MARKET INTELLIGENCE · FINANCIAL PLANNING · EXECUTIVE DECISION SUPPORT
Population & Customer Market Intelligence System — a market-intelligence, scenario-modeling, financial-planning, and executive decision-support system that connects population data and configurable assumptions to strategic planning outputs.
Professional project profile
PCMIS connects market research, population intelligence, scenario modeling, financial planning, and software implementation into an explainable executive decision-support system.
Executive summary
PCMIS transforms population data, market assumptions, segmentation, subscription economics, and financial inputs into a connected planning system for market sizing, geographic prioritization, scenario analysis, financial modeling, and executive decision support. It is designed to make the assumptions behind a planning view visible so leaders can explore alternatives rather than depend on a single opaque forecast.
Early-stage product and commercialization planning can require a defensible connection between addressable population, target segments, market opportunity, subscription assumptions, operating economics, and financial outcomes. PCMIS was built to turn those interdependent questions into a connected, reviewable planning workflow.
Create an auditable market-intelligence and financial-planning system that moves from public population data and explicit assumptions to geographic priorities, scenario comparisons, modeled financial trajectories, risk signals, and executive-ready planning outputs.
Each stage exposes inputs and modeled outputs so population intelligence, market opportunity, operating assumptions, and financial planning can be considered as one connected decision chain.
Executive responsibility framework
Connected product opportunity, market research, commercialization questions, strategic planning, and executive decision-support requirements into a coherent business case for a planning system rather than an isolated dashboard.
Designed market-sizing, subscription-economics, scenario, contribution, P&L, cash-flow, runway, break-even, and SaaS KPI models to make planning assumptions and their financial implications reviewable.
Defined analytical workflows, scenario controls, dashboard requirements, planning outputs, executive reporting, and the decision-support experience that connects detailed models to leadership questions.
Architected the Python and Dash analytical application, validated population-data pipeline, modeling layers, visualization approach, deterministic recommendation logic, and Excel reporting design.
Led hands-on, AI-assisted engineering and review across the population-data pipeline, analytical modules, dashboards, validation, financial calculations, deterministic forecasting, rules-based insights, and executive Excel export.
Market intelligence engine
Validated Census PEP 2025 state-population data supports analysis across all 50 U.S. states and Washington, D.C., connecting public population context to addressable-market questions.
Configurable market assumptions and segmentation translate broad population context into total, serviceable, and obtainable market views rather than leaving the planning basis implicit.
Conservative, base, aggressive, and additional penetration assumptions make the sensitivity of strategic plans visible before a single forecast becomes a decision anchor.
State-level opportunity modeling and geographic views help compare concentration, prioritization, and modeled market potential across locations.
Subscription assumptions connect to modeled MRR, ARR, CAC, gross profit, contribution, monthly P&L, cash flow, runway, break-even, and SaaS KPI analysis.
Explainable, assumption-driven forecasting, risk signals, recommendation logic, strategic guidance, and CFO-style analytical narratives turn model state into reviewable executive context.
Explainable deterministic intelligence
PCMIS currently uses deterministic, rules-based, and assumption-driven calculations for forecasting, risk analysis, recommendation logic, strategic guidance, and CFO-style insight narratives. These outputs are explainable because they remain connected to the configured model inputs and calculation layers.
The current implementation does not present generative AI, LLMs, OpenAI integration, machine learning, or predictive AI as completed capabilities.
Executive Excel planning system
PCMIS generates formatted executive planning workbooks for one-, two-, and three-year horizons. The workbook structure brings together executive summary, strategic snapshot, deterministic recommendations, risk, assumptions, revenue, subscriber growth, operating expenses, monthly P&L, cash flow and runway, break-even, SaaS KPIs, geographic and demographic intelligence, and methodology views.
The export supports further planning and review; its historical “AI Recommendations” sheet name refers to the current deterministic rules-based recommendation layer, not an LLM implementation.
Product in action
The product experience connects market intelligence, financial planning, scenario modeling, geographic analysis, and executive reporting within one decision-support workflow.
Model-output disclosure: Screens show deterministic model outputs and scenario-based projections derived from configured assumptions. They do not represent realized revenue, profitability, customer adoption, ROI, or measured forecast accuracy.
Executive financial intelligence consolidates modeled market, financial, risk, and planning signals into a decision-support view.
Deterministic forecast trajectories show modeled revenue, margin, cash balance, runway, and risk signals under explicit assumptions.
State-level opportunity analysis supports geographic prioritization and concentration review from modeled outputs.
Population analysis connects Census PEP 2025 state data to modeled target-market, customer, and financial outputs.
Geographic visualization makes modeled market opportunity and revenue distribution easier to evaluate across states.
A twelve-month projection translates selected assumptions into modeled customer, MRR, ARR, and gross-profit trajectories.
Scenario comparison makes the effects of conservative, base, aggressive, and penetration assumptions visible before decisions are made.
Executive presentation view representing PCMIS's intended evolution toward AI-assisted market intelligence and financial interpretation while preserving deterministic financial models as the authoritative calculation layer.
System architecture & technology
PCMIS separates validated population data, configurable market and financial assumptions, deterministic analytical modules, dashboard visualizations, rules-based insight layers, and workbook generation so decision support can evolve without obscuring the underlying calculation model.
Current stage
The current PCMIS MVP implements deterministic, assumption-driven market intelligence, scenario modeling, financial planning, forecasting, risk analysis, rules-based recommendations, CFO-style insight narratives, executive dashboards, and dynamic Excel planning exports. Financial and customer figures shown in this profile are modeled outputs and projections, not realized commercial outcomes.
Current intelligence is deterministic, rules-based, and explainable. It is not presented as LLM-powered, generative-AI, machine-learning, or predictive-AI functionality.
Project evidence
Live application
Production application; access may require authentication.View Live ApplicationFuture intelligence architecture
Future direction can add optional predictive and statistical intelligence, followed by an AI / LLM reasoning and explanation layer with governance and human review. The LLM should interpret the financial model; the LLM should not become the financial model. Deterministic and auditable calculations remain the authoritative source of financial truth.
Connected product strategy
PCMIS supports strategic planning for PAi / Pocket Assistant AI while remaining a standalone case study for market intelligence, financial planning, and executive decision support.
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PCMIS demonstrates how business strategy, market research, quantitative analysis, financial planning, product strategy, analytical architecture, and hands-on engineering can become one executive decision-support system.
