{
  "$mulmocast": {
    "version": "1.1"
  },
  "lang": "en",
  "title": "Sample Presentation",
  "canvasSize": {
    "width": 1536,
    "height": 1024
  },
  "beats": [
    {
      "text": "sectionDividerSlide",
      "image": {
        "type": "vision",
        "style": "sectionDividerSlide",
        "data": {
          "heading": "How AI Is Reshaping Referencing",
          "subheading": "From sources to systems: reliability, traceability, and credit in the age of models"
        }
      }
    },
    {
      "text": "agendaSlide",
      "image": {
        "type": "vision",
        "style": "agendaSlide",
        "data": {
          "title": "Agenda",
          "items": [
            "Executive summary",
            "Reference reliability and hallucinations",
            "Attribution and credit in AI workflows",
            "Standards & compliance (academia, journalism, law)",
            "Roadmap & recommendations"
          ]
        }
      }
    },
    {
      "text": "executiveSummarySlide",
      "image": {
        "type": "vision",
        "style": "executiveSummarySlide",
        "data": {
          "title": "Executive Summary",
          "bullets": [
            "AI accelerates discovery but introduces novel risks in citation accuracy and provenance.",
            "RAG and structured retrieval reduce hallucinations when sources are governed and auditable.",
            "Attribution standards are emerging; early adoption lowers legal and reputational exposure.",
            "Watermarking and signed citations enable verifiable chains of reference.",
            "Organizations need policy, training, and tooling to ensure traceable, compliant referencing."
          ]
        }
      }
    },
    {
      "text": "keyMessageWithSupportsSlide",
      "image": {
        "type": "vision",
        "style": "keyMessageWithSupportsSlide",
        "data": {
          "headline": "Trustworthy referencing is a prerequisite for AI at scale.",
          "supports": [
            "Stakeholders require verifiable provenance for critical decisions.",
            "Standards (e.g., citations, licensing) are uneven across industries.",
            "Tooling gaps persist between LLM outputs and enterprise compliance systems."
          ]
        }
      }
    },
    {
      "text": "hypothesisSlide",
      "image": {
        "type": "vision",
        "style": "hypothesisSlide",
        "data": {
          "hypothesis": "Firms that implement verifiable AI referencing will reduce risk and accelerate adoption.",
          "implications": [
            "Lower legal exposure on copyright and misinformation claims.",
            "Faster audit cycles through machine-readable provenance.",
            "Higher user confidence and usage in knowledge-heavy workflows."
          ],
          "nextSteps": [
            "Deploy governed retrieval with source whitelists.",
            "Adopt signed citations and immutable logs for high-stakes outputs.",
            "Train users on prompt patterns that preserve attribution."
          ]
        }
      }
    },
    {
      "text": "issueTreeSlide",
      "image": {
        "type": "vision",
        "style": "issueTreeSlide",
        "data": {
          "rootIssue": "How to ensure accurate, compliant AI referencing?",
          "branches": [
            ["Provenance capture", "Source governance", "Traceability"],
            ["Legal & licensing", "Attribution norms", "Fair use boundaries"],
            ["User behavior", "Training & prompts", "Review workflows"]
          ]
        }
      }
    },
    {
      "text": "driverTreeSlide",
      "image": {
        "type": "vision",
        "style": "driverTreeSlide",
        "data": {
          "metric": "Reference accuracy rate (%)",
          "drivers": [
            ["Governed corpus coverage", "Retriever quality", "Index freshness"],
            ["Citation rendering logic", "Signed-source support", "Reviewer adherence"],
            ["User prompt hygiene", "Auto-evidence insertion", "UI nudges"]
          ]
        }
      }
    },
    {
      "text": "meceListSlide",
      "image": {
        "type": "vision",
        "style": "meceListSlide",
        "data": {
          "title": "MECE: Reference Risk Areas",
          "groups": [
            {
              "label": "Technical",
              "items": ["Hallucinations", "Retriever gaps", "Version drift"]
            },
            {
              "label": "Legal",
              "items": ["Copyright", "Licensing", "Privacy & PII"]
            },
            {
              "label": "Operational",
              "items": ["Review latency", "Policy ambiguity", "Training gaps"]
            }
          ]
        }
      }
    },
    {
      "text": "pyramidPrincipleSlide",
      "image": {
        "type": "vision",
        "style": "pyramidPrincipleSlide",
        "data": {
          "keyMessage": "Verifiable references unlock safe, scalable AI adoption.",
          "supports": ["Reduces legal and reputational risk", "Improves stakeholder confidence", "Shortens audit cycles"],
          "details": [
            ["Use source whitelists", "Track doc versions", "Sign evidence blobs"],
            ["Expose citations in UI", "Link to canonical sources", "Store prompts & context"],
            ["Automate QA sampling", "Monitor reference KPIs", "Escalate anomalies"]
          ]
        }
      }
    },
    {
      "text": "scqaSlide",
      "image": {
        "type": "vision",
        "style": "scqaSlide",
        "data": {
          "situation": "Teams increasingly rely on AI to synthesize knowledge and draft outputs.",
          "complication": "AI can misattribute or fabricate sources, risking credibility and compliance.",
          "question": "How can we ensure references are accurate, traceable, and compliant?",
          "answer": "Standardize governed retrieval, signed citations, and review workflows integrated into authoring tools."
