GridNav™ is the first platform to deliver the complete clean energy pre-development workflow in a single tool. Site identification, utility rate analysis, DOE-grade optimization, interactive financial modeling, AI-interpreted reporting, and portfolio comparison — all in one place, accessible to anyone, in minutes instead of months.
It runs on the same optimization engine the U.S. Department of Energy uses (NREL REopt), delivered through modern software that non-engineers can use from day one, with every result interpreted by ProtoGen AI.
The workflow that used to require a consultant, a GIS specialist, a financial analyst, and weeks of coordination now takes one person and a few clicks.
A traditional clean energy feasibility study costs $10,000–$50,000 and takes weeks to months. It requires hiring a specialized engineering consultant, providing building data, waiting for analysis, and receiving a static PDF that can’t be adjusted.
If a single assumption changes — incentive rate, equipment cost, utility rate — the entire study has to be re-run.
This is the bigger problem. A municipality, utility, or state agency that wants to evaluate clean energy across 50, 200, or 1,000 buildings can’t afford $10K per study. So they either:
GridNav runs NREL REopt — the same optimization model the Department of Energy, national laboratories, and major utilities use for clean energy planning. This isn’t a simplified calculator or a rule-of-thumb estimator. It’s a full mathematical optimization that simultaneously evaluates:
Customers aren’t trusting a startup’s math. They’re trusting the DOE’s math, delivered through better software. This is a credibility advantage that’s nearly impossible for competitors to replicate.
No competing product has anything equivalent.
The Financial Ledger is a live, interactive financial model that sits on top of every optimization result. It’s the single source of truth for payback period, NPV, LCOE, IRR, and lifetime savings — and it recalculates instantly when users adjust assumptions:
The breakthrough feature is grant back-calculation. Users work backwards: “What grant amount would I need to achieve a 7-year payback?” For anyone writing a grant application — municipalities, nonprofits, tribal nations, schools — this single feature justifies the entire platform. Instead of guessing at grant amounts, they calculate exactly what funding is needed to hit their target economics.
Traditional feasibility studies produce a static number. GridNav’s Financial Ledger lets users explore the entire financial landscape in real-time. A developer can sit with a building owner, move sliders, and show exactly how project economics respond to different assumptions. No waiting, no re-running, no calling an engineer. This is the feature that closes deals.
ProtoGen AI is not a chatbot bolted onto a results page. It’s a purpose-built narrative intelligence system that delivers the kind of analysis you’d expect from an experienced energy consultant — generated in seconds.
10 Distinct Narrative Sections, Each Independently Curated:
Every analysis produces a comprehensive, structured report across two tabs:
Results Tab:
Financials Tab:
Deep Analysis, Not Surface-Level Summaries:
ProtoGen AI doesn’t summarize numbers — it interprets them. Before generating a single word, the system analyzes a full year of hourly optimization data and distills it into behavioral insights: Is the battery peak-shaving or arbitraging? Is solar curtailment driven by rate structure or oversizing? How does the system perform in summer vs. winter? How many hours can it operate independently from the grid?
This is domain intelligence that generic AI can’t replicate. ProtoGen AI understands that battery arbitrage only exists with real rate differentials, that resilience depends on dispatchable resources not weather, and that a system curtailing solar at midday might be behaving exactly as intended under a TOU tariff. The narratives explain the why, not just the what.
Self-Improving Through Human Feedback:
ProtoGen AI incorporates continuous human-derived feedback loops — expert-validated outputs are fed back into the generation pipeline, meaning narrative quality compounds over time. Every scenario type, technology combination, and market context gets sharper with use. This isn’t a static system — it learns what “good” looks like from ProtoGen’s energy analysts and gets better at delivering it.
Portfolio Comparative Analysis — Industry First:
When users select multiple scenarios for comparison, ProtoGen AI automatically classifies the comparison type and generates the appropriate cross-scenario analysis:
No other product offers AI-generated comparative portfolio analysis across clean energy scenarios. For individual analyses, ProtoGen AI saves 10-20 hours of consulting per deliverable. For portfolio comparisons, there is no manual equivalent.
GridNav isn’t a single-project tool. It’s a portfolio platform built for the way program managers, developers, and consultants actually work — evaluating dozens or hundreds of projects and deciding where to focus.
At-a-Glance Project Cards: Every saved scenario gets a rich summary card showing the metrics that matter: technologies selected (PV, battery, wind, generator — visible as icons), operational intent (standard vs. self-consumption), payback period, LCOE, annual savings, system size, and project location. A portfolio of 50 projects becomes scannable in seconds — standout economics surface immediately, underperformers are obvious, and the technology mix across the portfolio is visible at a glance.
