here. Different sources are saying different things.", }, { Number: 17, Slug: "demo1b", Step: "Demo 1b", Text: "Look at the weight distribution. FDA clinical trial data says 0.2 percent incidence. But patient reports are saying something different. Both are visible. Both have sources you can trace.", }, { Number: 18, Slug: "demo1c", Step: "Demo 1c", Text: "Most databases would give you the FDA number and call it done. We show you the disagreement. Your medical affairs team can investigate before it becomes a problem. Nobody gets blindsided.", }, { Number: 19, Slug: "demo1-amaze", Step: "Demo 1 Amaze", Text: "This isn't a recommendation from a black box. This is a recommendation with a complete evidence chain that you can trace back to every source.", }, // DEMO - Audit Trail { Number: 20, Slug: "demo2a", Step: "Demo 2a", Text: "Every query. Every agent. Every decision. It's all logged. Click any entry and you see exactly which assertions contributed to that decision.", }, { Number: 21, Slug: "demo2-amaze", Step: "Demo 2 Amaze", Text: "Audit response time drops dramatically. What used to require manual log archaeology is now a single click.", }, // DEMO - Cascade Invalidation { Number: 22, Slug: "demo3a", Step: "Demo 3a", Text: "Here's a real FDA label. Over a hundred assertions in the system cite it as a source. Now imagine: the agency updates this label tomorrow morning with new safety data. What do you do?", }, { Number: 23, Slug: "demo3b", Step: "Demo 3b", Text: "A JAMA study found that devices cleared using predicates with recall history had six point four times higher risk of future Class I recalls. When you can't trace which sources supported which decisions, you inherit that risk silently.", }, { Number: 24, Slug: "demo3c", Step: "Demo 3c", Text: "One click. Preview Impact. Here's every decision that relied on this source. Your team can review them in priority order before anything goes wrong.", }, { Number: 25, Slug: "demo3-amaze", Step: "Demo 3 Amaze", Text: "Time to identify impact goes from days to seconds.", }, // DEMO - Time Travel { Number: 26, Slug: "demo4", Step: "Demo 4", Text: "A patient had an adverse event eight months ago. Their attorney asks: what information was available to your system at that time? Can you reconstruct that state? We can. This is the exact state of the knowledge graph on that specific date.", }, { Number: 27, Slug: "demo4-amaze", Step: "Demo 4 Amaze", Text: "Point-in-time reconstruction is native. It's not a manual archaeology project. It's a query parameter.", }, // DEMO - Trust & Safety { Number: 28, Slug: "demo5a", Step: "Demo 5a", Text: "What happens when things go wrong? Let's say someone tries to inject high-confidence assertions without proper credentials. A new agent claiming ninety-five percent confidence on a safety claim? That's suspicious. It goes to the review queue, not production. Humans decide.", }, { Number: 29, Slug: "demo5-amaze", Step: "Demo 5 Amaze", Text: "Your knowledge base cannot be poisoned. And when something gets blocked, you know about it.", }, // CLOSE { Number: 30, Slug: "return-bridge", Step: "Return Bridge", Text: "That's the core of what StemeDB does. Conflict visibility. Cascade invalidation. Complete audit trails. Time travel. And trust controls. Questions?", }, }