        }
      }
    },
    {
      "text": "swotSlide",
      "image": {
        "type": "vision",
        "style": "swotSlide",
        "data": {
          "strengths": ["Speed of synthesis", "Scalable drafting", "Broad corpus reach"],
          "weaknesses": ["Hallucinations", "Opaque provenance", "Reviewer overload"],
          "opportunities": ["New evidence UX", "Standardized attribution", "Automated audits"],
          "threats": ["Regulatory fines", "Misinformation", "IP disputes"]
        }
      }
    },
    {
      "text": "threeCSlide",
      "image": {
        "type": "vision",
        "style": "threeCSlide",
        "data": {
          "company": ["Commit to verifiable AI outputs", "Invest in governed retrieval"],
          "customer": ["Needs trustworthy citations", "Wants explorable sources"],
          "competitor": ["Adopting reference-safe workflows", "Marketing 'trust' as a differentiator"]
        }
      }
    },
    {
      "text": "fourPSlide",
      "image": {
        "type": "vision",
        "style": "fourPSlide",
        "data": {
          "product": ["Reference-safe AI assistant", "Evidence panel", "Citation export"],
          "price": ["Tiered by audit features", "Enterprise compliance add-ons"],
          "place": ["Browser extension", "Docs add-in", "APIs"],
          "promotion": ["Risk reduction ROI", "Case studies", "Compliance partnerships"]
        }
      }
    },
    {
      "text": "sevenSSlide",
      "image": {
        "type": "vision",
        "style": "sevenSSlide",
        "data": {
          "strategy": "Make 'trustworthy references' a core AI value prop",
          "structure": "Central knowledge governance with federated champions",
          "systems": "RAG, signing, audit logs integrated in content tools",
          "sharedValues": "Truth, transparency, accountability",
          "skills": "Prompting, retrieval tuning, compliance literacy",
          "style": "Evidence-first culture",
          "staff": "Knowledge stewards, AI librarians, compliance reviewers"
        }
      }
    },
    {
      "text": "valueChainSlide",
      "image": {
        "type": "vision",
        "style": "valueChainSlide",
        "data": {
          "primary": ["Ingestion", "Indexing", "Retrieval", "Generation", "Review", "Publication"],
          "support": ["Governance", "Security", "Compliance", "Training", "Monitoring"]
        }
      }
    },
    {
      "text": "porterFiveForcesSlide",
      "image": {
        "type": "vision",
        "style": "porterFiveForcesSlide",
        "data": {
          "newEntrants": ["AI-first doc tools", "Verification startups"],
          "suppliers": ["Model providers", "Content licensors"],
          "buyers": ["Enterprises", "Universities", "Newsrooms"],
          "substitutes": ["Manual research", "Traditional search-only"],
          "rivalry": ["Platform ecosystems", "Vertical specialists"]
        }
      }
    },
    {
      "text": "businessModelCanvasSlide",
      "image": {
        "type": "vision",
        "style": "businessModelCanvasSlide",
        "data": {
          "blocks": {
            "Key Partners": ["Model vendors", "Content platforms", "Auditors"],
            "Key Activities": ["Indexing", "Retrieval", "Signing", "QA"],
            "Key Resources": ["Curated corpora", "Embeddings index", "Audit logs"],
            "Value Propositions": ["Trustworthy AI outputs", "Time saved", "Reduced risk"],
            "Customer Relationships": ["Embedded in workflows", "SLAs"],
            "Channels": ["Add-ins", "APIs", "Marketplace"],
            "Customer Segments": ["Legal", "Research", "Editorial"],
            "Cost Structure": ["Compute", "Licenses", "Review ops"],
            "Revenue Streams": ["Seats", "Usage", "Compliance tier"]
          }
        }
      }
    },
    {
      "text": "customerJourneySlide",
      "image": {
        "type": "vision",
        "style": "customerJourneySlide",
        "data": {
          "stages": ["Discover", "Draft", "Verify", "Publish", "Audit"],
          "touchpoints": [
            ["Search UI", "Corpus filters"],
            ["Editor plugin", "Reference panel"],
            ["Reviewer queue", "Signed citations"],
            ["Export formats", "Permalinks"],
            ["Randomized QA", "Dashboards"]
          ]
        }
