Waabi raises up to $1 billion and partners with Uber to deploy 25,000 robotaxis as the race to dominate self-driving heats up

Waabi raised $1 billion to accelerate commercial deployments, consisting of a $750 million Series C led by Khosla Ventures and G2 Venture Partners plus a $250 million milestone-based investment from Uber tied to deploying at least 25,000 robotaxis on Uber’s platform; the company says this is the largest fundraise in Canadian history. Investors include Uber, Nvidia’s NVentures, Volvo Group Venture Capital, Porsche Automobil Holding SE, BlackRock, Radical Ventures and an ADIA subsidiary; Waabi declined to disclose a valuation (reported earlier as seeking $3 billion). Founder and CEO Raquel Urtasun said the company is expanding from autonomous trucking to robotaxis using the same end-to-end AI models, with Uber already a board investor, though rollout timing and initial locations remain undisclosed.

Analysis

Market structure: Uber (UBER) and cloud/AI compute suppliers (NVDA) are the direct beneficiaries—Uber gains distribution/scale (25k robotaxi potential) and Nvidia benefits from increased GPU/RTU demand and NVentures alignment. OEM partners (Volvo, Porsche) and large asset managers (BLK, ADIA) get optionality; pure-play lidar/sensor specialists and legacy Tier-1s reliant on hand-coded stacks are the likely losers as end-to-end models compress their TAM. Expect upward pressure on NVDA hardware demand and data services for 12–36 months; sensor demand becomes bifurcated (vision-first vs lidar) depressing mid-size lidar vendor multiples immediately.

Risk assessment: Tail risks include a major safety incident or adverse regulation that could wipe 20–50% off early-stage AV valuations and cause immediate re-pricing of UBER and participating OEM debt. Near-term (days–weeks) volatility will be driven by announcements of pilot cities and milestone funding draws; medium-term (3–12 months) risk centers on Volvo’s validation and Uber’s deployment cadence; long-term (2–5 years) outcome hinges on unit economics (target breakeven utilization >60% and vehicle capex <$80k). Hidden dependencies: Waabi’s milestones, Nvidia hardware availability, and Uber’s regulatory approvals are binary catalysts.

Trade implications: Tactical: overweight NVDA exposure via 6–12 month call spreads to capture contract wins and semiconductor tailwinds; establish a modest 2–4% long in UBER equity or 12-month call spreads to ride distribution optionality while capping cost. Defensive/relative: hedge ride-hail beta by buying 3–6 month puts on TSLA (1–2% portfolio) or short small-cap lidar (size 0.5–1%) to play sensor consolidation; shift 1–3% allocation from traditional auto suppliers into AI/semis and fleet software names.

Contrarian angles: Consensus understates execution friction—Waymo’s decade-long commercialization shows scale does not equal near-term profits, and Waabi’s milestone funding implies downside if deployments slip. The market may be underpricing the liability/regulatory tail (one high-profile accident could trigger moratoria), so implied vols for UBER/NVDA could spike 40–80% on bad news; consider convex option hedges rather than outright large directional bets.

Key Decisions for Investors

• Establish a 2–3% portfolio long in NVDA via a 9–12 month call spread (buy 30% OTM call, sell 60% OTM call) to capture increased GPU demand for AV training/edge compute; size to limit max loss to ~2% of portfolio and take profits if NVDA rises >40% within 6 months.
• Initiate a 3% long position in UBER equity within 1–3 months or use a 12-month 25% OTM call spread (cap upside) to play distribution of 25k robotaxis; trim if Uber fails to announce first deployment city within 90 days or misses a milestone payment to Waabi.
• Reduce exposure to traditional Tier-1 auto suppliers by 1–3% and reallocate into AI/semiconductor exposure (NVDA, MSFT exposure via cloud) over the next quarter as end-to-end AV architectures likely compress supplier TAM.
• Hedge AV/regulatory tail: buy 3–6 month ATM puts on TSLA sized at 1% of portfolio (or equivalent put spreads) to protect against industry-wide adverse news; alternatively short 0.5–1% exposure in public lidar/sensor pure-plays if available.
• Trigger-based monitoring: if Waabi+Uber announce first city and vehicle-free trials within 90 days, increase UBER/NVDA exposure by another 1–2%; if Volvo delays full validation beyond two quarters, reduce UBER exposure by 50% and cover short lidar positions.