Rapid Identification of Winners: Sort and filter across any metric. Which projects pay back fastest? Which have the lowest LCOE? Which ones included battery storage? Which are running in self-consumption mode? A program manager evaluating 100 municipal buildings can rank every site by financial performance and prioritize the top 10 for immediate action — work that would take a consultant days of spreadsheet assembly.
Side-by-Side Comparison: Select any 2+ scenarios and launch a direct comparison view that puts their metrics, cashflow charts, and dispatch curves next to each other:
ProtoGen AI Portfolio Analysis: On top of the visual comparison, ProtoGen AI generates a written cross-scenario analysis — automatically classifying whether the comparison is a configuration trade-off (same site, different designs), a market comparison (different sites, different economics), or a cluster assessment (nearby sites with shared grid potential). The narrative highlights which projects win on which axes and why.
Project Organization: Rename, reassign, and organize scenarios across projects and clients. Consulting firms manage separate client portfolios with role-based access — analysts see their assigned projects, client admins see everything in their organization, super admins see across the platform.
For a municipal planner with 50 buildings, a developer with 200 prospects, or a state energy office evaluating 500 grant applications — the portfolio view is where GridNav transforms from a project tool into a program platform.
Most REopt implementations focus exclusively on commercial and industrial buildings. GridNav is the only platform with a complete residential pathway through DOE-grade optimization:
The residential clean energy market is enormous and underserved by optimization tools. Homeowners, residential solar installers, and home energy auditors have no other way to run DOE-grade multi-technology optimization for a house. GridNav opens this entire market.
Most tools optimize one technology at a time. GridNav optimizes solar, wind, battery, and generator together as an integrated system. But what truly sets it apart is accessibility:
N+X Optimization: Users opt into technology combinations with simple toggles — PV only, PV+Battery, PV+Battery+Generator, or the full stack including Wind. The optimizer determines the right mix and sizing. What takes an engineer hours of manual scenario setup takes a GridNav user 10 seconds.
Self-Consumption Mode: For markets where net metering is unfavorable or unavailable, GridNav optimizes for maximum on-site energy use rather than grid export. This unlocks markets in states with poor net metering policies and positions GridNav for international expansion where export compensation is minimal.
These capabilities exist in engineering tools like Homer Energy — but require significant technical expertise to configure. GridNav makes them accessible through clear, intuitive controls.
GridNav includes a full parametric turbine builder that lets industry professionals define, test, and optimize custom wind turbines — not just select from a dropdown.
Build Any Turbine From First Principles: Define rated capacity, hub height, rotor diameter, cut-in speed, rated speed, and cut-out speed. GridNav computes power coefficient and validates against the Betz limit. Four presets cover residential (2.5 kW) through utility-scale (2 MW), but the real power is in custom configurations.
Interactive Power Curve Editing: Generate a power curve from parametric inputs, then refine it visually with draggable control points. For users with manufacturer datasheets, paste speed/power pairs directly — the system auto-detects cut-in, rated, and cut-out speeds from the imported data.
Dual Wind Resource Data — US + Global:
Professional-Grade Production Analysis: Wind shear correction with terrain presets, production loss modeling across four categories (wake, electrical, availability, environmental), and seven interactive visualizations including wind rose, power curve overlay, and vertical wind profile. All fed directly into the REopt economic optimization.
Shared Turbine Library: Defined turbines are saved to a client-scoped library with role-based access. Consulting firms maintain a master turbine library and deploy it across any client portfolio.
Wind developers currently use separate tools to evaluate turbine options before running economic analysis in another tool. GridNav puts both in one workflow — define the turbine, fetch the wind data, see the production analysis, and run full economic optimization without leaving the platform.
Tariff Explorer: Browse, search, and select from the entire URDB (Utility Rate Database) — thousands of real utility tariffs across the U.S. See the actual rate structure: TOU schedules, demand charges, tiered rates, in a clear visual format.
Bill Exploration Tool: Once a tariff and load profile are selected, GridNav generates a complete visual bill analysis — instantly answering the questions every building owner and energy manager asks:
Users upload their actual load profile, select their real tariff, and instantly see what they’re paying and why — before running a single optimization. This makes the subsequent clean energy analysis far more meaningful because users already understand their baseline.
Custom Tariff Builder with Independent Export Rates: For tariffs not in the URDB, GridNav provides a visual builder for custom TOU schedules — including a drag-to-paint schedule editor where users color in rate periods on a 12×24 month-by-hour grid. The standout capability: independent export rate schedules. Users model scenarios where the utility pays a different rate for exported energy than what the user pays for consumption. Critical for:
No other self-service tool offers this level of tariff visualization, bill analysis, and rate modeling flexibility in one integrated experience.
