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**EXECUTIVE SUMMARY DECK**

**Agentic AI Governance Platform**

**Version:** 2.0 \| **Date:** January 2026 \| **Confidential**

**SLIDE 1: COVER**

**\[Phase Mirror Logo\]**

**PHASE MIRROR**

**Governance for AI That Acts**

**Executive Summary**

Proof Labs LLC d/b/a Phase Mirror\
[[https://phasemirror.com]{.underline}](https://phasemirror.com)

*Confidential - For Executive Review*

**SLIDE 2: THE PROBLEM**

**Enterprise AI Is Breaking Traditional Governance**

**Three converging forces creating crisis:**

  Force                           Impact
  ------------------------------- -----------------------------------------------------
  **🤖 AI Autonomy**               Systems make decisions without human approval
  **📋 Compliance Requirements**   EU AI Act, SEC disclosure, SR 11-7, fair lending
  **⚖️ Governance Gap**           Existing frameworks designed for humans, not agents

**The Result:**

> *\"We have a policy that says X, but our AI actually does Y, and
> nobody knows until an examiner asks.\"*\
> --- CISO, Top 10 U.S. Bank

**Cost of Failure:**

-   Regulatory enforcement actions (\$10M-\$100M+)

-   Failed audits and examination findings

-   Reputational damage

-   AI deployment delays costing competitive advantage

**SLIDE 3: WHY EXISTING SOLUTIONS FAIL**

**The Tools Don\'t Match the Problem**

  What Enterprises Try            Why It Fails
  ------------------------------- ---------------------------------------------------------------
  **Traditional GRC Platforms**   Built for policy compliance, not AI autonomy
  **MLOps Tools**                 Monitor technical performance, ignore governance
  **Compliance Checklists**       Static documents don\'t catch dynamic AI behavior
  **Big 4 Consulting**            Expensive one-time assessments, no ongoing enforcement
  **Internal Build**              18-24 months, \$2M-\$5M, still doesn\'t solve methodology gap

**The Core Issue:**

Traditional governance assumes **humans execute decisions** that
**policies guide**.

Agentic AI **executes autonomously** and **policies can\'t keep up**.

**This isn\'t a technology problem. It\'s a structural problem.**

**SLIDE 4: THE PHASE MIRROR SOLUTION**

**Surface Contradictions. Create Levers. Govern What Acts.**

**Phase Mirror is the only platform that:**

1.  **Surfaces productive contradictions** between stated governance and
    > actual AI behavior

2.  **Converts those tensions into actionable levers** with owners,
    > metrics, and timelines

3.  **Creates binding artifacts** (specs, contracts, SLAs) instead of
    > vague policies

**Our Methodology: Mirror → Dissonance → Phase**

  Step             What It Means                                     Output
  ---------------- ------------------------------------------------- --------------------------
  **Mirror**       Reflect your claims back without endorsement      Neutral factual baseline
  **Dissonance**   Identify underlying tensions and contradictions   Root problems exposed
  **Phase**        Propose small, testable, incremental shifts       Concrete action levers

**Example Dissonance:**

-   **Your Policy:** \"All AI decisions require human oversight\"

-   **Your Reality:** Fraud detection AI approves 10,000
    > transactions/hour autonomously

-   **Our Lever:** \"Define \'oversight\' as human-reviewable audit
    > trail + exception escalation\"

**SLIDE 5: HOW IT WORKS**

**Platform + Methodology + Compliance Packs**

┌─────────────────────────────────────────────────────────────┐\
│ PHASE MIRROR ORACLE │\
│ (SaaS Platform Core) │\
│ │\
│ • AI System Registry & Classification │\
│ • Dissonance Detection Engine │\
│ • Governance Gap Identification │\
│ • Audit Trail (7 years) │\
│ • C Board Packet Generation │\
└─────────────────────────────────────────────────────────────┘\
↓\
┌──────────────────┬──────────────────┬──────────────────────┐\
│ COMPLIANCE PACKS │ METHODOLOGY │ INTEGRATIONS │\
├──────────────────┼──────────────────┼──────────────────────┤\
│ • EU AI Act │ • Diagnostic │ • GitHub/GitLab │\
│ • Financial │ • Workshop │ • CI/CD Pipelines │\
│ Services │ • Advisory │ • Jira/ServiceNow │\
│ • Healthcare │ • Training │ • SIEM/Splunk │\
│ • Agentic AI │ • Certification │ • SSO │\
└──────────────────┴──────────────────┴──────────────────────┘

**Key Differentiator:**

We\'re not selling a monitoring dashboard. We\'re selling a **governance
operating system** for AI that acts.