      }
    },
    {
      "text": "stakeholderMapSlide",
      "image": {
        "type": "vision",
        "style": "stakeholderMapSlide",
        "data": {
          "stakeholders": [
            {
              "style": "Legal",
              "influence": 9,
              "interest": 8,
              "notes": "Reduce liability"
            },
            {
              "style": "Editorial",
              "influence": 7,
              "interest": 9,
              "notes": "Protect credibility"
            },
            {
              "style": "Engineering",
              "influence": 8,
              "interest": 7,
              "notes": "Build RAG & signing"
            },
            {
              "style": "End users",
              "influence": 6,
              "interest": 10,
              "notes": "Need clarity & speed"
            }
          ]
        }
      }
    },
    {
      "text": "raciSlide",
      "image": {
        "type": "vision",
        "style": "raciSlide",
        "data": {
          "tasks": ["Define policy", "Implement RAG", "Roll out training", "Monitor KPIs"],
          "roles": ["Legal", "Engineering", "L&D", "Ops"],
          "assignments": [
            ["A", "R", "C", "I"],
            ["C", "A/R", "I", "I"],
            ["I", "C", "A/R", "I"],
            ["C", "R", "I", "A"]
          ]
        }
      }
    },
    {
      "text": "okrKpiDashboardSlide",
      "image": {
        "type": "vision",
        "style": "okrKpiDashboardSlide",
        "data": {
          "title": "Reference Quality KPIs",
          "metrics": [
            {
              "label": "Reference accuracy",
              "value": "97%",
              "target": "≥95%",
              "status": "On track"
            },
            {
              "label": "Signed citation coverage",
              "value": "82%",
              "target": "≥80%",
              "status": "On track"
            },
            {
              "label": "Reviewer SLA",
              "value": "4h",
              "target": "≤6h",
              "status": "On track"
            }
          ]
        }
      }
    },
    {
      "text": "balancedScorecardSlide",
      "image": {
        "type": "vision",
        "style": "balancedScorecardSlide",
        "data": {
          "perspectives": [
            {
              "style": "Financial",
              "items": ["Reduce rework costs", "Avoid penalties"]
            },
            {
              "style": "Customer",
              "items": ["Trust score ↑", "NPS ↑"]
            },
            {
              "style": "Internal",
              "items": ["QA automation", "Corpus governance"]
            },
            {
              "style": "Learning & Growth",
              "items": ["Reviewer upskilling", "Prompt playbooks"]
            }
          ]
        }
      }
    },
    {
      "text": "quarterlyRoadmapSlide",
      "image": {
        "type": "vision",
        "style": "quarterlyRoadmapSlide",
        "data": {
          "quarters": ["Q1", "Q2", "Q3", "Q4"],
          "items": [
            {
              "quarter": "Q1",
              "label": "Policy & baseline KPIs"
            },
            {
              "quarter": "Q2",
              "label": "Signed citations rollout"
            },
            {
              "quarter": "Q3",
              "label": "Reviewer workflow automation"
            },
            {
              "quarter": "Q4",
              "label": "External audits & certification"
            }
          ]
        }
      }
    },
    {
      "text": "milestoneTimelineSlide",
      "image": {
        "type": "vision",
        "style": "milestoneTimelineSlide",
        "data": {
          "title": "Implementation Timeline",
          "milestones": [
            {
              "label": "Policy approved",
              "date": "2025-02-01",
              "notes": "Exec sign-off"
            },
            {
              "label": "RAG MVP live",
              "date": "2025-04-15",
              "notes": "Limited corpus"
            },
            {
              "label": "Signed citations",
              "date": "2025-06-30",
              "notes": "Tier-1 content"
            },
            {
              "label": "Audit-ready",
              "date": "2025-09-30",