GridNav doesn’t just tell users their system survives an outage — it lets them explore exactly when, where, and how.
Interactive Outage Window Selection: The Outage Analyzer displays a full year of daily load and solar generation on a zoomable chart. Users drag a brush across any window — 24 hours, 3 days, 2 weeks — to define exactly when the outage happens. Preset buttons offer quick 1-day, 3-day, and 14-day scenarios, with seasonal best/worst/average cases that automatically scan every possible window in summer or winter to find the hardest and easiest survival scenarios.
Real-Time Survival Analysis: As users adjust the outage window, the analyzer instantly calculates:
Post-Optimization Dispatch Visualization: After the optimization runs, results include a dispatch chart showing exactly how each technology contributes during the outage period — battery discharge cycles, generator runtime, solar contribution, and the margin of safety at every hour.
Post-hurricane, post-wildfire, and grid reliability concerns are driving unprecedented demand for resilience planning. Emergency management offices, military installations, hospitals, and critical infrastructure operators all face the same question: “If the grid goes down on the worst possible day, for the longest realistic duration, will our system keep the lights on?” GridNav lets them explore that question interactively — not wait weeks for a consultant’s yes/no answer.
GridNav includes a full-featured map tool that turns satellite imagery into a collaborative planning workspace — no GIS software, no shapefiles, no training required.
Draw, Measure, and Categorize: Users draw polygons, lines, and points directly on the map to site equipment and define project boundaries. Every feature is automatically measured (square footage for areas, linear feet for lines) and assigned to one of 12 asset categories — Solar, Rooftop PV, Wind, Battery Storage, Generator, Transformer, Critical Facility, Microgrid Site, and more. Each category gets its own icon and color on the map.
PV Sizing From Satellite Imagery: Draw polygons on rooftops or open land using satellite imagery, and GridNav automatically calculates available area and feeds it into the optimization. Users see exactly what fits where before committing to an analysis.
Distribution Network Mapping: GridNav includes a full electrical infrastructure layer — distribution lines, feeders, transformers, and bus topology. Users draw distribution lines with intelligent snapping (lines automatically connect to nearby infrastructure junctions), assign voltage levels and line types (overhead, underground), and build out feeder networks visually. Transformers connect to primary and secondary buses with dropdown selection sorted by proximity and voltage.
This isn’t just visualization — it’s the foundation for the upcoming OpenDSS integration, where the distribution network drawn on the map becomes the direct input for substation-level grid impact analysis.
Building Categorization: Click any building on the map to assign it to a feeder, categorize it (commercial, residential, industrial), and link it to the distribution network. This creates the building-to-grid relationship needed for substation-level analysis.
Scenario Integration: Every optimization scenario appears as a pin on the map. Click any pin to see key metrics, dispatch charts, and financial headlines without leaving the map view. Select multiple scenarios and launch a side-by-side portfolio comparison directly from the map — ideal for program managers evaluating sites geographically.
Layer Management: Toggle visibility of public and client-specific data layers, with role-based access controlling who sees what. Shared infrastructure layers (transmission networks, substations) are visible across clients while project-specific features stay scoped.
Energy project planning is inherently spatial — which buildings, which rooftops, which substations, which feeders. Today this work happens in GIS software that requires specialized training, or it doesn’t happen at all. GridNav puts spatial planning in the same tool as optimization and financial analysis, closing the last gap in the pre-development workflow.
Most energy analysis tools are built by engineers, for engineers. When a non-technical user enters an unusual input combination, the tool either silently produces garbage results or crashes with a cryptic error. GridNav does neither.
Meaningful warnings, not silent failures. When a user ventures into advanced territory — unusual tariff structures, export-level inputs, edge-case configurations — GridNav surfaces clear, contextual guidance explaining what the input means and what to consider. The system steers users toward valid configurations before they waste time on a failed analysis.
Help text on everything. Every input field, every result metric, every chart has contextual explanation in plain language. A municipal planner who has never heard of “critical load fraction” hovers over it and immediately understands what they’re configuring.
Progressive complexity. The default configuration produces a valid, meaningful result. Advanced features are available but revealed progressively. Users who need simplicity get simplicity. Users who need depth find it when they go looking.
Every competitor has a learning curve measured in hours or days. GridNav’s is measured in minutes.
GridNav offers an unauthenticated “try it now” experience where prospects run a real DOE-grade optimization without creating an account. Results are gated — enough to demonstrate the depth and quality of the analysis, with full results unlocked on signup. No sales call required, no demo scheduling, no friction between curiosity and conversion.
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