**SLIDE 6: UNIQUE VALUE PROPOSITIONS**

**What You Get That Nobody Else Provides**

  Capability                                  Traditional GRC   MLOps Tools     Phase Mirror
  ------------------------------------------- ----------------- --------------- -----------------------------
  **Identifies governance-reality gaps**      ❌                 ❌               ✅
  **Agentic AI governance**                   ❌                 ❌               ✅
  **Actionable levers (not just alerts)**     ❌                 ❌               ✅
  **Binding artifacts (specs, SLAs)**         ❌                 ❌               ✅
  **Owner, metrics, timeline for each gap**   ❌                 ❌               ✅
  **Regulatory compliance depth**             ⚠️ Generic        ❌               ✅ Financial, Healthcare, EU
  **C-suite/Board reporting**                 ⚠️ Manual         ❌               ✅ Automated
  **Open-core (self-hosting option)**         ❌                 Varies          ✅
  **Consulting + Platform integrated**        Services only     Platform only   ✅ Both

**Bottom Line:**

Phase Mirror addresses the **structural friction** between AI autonomy
and enterprise governance that no other solution targets.

**SLIDE 7: TARGET MARKETS & CUSTOMERS**

**Who Needs This Now**

**Primary Markets:**

  Sector                       Why Phase Mirror                                      Annual Spend Potential
  ---------------------------- ----------------------------------------------------- ------------------------
  **Financial Services**       SR 11-7, SEC AI disclosure, fair lending, OCC exams   \$100K-\$500K
  **Healthcare**               FDA guidance, HIPAA, clinical decision support        \$75K-\$250K
  **Enterprise Tech**          EU AI Act, internal compliance, product governance    \$50K-\$200K
  **Government Contractors**   Compliance requirements, audit readiness              \$100K-\$500K

**Customer Profile:**

  Role                     Pain Point                                     Phase Mirror Solution
  ------------------------ ---------------------------------------------- ------------------------------------------
  **CISO**                 \"Can\'t prove governance to regulators\"      Audit trail + dissonance reports
  **Chief Risk Officer**   \"AI systems creating unknown risks\"          Gap identification + risk quantification
  **Chief AI Officer**     \"Governance blocking AI deployment\"          Converts blocks into workable levers
  **General Counsel**      \"Can\'t defend AI decisions in litigation\"   Binding artifacts + documentation
  **Board of Directors**   \"Don\'t understand AI risks\"                 C Board Packet summaries

**Current Traction:** \[Insert customer count, logos, and notable wins\]

**SLIDE 8: BUSINESS MODEL & PRICING**

**Three Revenue Streams**

**1. Platform (SaaS) - Recurring Revenue**

  Tier             Annual Price   Seats       Use Case
  ---------------- -------------- ----------- ------------------------------------
  **Community**    Free           3           Individual developers, open source
  **Team**         \$6,000        10          Startups, single AI systems
  **Business**     \$36,000       50          Mid-market, multiple AI systems
  **Enterprise**   \$100K+        Unlimited   Fortune 500, regulated industries

**2. Compliance Packs - Add-On Revenue**

  Pack                         Price      Target
  ---------------------------- ---------- -----------------------
  EU AI Act Readiness          \$30,000   EU operations
  Financial Services           \$25,000   Banks, broker-dealers
  Healthcare & Life Sciences   \$25,000   Hospitals, pharma
  Agentic AI Governance        \$20,000   Cutting-edge AI teams

**3. Professional Services - Project Revenue**

  Service                    Price Range      Duration
  -------------------------- ---------------- ------------
  AI Governance Diagnostic   \$75K-\$500K     6-12 weeks
  Compliance Workshop        \$35K-\$50K      2 days
  Advisory Retainer          \$10K-\$50K/mo   Ongoing
  Implementation             \$15K-\$200K     4-16 weeks