              "notes": "Dashboards & sampling"
            }
          ]
        }
      }
    },
    {
      "text": "ganttSimpleSlide",
      "image": {
        "type": "vision",
        "style": "ganttSimpleSlide",
        "data": {
          "tasks": [
            {
              "style": "Policy drafting",
              "start": "2025-01-05",
              "end": "2025-02-01"
            },
            {
              "style": "RAG build",
              "start": "2025-02-05",
              "end": "2025-04-15"
            },
            {
              "style": "Signing & logs",
              "start": "2025-04-01",
              "end": "2025-06-30"
            },
            {
              "style": "Reviewer ops",
              "start": "2025-05-15",
              "end": "2025-08-01"
            }
          ]
        }
      }
    },
    {
      "text": "waterfallSlide",
      "image": {
        "type": "vision",
        "style": "waterfallSlide",
        "data": {
          "title": "Time Savings from AI Referencing (hrs/month)",
          "steps": [
            {
              "label": "Baseline (manual search)",
              "value": 0
            },
            {
              "label": "RAG-enabled drafting",
              "value": 120
            },
            {
              "label": "Signed citations",
              "value": 160
            },
            {
              "label": "Automated QA",
              "value": 190
            }
          ]
        }
      }
    },
    {
      "text": "funnelSlide",
      "image": {
        "type": "vision",
        "style": "funnelSlide",
        "data": {
          "stages": [
            {
              "label": "Drafts created",
              "value": 1000
            },
            {
              "label": "Drafts with citations",
              "value": 850
            },
            {
              "label": "Signed citations",
              "value": 700
            },
            {
              "label": "Approved & published",
              "value": 630
            }
          ]
        }
      }
    },
    {
      "text": "twoByTwoMatrixSlide",
      "image": {
        "type": "vision",
        "style": "twoByTwoMatrixSlide",
        "data": {
          "xAxis": "Evidence depth",
          "yAxis": "Ease of use",
          "quadrants": [["Scholarly databases"], ["AI assistants with signing"], ["Raw web search"], ["Legacy manual workflows"]]
        }
      }
    },
    {
      "text": "bcgMatrixSlide",
      "image": {
        "type": "vision",
        "style": "bcgMatrixSlide",
        "data": {
          "stars": ["Signed-citation AI editors"],
          "cashCows": ["Governed enterprise search"],
          "questionMarks": ["Generative browsers"],
          "dogs": ["Unverified copy-paste tools"]
        }
      }
    },
    {
      "text": "geMcKinseyMatrixSlide",
      "image": {
        "type": "vision",
        "style": "geMcKinseyMatrixSlide",
        "data": {
          "industryAttractiveness": ["Regulatory clarity", "IP-safe corpora", "Audit tooling"],
          "competitiveStrength": ["Corpus quality", "Model integration", "Compliance features"],
          "placements": [
            {
              "style": "Signed AI editor",
              "row": 0,
              "col": 2
            },
            {
              "style": "Generic chatbot",
              "row": 1,
              "col": 1
            },
            {
              "style": "Manual search",
              "row": 2,
              "col": 0
            }
          ]
        }
      }
    },
    {
      "text": "marimekkoPlaceholderSlide",
      "image": {
        "type": "vision",
        "style": "marimekkoPlaceholderSlide",
        "data": {
          "title": "Content Types by Share & Effort",
          "categories": ["Academic", "News", "Internal docs", "Web"]
        }
      }
    },
    {
      "text": "bubbleChartPlaceholderSlide",
      "image": {
        "type": "vision",
        "style": "bubbleChartPlaceholderSlide",
        "data": {
          "title": "Risk vs Impact vs Adoption",
          "points": [
            {
              "label": "Legal memos",
              "x": 8,
              "y": 9,
              "r": 20
            },
            {
              "label": "Blog posts",
              "x": 4,
              "y": 5,
