DEPLOYDatabase

Company

Wayve

UK embodied-AI / autonomous-driving company (London; founded 2017) building the AI Driver end-to-end driving foundation model + GAIA generative world models;…

Founded
2017
HQ
London, United Kingdom
Status
private (~$1.05B Series C 2024; ~$1.2B round 2026)

Overview

UK embodied-AI / autonomous-driving company (London; founded 2017) building the AI Driver end-to-end driving foundation model + GAIA generative world models; OEM-agnostic licensed brain (SoftBank/Nvidia-backed).

Verified record

Verified deployments
None on file
Active incidents
None on file

DEPLOY Intelligence

Market intelligence for physical AI

Analyst-grade signals, competitive tracking, and investment context across the global physical AI landscape. Launching 2026.

Key facts

Models

AI Driver (AV2.0 driving FM) + GAIA generative world models + LINGO.

Distinction

Foundation-model-first, OEM-agnostic LICENSED brain (vs captive robotaxi stacks); Nissan ProPilot FY2027.

Backers

SoftBank and Nvidia

Focus area

Embodied AI

AI Driver architecture

End-to-end driving foundation model

Funding

$1.2B Series D at $8.6B valuation (Feb 2026); led by NVIDIA, Uber, Mercedes-Benz, Stellantis, Nissan; total ~$1.6B+

Data & sources

Press releases

1

News coverage

1

Research

1

3 sources backing this record.View all →

Explainers

Plain-language answers to the questions people ask about Wayve, from DEPLOY’s explainer library. Each is written in the language of the question and cross-checked against this registry.

  • What is Wayve?

    Wayve is a UK-based brain-provider building foundation-model-for-driving for autonomous vehicles. Per Agent A source-depth hygiene: $8.6B valuation following Series D February 2026 (largest UK AI Series D on record). Model lineage: AI Driver (production end-to-end driving model deployed via OEM integration) + GAIA-3 (generative world model for driving simulation). Production deployment via Stellantis STLA AutoDrive partnership: commercial-tier deployment maturity (rare in the foundation-model brain-provider cohort). Cohort positioning: foundation-model-for-driving tier distinct from foundation-model-for-robotics (PI) + foundation-model-for-physical-AI-general (NVIDIA GR00T) + foundation-model-for-robotic-manipulation (Covariant) cohort tiers.

  • How does DEPLOY track partnership lifecycle state?

    DEPLOY tracks partnership lifecycle state as a four-state framework operating at relationship-graph granularity: announced (verified-from-press-release; not-yet-active) → active (verified-deployed or verified-shipped; current_status=true) → dissolved (terminated; current_status=false with end_date populated) → unverified-current-state (announced-but-no-update-since; cap-flag honest-absence). Per Agent A's Arc C substrate, 18 partnerships + 32 parties + 14 external counterparties (via XOR pattern) + NVIDIA 4-counterparty multi-party-partnership node verified at primary-source-anchored depth. The canonical lifecycle worked example: Figure × OpenAI announced 2024 → dissolved February 2025 (status=dissolved + endDate populated). The external-name XOR pattern (partnership_parties.company_id when counterparty is tracked entity; external_name when counterparty is genuinely not-in-registry; OpenAI + Uber + Nissan + Microsoft as canonical worked examples) operates as verification-posture discipline at relationship-graph granularity. Cap-flag-as-trust-signal operates recursively on partnership framing.

  • How does DEPLOY track cross-cluster talent-flow as diaspora graph?

    DEPLOY tracks cross-cluster talent-flow at primary-source-anchored PersonCompany-edge granularity per Arc A people graph substrate. The diaspora graph framework operates at three canonical pattern classes: post-wind-down diaspora (Cruise canonical worked example; founders + executives + technical leadership transition across multiple destinations after corporate wind-down); license-and-hire diaspora (Amazon × Covariant canonical worked example; co-founders + ~25% staff transition to acquirer while standalone entity continues under remaining leadership); adjacent-employer-prior diaspora (Meta AI / FAIR + Google X / Everyday Robots as recurring prior employers in brain-providers and humanoid cohort hires). Each pattern class operates at distinct PersonCompany-edge structure: current_role=false with end_date populated + where-they-went edge (post-wind-down + license-and-hire); current_role=true with prior-employer edge at honest-absence end_date if no specific tenure-end disclosed (adjacent-employer-prior). The framework reads talent-flow at four substrate-axis granularity: source company + destination company + role transition + tenure date precision; cap-flag-as-trust-signal operates recursively on diaspora framing same as on any other relationship-record claim depth. Cross-property bidirectional discipline operational: PersonCompany edges cross-reference acquisition records (Cruise wind-down ↔ GM full re-absorption Acquisition record; Covariant license_and_hire ↔ Amazon × Covariant Acquisition record) + partnership records + entity records simultaneously.

Current leadership (13)

Founders (2)

Board (2)

Former / Previously (1)

  • Amar Shah Co-founder & initial CEO (2017-2020)secondary-verified

Safety record

No incidents on record for Wayve.

Only active incidents are counted. Retracted incidents are excluded from this summary but remain reachable at their canonical URLs.

Full safety record: incidents, sourcing, and exposure data →

Brains developed (1)

Recent coverage

Wayve in third-party press