**Unit Economics:**

-   **Customer Acquisition Cost (CAC):** \$\[X\]K

-   **Lifetime Value (LTV):** \$\[X\]K

-   **LTV:CAC Ratio:** \[X\]:1

-   **Payback Period:** \[X\] months

-   **Gross Margin:** 80-85% (SaaS), 60-70% (services)

**SLIDE 9: COMPETITIVE LANDSCAPE**

**We Compete in Three Adjacent Markets**

**Market 1: AI Governance Platforms**

  Competitor         Focus                 Our Advantage
  ------------------ --------------------- ---------------------------------------------------
  Fiddler AI         ML observability      We do governance methodology, not just monitoring
  Arthur AI          ML monitoring         We handle agentic AI, not just traditional ML
  Weights & Biases   Experiment tracking   We provide regulatory compliance depth

**Market 2: Traditional GRC**

  Competitor       Focus                  Our Advantage
  ---------------- ---------------------- -----------------------------------------
  OneTrust         Privacy & compliance   We\'re AI-native, they\'re retrofitting
  ServiceNow GRC   Enterprise GRC         We have AI governance methodology
  Archer           Risk management        We\'re modern SaaS, they\'re legacy

**Market 3: Big 4 Consulting**

  Competitor                Focus                  Our Advantage
  ------------------------- ---------------------- ---------------------------------------------------
  Deloitte, PwC, EY, KPMG   One-time assessments   Continuous platform + methodology at 1/5 the cost

**Unique Position:**

We\'re the **only** solution at the intersection of:

-   AI-native platform

-   Governance methodology (not just tools)

-   Regulatory compliance depth

-   Open-core option

**SLIDE 10: GO-TO-MARKET STRATEGY**

**Land and Expand**

**Phase 1: Land (Months 1-3)**

  Channel            Tactic                                       Goal
  ------------------ -------------------------------------------- -----------------------------
  **Direct Sales**   Outbound to financial services CISOs/CROs    10-20 qualified leads/month
  **Inbound**        Content marketing (dissonance methodology)   50-100 MQLs/month
  **Partnerships**   Big 4, legal firms, compliance consultants   2-3 partnerships in Year 1

**Phase 2: Expand (Months 4-12)**

  Expansion Vector        Revenue Impact
  ----------------------- ------------------------------
  Compliance packs        +\$25K-\$30K per pack
  Additional seats        +\$10K-\$50K/year
  Professional services   +\$50K-\$500K per engagement
  Enterprise upgrades     +\$50K-\$200K/year

**Phase 3: Network Effects (Year 2+)**

  Moat                          Description
  ----------------------------- ----------------------------------------------
  **Calibration data**          More customers = better dissonance detection
  **Compliance templates**      Crowdsourced best practices
  **Regulatory intelligence**   Aggregated examination insights

**Sales Cycle:**

-   **Pilot:** 30-60 days (\$10K-\$25K)

-   **Production:** 60-90 days (\$50K-\$150K)

-   **Enterprise:** 90-180 days (\$200K-\$500K+)

**SLIDE 11: MARKET OPPORTUNITY**

**\$50B+ Addressable Market**

**TAM (Total Addressable Market):**

  Market Segment         2025 Value      2030 Projection   CAGR
  ---------------------- --------------- ----------------- -----------
  AI Compliance SaaS     \$5.1B          \$39.5B           22.8%
  AI Governance Market   \$309M          \$3.7B            35%
  AI Consulting          \$11.1B         \$91B             26.2%
  **TOTAL TAM**          **\~\$16.5B**   **\~\$134B**      **\~25%**

**SAM (Serviceable Addressable Market):**

Phase Mirror targets regulated enterprises deploying AI:

  Segment                  Enterprise Count   Avg Contract Value   SAM
  ------------------------ ------------------ -------------------- ------------
  **Financial Services**   10,000+            \$150K               \$1.5B
  **Healthcare**           8,000+             \$100K               \$800M
  **Enterprise Tech**      5,000+             \$75K                \$375M
  **Government/Defense**   2,000+             \$200K               \$400M
  **TOTAL SAM**            **25,000+**        **\~\$120K avg**     **\~\$3B**