              "r": 15
            },
            {
              "label": "Research briefs",
              "x": 7,
              "y": 7,
              "r": 18
            }
          ]
        }
      }
    },
    {
      "text": "heatmapPlaceholderSlide",
      "image": {
        "type": "vision",
        "style": "heatmapPlaceholderSlide",
        "data": {
          "rows": ["Teams"],
          "cols": ["Accuracy", "Provenance", "Speed", "Compliance"],
          "values": [[8, 7, 9, 6]]
        }
      }
    },
    {
      "text": "kpiHighlightSlide",
      "image": {
        "type": "vision",
        "style": "kpiHighlightSlide",
        "data": {
          "title": "KPI Highlights",
          "kpis": [
            {
              "label": "Reference Accuracy",
              "value": "97%",
              "delta": "+2pp"
            },
            {
              "label": "Signed Coverage",
              "value": "82%",
              "delta": "+5pp"
            },
            {
              "label": "Audit Exceptions",
              "value": "1.2%",
              "delta": "-0.4pp"
            }
          ]
        }
      }
    },
    {
      "text": "beforeAfterSlide",
      "image": {
        "type": "vision",
        "style": "beforeAfterSlide",
        "data": {
          "title": "Before vs After AI Referencing",
          "before": ["Manual searches", "Inconsistent citations", "Slow audits"],
          "after": ["Governed retrieval", "Standardized citations", "Signed evidence"]
        }
      }
    },
    {
      "text": "optionEvaluationSlide",
      "image": {
        "type": "vision",
        "style": "optionEvaluationSlide",
        "data": {
          "criteria": ["Accuracy", "Latency", "Compliance", "Cost"],
          "options": ["Generic chatbot", "RAG + signing", "Manual review"],
          "scores": [
            [5, 7, 9, 6],
            [8, 7, 9, 7],
            [9, 3, 10, 4]
          ]
        }
      }
    },
    {
      "text": "riskMitigationSlide",
      "image": {
        "type": "vision",
        "style": "riskMitigationSlide",
        "data": {
          "risks": [
            {
              "risk": "Misattribution",
              "impact": "High",
              "likelihood": "Medium",
              "mitigation": "Signed citations + review"
            },
            {
              "risk": "Copyright claims",
              "impact": "High",
              "likelihood": "Low",
              "mitigation": "Licensed corpora + filters"
            },
            {
              "risk": "PII leakage",
              "impact": "High",
              "likelihood": "Low",
              "mitigation": "Redaction + policy"
            }
          ]
        }
      }
    },
    {
      "text": "positioningMapSlide",
      "image": {
        "type": "vision",
        "style": "positioningMapSlide",
        "data": {
          "xAxis": "Compliance readiness",
          "yAxis": "User adoption",
          "players": [
            {
              "style": "AI Editor (signed)",
              "x": 8,
              "y": 8
            },
            {
              "style": "Generic chatbot",
              "x": 4,
              "y": 7
            },
            {
              "style": "Manual research",
              "x": 9,
              "y": 4
            }
          ]
        }
      }
    },
    {
      "text": "tamSamSomSlide",
      "image": {
        "type": "vision",
        "style": "tamSamSomSlide",
        "data": {
          "tam": 50000000000,
          "sam": 12000000000,
          "som": 3000000000,
          "notes": "Knowledge-heavy enterprises, academia, and media markets."
        }
      }
    },
    {
      "text": "marketDriversSlide",
      "image": {
        "type": "vision",
        "style": "marketDriversSlide",
        "data": {
          "title": "Market Growth Drivers",
          "drivers": ["Regulatory push for provenance", "Enterprise AI adoption", "Cost pressure to automate reviews"]
        }
      }
    },
    {
      "text": "revenueModelSlide",
      "image": {
        "type": "vision",
        "style": "revenueModelSlide",
        "data": {
          "streams": ["Seats", "Usage", "Compliance add-on"],
          "pricingNotes": "Discounts for academic & nonprofit segments with strict compliance needs."
