The client had proven the technology. The harder question was whether it could become a business. Specifically: how do you scale autonomous ride-hail commercially without assuming the capital burden of owning a fleet?
Engaged to build the business value case. A financial model and partnership framework that would answer whether the asset-light model could work, what the economics looked like for both the company and its partners, and which path to market made sense. This is the define layer: before anyone builds or fixes anything, someone has to determine whether the model is viable at all.
Can the economics work?
At 2,500 vehicles, is unit economics viable enough to attract fleet operators and capital without the company owning assets?
Who owns what?
Franchise model (partner-owned fleet) vs. corporate model (operator-owned fleet). Different risk, return, and scalability profiles for each party.
What makes a partner say yes?
Fleet operators, rental companies, PE firms, OEM dealerships. Each with different motivations. The case had to prove ROI for the partner, not just the client.
Trust as the gating factor
The client's equity as a technology company was strong. Its equity as a ride-hail provider was nascent. Consumer adoption was the variable that would make or break unit economics.
What drives ROI?
Charging costs were ~80% of OpEx. Making energy infrastructure the primary lever for partner economics, not fleet size.
Regulatory surface
AV regulation evolving at federal and local levels simultaneously. Any commercial model had to account for constraints that would shift.
First-Principles Financial Model
Two revenue split scenarios modeled (20/80 and 70/30 client / fleet operator), projecting NOI for both parties and isolating the variables that most affected partner returns.
Partnership Framework
Franchise vs. corporate structures evaluated across fleet operators, rental companies, PE firms, OEM dealerships, robo-taxi fleets, and consumer brands.
Recommendation: Franchise-First
Lower client CapEx, faster market entry, consumer brand partnerships as the adoption accelerant. Delivered to program leadership.
Client NOI · asset-light
At the asset-light split, the client retains the technology premium while offloading capital risk. And still projects $61M NOI at initial scale.
Fleet Operator NOI
Partner economics compelling enough to attract capital without the client subsidizing the deal. Asset-light works for both sides.
Fleet operator 3-yr ROI
Returns are consistent across fleet sizes. Ride volume is the primary driver, not scale. A 500-vehicle operator has a viable business case.
Client 3-yr ROI · corporate model
Even absorbing full OpEx including charging, the client's returns create headroom to subsidize partner adoption.
Primary OpEx lever
Charging is ~80% of total OpEx. Energy cost management is the single biggest lever for improving partner economics.
Path-to-market recommendation
Lower CapEx, faster entry, existing fleet operators as the most viable first partners. Consumer brand partnerships as trust accelerant.
Modeled projection, not an achieved result. Figures represent what the asset-light path returned under the assumptions agreed with leadership.
She was able to articulately speak to each lever and bring it to a higher level executive narrative.