**SOM (Serviceable Obtainable Market):**

Conservative 3-year target: **1% of SAM = \$30M ARR**

**Market Drivers:**

1.  **Regulatory pressure:** EU AI Act (2025), SEC AI disclosure, SR
    > 11-7

2.  **AI adoption acceleration:** 72% of enterprises deploying AI by
    > 2026

3.  **Governance gap recognition:** High-profile AI failures driving
    > demand

4.  **Agentic AI wave:** Autonomous systems creating new governance
    > urgency

**SLIDE 12: TRACTION & MILESTONES**

**Momentum Building**

**Current Status (January 2026):**

  Metric                               Value
  ------------------------------------ ------------
  **Annual Recurring Revenue (ARR)**   \$\[X\]M
  **Total Customers**                  \[X\]
  **Enterprise Customers**             \[X\]
  **Average Contract Value**           \$\[X\]K
  **MRR Growth Rate**                  \[X\]% MoM
  **Net Revenue Retention**            \[X\]%
  **Gross Margin**                     \[X\]%

**Notable Customers:**

\[Insert customer logos and brief use cases\]

**Recent Milestones:**

-   ✅ SOC 2 Type II certification achieved

-   ✅ Financial Services Compliance Pack launched

-   ✅ EU AI Act Readiness Pack launched

-   ✅ \[X\] Fortune 500 customers acquired

-   ✅ \[Partnership announcement\]

-   ⏳ ISO 27001 in progress (Q\[X\] 2026)

**Pipeline:**

  Stage                   Count       Total Value
  ----------------------- ----------- --------------
  Qualified leads         \[X\]       \$\[X\]M
  POCs in progress        \[X\]       \$\[X\]M
  Contracts negotiating   \[X\]       \$\[X\]M
  **Total Pipeline**      **\[X\]**   **\$\[X\]M**

**SLIDE 13: TEAM & ADVISORS**

**Deep Expertise in AI, Governance, and Regulation**

**Leadership Team:**

  Name                Role                    Background
  ------------------- ----------------------- -------------------------------------------------------------
  **\[CEO Name\]**    CEO & Co-Founder        \[Prior experience - e.g., AI governance at Fortune 100\]
  **\[CTO Name\]**    CTO & Co-Founder        \[Prior experience - e.g., 15 years building ML platforms\]
  **\[CPO Name\]**    Chief Product Officer   \[Prior experience - e.g., GRC product leadership\]
  **\[CRO Name\]**    Chief Revenue Officer   \[Prior experience - e.g., Enterprise SaaS sales\]
  **\[CISO Name\]**   CISO                    \[Prior experience - e.g., Financial services security\]

**Advisory Board:**

  Name                Expertise              Affiliation
  ------------------- ---------------------- ----------------------------------
  **\[Advisor 1\]**   Financial regulation   \[Former OCC/Fed official\]
  **\[Advisor 2\]**   AI ethics              \[Leading university professor\]
  **\[Advisor 3\]**   Enterprise sales       \[Former CRO of unicorn SaaS\]

**Team Size:** \[X\] employees

-   Engineering: \[X\]

-   Product: \[X\]

-   Sales & Marketing: \[X\]

-   Customer Success: \[X\]

-   Operations: \[X\]

**SLIDE 14: FINANCIAL PROJECTIONS**

**Path to \$100M ARR**

**3-Year Revenue Projection:**

                              2026           2027           2028
  --------------------------- -------------- -------------- --------------
  **Platform Revenue**        \$\[X\]M       \$\[X\]M       \$\[X\]M
  **Compliance Packs**        \$\[X\]M       \$\[X\]M       \$\[X\]M
  **Professional Services**   \$\[X\]M       \$\[X\]M       \$\[X\]M
  **Total Revenue**           **\$\[X\]M**   **\$\[X\]M**   **\$\[X\]M**
  **Growth Rate YoY**         \[X\]%         \[X\]%         \[X\]%