        }
      }
    },
    {
      "text": "costStructureSlide",
      "image": {
        "type": "vision",
        "style": "costStructureSlide",
        "data": {
          "buckets": ["Compute", "Licenses", "Storage", "Review ops"],
          "fixedVsVariable": ["Fixed: platform & storage", "Variable: compute & review time"]
        }
      }
    },
    {
      "text": "orgChartSlide",
      "image": {
        "type": "vision",
        "style": "orgChartSlide",
        "data": {
          "nodes": [
            {
              "id": "1",
              "label": "Head of Knowledge Governance",
              "parentId": ""
            },
            {
              "id": "2",
              "label": "AI Librarian",
              "parentId": "1"
            },
            {
              "id": "3",
              "label": "Compliance Reviewer",
              "parentId": "1"
            }
          ]
        }
      }
    },
    {
      "text": "capabilityMaturitySlide",
      "image": {
        "type": "vision",
        "style": "capabilityMaturitySlide",
        "data": {
          "capabilities": [
            {
              "style": "Provenance capture",
              "level": 3
            },
            {
              "style": "Signing & verification",
              "level": 2
            },
            {
              "style": "Reviewer workflow",
              "level": 4
            }
          ]
        }
      }
    },
    {
      "text": "techRoadmapSlide",
      "image": {
        "type": "vision",
        "style": "techRoadmapSlide",
        "data": {
          "phases": ["MVP", "Scale", "Certify"],
          "items": [
            {
              "phase": "MVP",
              "label": "Governed RAG"
            },
            {
              "phase": "Scale",
              "label": "Signed citations"
            },
            {
              "phase": "Certify",
              "label": "External audits"
            }
          ]
        }
      }
    },
    {
      "text": "digitalMaturitySlide",
      "image": {
        "type": "vision",
        "style": "digitalMaturitySlide",
        "data": {
          "dimensions": ["Data", "Process", "People", "Tech"],
          "levels": [3, 3, 2, 4],
          "notes": "Prioritize training and governance backlog."
        }
      }
    },
    {
      "text": "ecosystemMapSlide",
      "image": {
        "type": "vision",
        "style": "ecosystemMapSlide",
        "data": {
          "categories": ["Models", "Content", "Tooling", "Auditors"],
          "entities": [
            {
              "category": "Models",
              "style": "General LLMs"
            },
            {
              "category": "Content",
              "style": "Licensed databases"
            },
            {
              "category": "Tooling",
              "style": "Signing libraries"
            },
            {
              "category": "Auditors",
              "style": "External firms"
            }
          ]
        }
      }
    },
    {
      "text": "changeCurveSlide",
      "image": {
        "type": "vision",
        "style": "changeCurveSlide",
        "data": {
          "stages": ["Awareness", "Understanding", "Adoption", "Advocacy"],
          "notes": "Evidence-first culture requires incentives and leadership modeling."
        }
      }
    },
    {
      "text": "communicationPlanSlide",
      "image": {
        "type": "vision",
        "style": "communicationPlanSlide",
        "data": {
          "audiences": ["Executives", "Managers", "Contributors"],
          "channels": ["Town halls", "Docs add-in tips", "Slack nudges"],
          "cadence": "Bi-weekly updates for first two quarters"
        }
      }
    },
    {
      "text": "integrationPlanSlide",
      "image": {
        "type": "vision",
        "style": "integrationPlanSlide",
        "data": {
          "workstreams": ["Tech", "Policy", "Training", "Ops"],
          "milestones": ["MVP live", "Org-wide training", "Audit pilot"]
        }
      }
    },
    {
      "text": "benchmarkingTableSlide",
      "image": {
        "type": "vision",
        "style": "benchmarkingTableSlide",
        "data": {
          "metrics": ["Accuracy", "Provenance", "Latency", "Cost"],
          "competitors": ["Manual", "Generic chatbot", "Signed AI editor"]
        }
      }
    },
    {
      "text": "surveyResultsSlide",
      "image": {
        "type": "vision",
        "style": "surveyResultsSlide",
        "data": {
          "questions": ["Do you trust AI references?", "Is evidence easy to review?"],
          "summaries": ["Trust increased post-signing rollout.", "Review time dropped by 35%."]
        }
      }
    },
    {
      "text": "personasSlide",
      "image": {
        "type": "vision",
        "style": "personasSlide",
        "data": {
          "personas": [
            {
              "style": "Researcher",
              "bio": "Synthesizes reports daily",
              "needs": ["Accurate citations", "Deep sources"]
            },
            {
              "style": "Editor",
              "bio": "Approves publications",
              "needs": ["Fast verification", "Audit trail"]
            }
          ]
        }
      }
    },
    {
      "text": "segmentationSlide",
      "image": {
        "type": "vision",
        "style": "segmentationSlide",
        "data": {
          "segments": ["Academic", "Enterprise", "Media"],
          "descriptors": ["Risk tolerance", "Compliance needs", "Speed expectations"]
        }
      }
    },
    {
      "text": "pricingWaterfallSlide",
      "image": {
        "type": "vision",
        "style": "pricingWaterfallSlide",
        "data": {
          "steps": [
            {
              "label": "List price",
              "value": 100
            },
            {
              "label": "Compliance discount",
              "value": -15
            },
            {
              "label": "Volume discount",
              "value": -10
            },
            {
              "label": "Final",
              "value": 75
            }
          ]
        }
      }
    },
    {
      "text": "sensitivityAnalysisSlide",
      "image": {
        "type": "vision",
        "style": "sensitivityAnalysisSlide",
        "data": {
          "variables": ["Corpus coverage", "Reviewer time", "Compute cost"],
          "scenarios": ["Best case", "Expected", "Stress"]
        }
      }
    },
    {
      "text": "pLBreakdownSlide",
      "image": {
        "type": "vision",
        "style": "pLBreakdownSlide",
        "data": {
          "categories": ["Revenue", "COGS", "Opex"],
          "values": [20, 8, 6]
        }
      }
    },
    {
      "text": "cashFlowSlide",
      "image": {
        "type": "vision",
        "style": "cashFlowSlide",
        "data": {
          "inflows": [8, 10, 12, 14],
          "outflows": [6, 7, 8, 9]
        }
      }
    },
    {
      "text": "balanceSheetSlide",
      "image": {
        "type": "vision",
        "style": "balanceSheetSlide",
        "data": {
          "assets": ["Cash", "Intangibles", "Receivables"],
          "liabilities": ["Deferred revenue", "Accounts payable"],
          "equity": ["Paid-in capital", "Retained earnings"]
        }
      }
    },
    {
      "text": "shareholderValueTreeSlide",
      "image": {
        "type": "vision",
        "style": "shareholderValueTreeSlide",
        "data": {
          "drivers": ["Adoption", "Retention", "Compliance premium"]
        }
      }
    },
    {
      "text": "npvSummarySlide",
      "image": {
        "type": "vision",
        "style": "npvSummarySlide",
        "data": {
          "npv": 12500000,
          "assumptions": ["3-year horizon", "10% discount rate", "Compliance uplift included"]
        }
      }
    },
    {
      "text": "scenarioPlanningSlide",
      "image": {
        "type": "vision",
        "style": "scenarioPlanningSlide",
        "data": {
          "scenarios": ["Tight regulation", "Moderate", "Self-regulation"],
          "impacts": ["Higher audit cost", "Balanced investment", "Faster rollout"]
        }
      }
    },
    {
      "text": "complianceHeatmapSlide",
      "image": {
        "type": "vision",
        "style": "complianceHeatmapSlide",
        "data": {
          "areas": ["Copyright", "Privacy", "Disclosure"],
          "levels": ["Green", "Amber", "Red"]
        }
      }
    },
    {
      "text": "esgFrameworkSlide",
      "image": {
        "type": "vision",
        "style": "esgFrameworkSlide",
        "data": {
          "environmental": ["Efficient compute", "Green datacenters"],
          "social": ["Source credit", "Anti-bias reviews"],
          "governance": ["Audit logs", "Policy oversight"]
        }
      }
    },
    {
      "text": "csrInitiativesSlide",
      "image": {
        "type": "vision",
        "style": "csrInitiativesSlide",
        "data": {
          "initiatives": ["Open citations to public research", "Academic partnerships"]
        }
      }
    },
    {
      "text": "sustainabilityRoadmapSlide",
      "image": {
        "type": "vision",
        "style": "sustainabilityRoadmapSlide",
        "data": {
          "phases": ["Measure", "Reduce", "Offset"],
          "actions": ["Track energy per query", "Optimize inference", "Offset remaining"]
        }
      }
    },
    {
      "text": "circularEconomyMapSlide",
      "image": {
        "type": "vision",