**Unit Economics Maturation:**

  Metric                      2026       2027       2028
  --------------------------- ---------- ---------- ----------
  **CAC**                     \$\[X\]K   \$\[X\]K   \$\[X\]K
  **LTV**                     \$\[X\]K   \$\[X\]K   \$\[X\]K
  **LTV:CAC**                 \[X\]:1    \[X\]:1    \[X\]:1
  **Payback Period**          \[X\] mo   \[X\] mo   \[X\] mo
  **Net Revenue Retention**   \[X\]%     \[X\]%     \[X\]%

**Path to Profitability:**

                      2026          2027          2028
  ------------------- ------------- ------------- ---------------
  **Gross Margin**    \[X\]%        \[X\]%        \[X\]%
  **EBITDA Margin**   (\[X\])%      (\[X\])%      +\[X\]%
  **Cash Position**   \$\[X\]M      \$\[X\]M      \$\[X\]M
  **Burn Rate**       \$\[X\]K/mo   \$\[X\]K/mo   Cash positive

**Capital Efficient Growth:**

-   Self-serve Community tier drives inbound pipeline

-   Land-and-expand minimizes upfront CAC

-   High gross margins (80%+) on SaaS

-   Services revenue funds R&D

**SLIDE 15: FUNDING & USE OF PROCEEDS**

**\[Series X\] Round**

**Raise Amount:** \$\[X\]M

**Valuation:** \$\[X\]M post-money (\[X\]x ARR multiple)

**Use of Proceeds:**

  Category                    Allocation   Purpose
  --------------------------- ------------ ------------------------------------------------
  **Product & Engineering**   \[X\]%       Agentic AI features, integrations, scalability
  **Sales & Marketing**       \[X\]%       Enterprise sales team, demand generation
  **Customer Success**        \[X\]%       Implementation, support, retention
  **Compliance & Security**   \[X\]%       ISO 27001, FedRAMP readiness, SOC 1
  **Operations & G&A**        \[X\]%       Infrastructure, finance, legal
  **Working Capital**         \[X\]%       18-24 month runway

**Capital Strategy:**

-   **Current Runway:** \[X\] months at current burn

-   **Runway Post-Raise:** \[X\] months

-   **Next Milestone:** \$\[X\]M ARR, \[X\] enterprise customers

-   **Path to Series \[X+1\]:** Q\[X\] 202\[X\] at \$\[X\]M+ ARR

**Existing Investors:**

\[List if applicable\]

**SLIDE 16: RISKS & MITIGATION**

**How We Address Key Risks**

+----------------------------+----------------------------------------+
| Risk                       | Mitigation                             |
+============================+========================================+
| **Regulatory uncertainty** | \- Modular compliance packs adapt to   |
|                            | changing regulations                   |
|                            |                                        |
|                            | \- Advisory board includes former      |
|                            | regulators                             |
|                            |                                        |
|                            | \- Methodology-first approach stays    |
|                            | relevant                               |
+----------------------------+----------------------------------------+
| **Competitive pressure**   | \- Unique dissonance methodology is    |
|                            | defensible IP                          |
|                            |                                        |
|                            | \- Open-core model creates switching   |
|                            | costs                                  |
|                            |                                        |
|                            | \- Network effects from calibration    |
|                            | data                                   |
+----------------------------+----------------------------------------+
| **Enterprise sales cycle** | \- Self-serve tier creates inbound     |
|                            | pipeline                               |
|                            |                                        |
|                            | \- Pilot program reduces friction      |
|                            |                                        |
|                            | \- ROI documented (40-60% compliance   |
|                            | cost reduction)                        |
+----------------------------+----------------------------------------+
| **Technical execution**    | \- Experienced engineering team        |
|                            |                                        |
|                            | \- Proven scalable architecture        |
|                            |                                        |
|                            | \- SOC 2 certified operations          |
+----------------------------+----------------------------------------+
| **Market adoption**        | \- Regulatory tailwinds (EU AI Act,    |
|                            | SEC disclosure)                        |
|                            |                                        |
|                            | \- High-profile AI failures driving    |
|                            | demand                                 |
|                            |                                        |
|                            | \- Financial services early adopters   |
|                            | validate market                        |
+----------------------------+----------------------------------------+
| **Talent acquisition**     | \- Competitive compensation            |
|                            |                                        |
|                            | \- Mission-driven culture              |
|                            |                                        |
|                            | \- Remote-first flexibility            |
+----------------------------+----------------------------------------+
| **Customer concentration** | \- Diversified across financial,       |
|                            | healthcare, tech                       |
|                            |                                        |
|                            | \- 50+ customer target by end of 2026  |
|                            |                                        |
|                            | \- No single customer \>20% revenue    |
+----------------------------+----------------------------------------+