        "style": "circularEconomyMapSlide",
        "data": {
          "loops": ["Data ingestion", "Use", "Feedback", "Curation"]
        }
      }
    },
    {
      "text": "innovationFunnelSlide",
      "image": {
        "type": "vision",
        "style": "innovationFunnelSlide",
        "data": {
          "stages": ["Ideas", "Prototypes", "Pilots", "Scale"],
          "counts": [120, 24, 8, 3]
        }
      }
    },
    {
      "text": "productRoadmapSlide",
      "image": {
        "type": "vision",
        "style": "productRoadmapSlide",
        "data": {
          "releases": ["R1", "R2", "R3"],
          "items": [
            {
              "release": "R1",
              "label": "Evidence panel"
            },
            {
              "release": "R2",
              "label": "Signed citations"
            },
            {
              "release": "R3",
              "label": "Reviewer automation"
            }
          ]
        }
      }
    },
    {
      "text": "launchPlanSlide",
      "image": {
        "type": "vision",
        "style": "launchPlanSlide",
        "data": {
          "workstreams": ["Marketing", "Sales", "Success"],
          "milestones": ["Beta cohort", "GA", "Case studies"],
          "risks": ["Overpromise", "Adoption lag", "Change resistance"]
        }
      }
    },
    {
      "text": "pipelineFunnelSlide",
      "image": {
        "type": "vision",
        "style": "pipelineFunnelSlide",
        "data": {
          "stages": ["Leads", "Qualified", "Trials", "Paid"],
          "values": [400, 220, 120, 60]
        }
      }
    },
    {
      "text": "salesDashboardSlide",
      "image": {
        "type": "vision",
        "style": "salesDashboardSlide",
        "data": {
          "metrics": ["Win rate 32%", "Cycle time 48d", "Avg deal $85k"],
          "notes": "Education on value of signed references shortens cycles."
        }
      }
    },
    {
      "text": "marketingMixSlide",
      "image": {
        "type": "vision",
        "style": "marketingMixSlide",
        "data": {
          "levers": ["Content marketing", "Compliance webinars", "Partner co-sell", "Analyst briefings"],
          "notes": "Lead with risk reduction and measurable trust."
        }
      }
    },
    {
      "text": "customerSuccessJourneySlide",
      "image": {
        "type": "vision",
        "style": "customerSuccessJourneySlide",
        "data": {
          "stages": ["Onboard", "Adopt", "Expand", "Renew"],
          "metrics": ["Time-to-value", "Feature usage", "CSAT", "Renewal rate"]
        }
      }
    },
    {
      "text": "supportOrgModelSlide",
      "image": {
        "type": "vision",
        "style": "supportOrgModelSlide",
        "data": {
          "tiers": ["Tier 1", "Tier 2", "Tier 3"],
          "roles": ["Agent", "Specialist", "Engineer"]
        }
      }
    },
    {
      "text": "partnershipMapSlide",
      "image": {
        "type": "vision",
        "style": "partnershipMapSlide",
        "data": {
          "categories": ["Licensing", "Technology", "Audit"],
          "partners": [
            {
              "style": "Content provider A",
              "category": "Licensing"
            },
            {
              "style": "Signing toolkit B",
              "category": "Technology"
            },
            {
              "style": "Audit firm C",
              "category": "Audit"
            }
          ]
        }
      }
    },
    {
      "text": "mAPipelineSlide",
      "image": {
        "type": "vision",
        "style": "mAPipelineSlide",
        "data": {
          "stages": ["Identify", "Evaluate", "Negotiate", "Integrate"],
          "targets": ["Evidence startup X", "Audit SaaS Y"]
        }
      }
    },
    {
      "text": "synergyCaptureSlide",
      "image": {
        "type": "vision",
        "style": "synergyCaptureSlide",
        "data": {
          "sources": ["Cross-sell", "Shared infra", "Joint R&D"],
          "values": [4, 1.5, 2]
        }
      }
    },
    {
      "text": "cultureValuesSlide",
      "image": {
        "type": "vision",
        "style": "cultureValuesSlide",
        "data": {
          "values": ["Truth", "Transparency", "Accountability"],
          "behaviors": ["Cite sources", "Log context", "Flag uncertainty"]
        }
      }
    },
    {
      "text": "thankYouContactSlide",
      "image": {
        "type": "vision",
        "style": "thankYouContactSlide",
        "data": {
          "message": "Thank you!",
          "style": "AI Referencing Taskforce",
          "email": "references@company.example",
          "url": "https://example.com/ai-references",
          "qrImageUrl": "https://api.qrserver.com/v1/create-qr-code/?size=200x200&data=https://example.com/ai-references"
        }
      }
    }
  ]
}