**SLIDE 17: STRATEGIC ROADMAP**

**2026-2028 Vision**

**2026: Establish Market Leadership**

-   ✅ Launch agentic AI governance capabilities

-   ✅ Achieve 100+ enterprise customers

-   ✅ Complete ISO 27001 certification

-   ✅ Expand to 5-7 compliance packs

-   ✅ Launch partner program (Big 4, legal firms)

**2027: Scale & Network Effects**

-   🎯 Reach \$\[X\]M ARR

-   🎯 Launch FedRAMP moderate offering

-   🎯 International expansion (UK, EU, APAC)

-   🎯 Release open-source dissonance detection SDK

-   🎯 Build calibration data network (1000+ systems)

**2028: Platform Dominance**

-   🎯 Reach \$\[X\]M ARR

-   🎯 Become de facto standard for AI governance

-   🎯 Launch AI governance marketplace (third-party packs)

-   🎯 Achieve profitability

-   🎯 Strategic partnerships with hyperscalers (AWS, Azure, GCP)

**Long-Term Vision:**

Phase Mirror becomes the **governance operating system** for every AI
system in regulated industries.

**SLIDE 18: WHY INVEST IN PHASE MIRROR?**

**Seven Compelling Reasons**

**1. Massive Market Opportunity**

-   \$3B SAM growing at 25% CAGR

-   Regulatory tailwinds accelerating demand

**2. Defensible Differentiation**

-   Only platform addressing governance-reality gap

-   Dissonance methodology is unique IP

-   Agentic AI governance capabilities

**3. Product-Market Fit Validated**

-   \[X\] enterprise customers

-   \[X\]% NRR demonstrates value

-   Fortune 500 adoption

**4. Capital Efficient**

-   80%+ gross margins on SaaS

-   Self-serve motion drives efficient CAC

-   Land-and-expand maximizes LTV

**5. Experienced Team**

-   Deep expertise in AI, governance, regulation

-   Prior exits and enterprise SaaS success

-   Advisors include former regulators

**6. Regulatory Tailwinds**

-   EU AI Act enforcement (2025-2026)

-   SEC AI disclosure requirements

-   Financial services model risk management

**7. Network Effects Emerging**

-   Calibration data improves with scale

-   Open-core community creating ecosystem

-   Compliance templates crowdsourced

**Bottom Line:**

Phase Mirror is solving a **structural problem** that will only grow as
AI becomes more autonomous. We\'re building the infrastructure layer for
AI governance.

**SLIDE 19: THE ASK**

**Join Us in Governing AI That Acts**

**Investment Opportunity:**

  ------------------------ --------------------------------------------------
  **Raise Amount**         \$\[X\]M
  **Security**             \[Series X Preferred / SAFE / Convertible Note\]
  **Valuation**            \$\[X\]M post-money
  **Minimum Investment**   \$\[X\]K
  **Use of Proceeds**      Product, sales, compliance certifications
  **Expected Close**       Q\[X\] 2026
  ------------------------ --------------------------------------------------

**What We\'re Looking For:**

-   Strategic investors with enterprise SaaS expertise

-   Domain experts in AI governance and regulation

-   Investors who can open doors in financial services

-   Long-term partners aligned with our mission

**Next Steps:**

1.  ☐ Review detailed investor deck and financials

2.  ☐ Customer reference calls

3.  ☐ Technical deep dive with CTO

4.  ☐ Term sheet negotiation

5.  ☐ Close within \[X\] days

**SLIDE 20: CONTACT & DUE DILIGENCE**

**Let\'s Talk**

**Primary Contact:**

**\[CEO Name\]**\
Chief Executive Officer\
📧 \[email\]\@phasemirror.com\
📱 +1 (\[XXX\]) XXX-XXXX\
🔗
[[linkedin.com/in/\[profile\]]{.underline}](http://linkedin.com/in/%5Bprofile%5D)

**Additional Contacts:**

  Role                      Name           Email
  ------------------------- -------------- ------------------------------------------------------------------------------
  **Investor Relations**    \[Name\]       [[investors\@phasemirror.com]{.underline}](mailto:investors@phasemirror.com)
  **Technical DD**          \[CTO Name\]   \[email\]\@phasemirror.com
  **Customer References**   \[Name\]       \[email\]\@phasemirror.com

**Data Room Access:**

📁 \[Secure link to data room\]

**Due Diligence Materials Available:**

-   ✅ Detailed financial model (5-year projections)

-   ✅ Customer list and case studies

-   ✅ Product roadmap

-   ✅ Go-to-market strategy

-   ✅ Competitive analysis

-   ✅ Legal documents (cap table, contracts, IP)

-   ✅ Security documentation (SOC 2, policies)

-   ✅ Team bios and org chart

**Company Information:**

**Proof Labs LLC d/b/a Phase Mirror**\
Website:
[[https://phasemirror.com]{.underline}](https://phasemirror.com)\
GitHub:
[[https://github.com/RyVanGyver/Phase-Mirror]{.underline}](https://github.com/RyVanGyver/Phase-Mirror)\
Status:
[[https://status.phasemirror.com]{.underline}](https://status.phasemirror.com)

**APPENDIX: SUPPLEMENTARY SLIDES**

**A1: Detailed Product Architecture**

\[Technical architecture diagram showing:

-   Oracle platform core

-   Compliance pack architecture

-   Integration layer

-   Data flow

-   Security boundaries\]

**A2: Customer Case Studies**

**Case Study 1: \[Regional Bank\]**

-   Problem: Failed OCC examination on AI governance

-   Solution: Phase Mirror Financial Services Compliance Pack

-   Result: Clean follow-up exam, 60% reduction in compliance costs

**Case Study 2: \[Healthcare System\]**

-   Problem: FDA compliance for clinical decision support AI

-   Solution: Phase Mirror Healthcare Compliance Pack

-   Result: FDA submission approved, documented governance framework

**Case Study 3: \[Fintech Unicorn\]**

-   Problem: Fair lending concerns blocking product launch

-   Solution: Phase Mirror diagnostic + advisory

-   Result: Launched in 90 days with defensible governance

**A3: Detailed Competitive Matrix**

\[Full feature-by-feature comparison with:

-   Fiddler AI

-   Arthur AI

-   Weights & Biases

-   OneTrust

-   ServiceNow GRC

-   Big 4 Consulting\]

**A4: Go-to-Market Playbook**

\[Detailed breakdown of:

-   Sales process

-   Marketing campaigns

-   Partnership strategy

-   Customer success motion

-   Pricing negotiations\]

**A5: Financial Model Details**

\[Detailed financial model showing:

-   Revenue build-up by product line

-   Cohort analysis

-   Unit economics by segment

-   Headcount plan

-   P&L statement

-   Cash flow analysis

-   Balance sheet\]

**END OF DECK**

This executive summary deck provides a comprehensive overview for
investors, board members, and strategic partners. Would you like me to
create:

-   A shorter \"pitch deck\" version (10 slides for initial meetings)

-   A \"board update\" version focused on operational metrics

-   An \"enterprise sales\" deck for customer acquisition

-   Visual design specifications for each slide

-   Speaker notes for presenting the deck?

⁂

1.  A Clear Guide to Phase Mirror\'s Services.pdf

2.  Phase mirror dissonance\_\_\_Open core must be useful.pdf

3.  Phase Mirror\_ Comprehensive Services Catalog.docx.pdf

4.  License\_ Strategic & Legal Analysis.pdf

5.  Phase Mirror\_ Consultation & SaaS.pdf

6.  Agentic Domain-Specific Reasoning.pdf

7.  Policy Memo\_ Managing Agentic AI Liability with the Phase Mirror
    > Framework.pdf

8.  The Phase Mirror does not resolve dissonance---it names it.pdf

9.  Understanding Phase Mirror Dissonance\_ A Beginner\'s Guide.pdf

10. The Phase of Mirror Dissonance.pdf

11. Implementation Guide\_ Applying Phase Mirror Dissonance.pdf
