48 companies in the Modeling Warehouse run on Hybrid, and how directly they consume their foundational models. Avg Foundation Proximity Score 78/100.
AI/LLM · Hybrid · Native (own / self-hosted weights)
Aleph Alpha’s current product layer appears to be PhariaAI, a sovereign enterprise stack that includes knowledge capture, development, operation, access control, and monitoring components. Public materials also show first-party API access and containerized deployment patterns, but the exact production datastore and hosting mix are not fully disclosed, so the infrastructure is best characterized as hybrid rather than purely on-prem or purely cloud.[2][5][10]
Telecom · Hybrid · Native (own / self-hosted weights)
Telecom; in-house network ML plus partner LLMs (Ask AT&T on Azure OpenAI) for employees.
Banking (EU) · Hybrid · Native (own / self-hosted weights)
European bank; in-house risk ML plus Mistral for EU-sovereign generative AI.
Travel · Hybrid · Native (own / self-hosted weights)
Travel marketplace; huge own ranking/pricing ML plus OpenAI for the AI Trip Planner.
Social/Consumer · Hybrid · Native (own / self-hosted weights)
ByteDance runs a large-scale hybrid architecture with proprietary cloud-native data and streaming systems (ByteHouse, ByteHTAP, ByteMQ/Flux) atop commodity storage and compute, tightly integrated with recommendation and multimodal AI stacks for products like TikTok/Douyin and robotics.[1][3][6][7][8][9] Real-time streaming (Kafka/ByteMQ), HTAP, and on-device AI infrastructure (Pitaya) form the core substrate for online training, inference, and global content delivery.[1][2][3][8][10][11]
Telecom/Media · Hybrid · Native (own / self-hosted weights)
Cable/media; own voice-remote + network ML plus partner LLMs for assistants.
Cybersecurity · Hybrid · Native (own / self-hosted weights)
Self-Learning AI built in-house; models the network rather than calling an LLM.
AI/Translation · Hybrid · Native (own / self-hosted weights)
European MT leader training its own translation + writing models on its own EU infrastructure.
Hardware/Enterprise · Hybrid · Native (own / self-hosted weights)
Dell AI Factory packages on-prem open models (Llama) + partners (Cohere) for enterprise/sovereign deployment.
Media · Hybrid · Native (own / self-hosted weights)
Media/parks; large in-house recommendation/VFX ML plus partner LLMs for assistants; cautious GenAI posture.
Gaming · Hybrid · Native (own / self-hosted weights)
Game publisher; large in-house animation/matchmaking ML plus partner LLMs for tooling.
Gaming · Hybrid · Native (own / self-hosted weights)
Unreal Engine + Fortnite; in-house generative/animation ML (MetaHuman) on its own infra.
Robotics · Hybrid · Native (own / self-hosted weights)
Figure’s production architecture is centered on its in-house **Helix** vision-language-action stack running on vertically integrated humanoid hardware and a proprietary BotQ manufacturing/software infrastructure, with robots streaming high-bandwidth data for continuous training and fleet improvement[1][2][7][9]. Core control and reasoning have moved off external LLMs to fully in-house Helix models, with cloud services used as supporting infrastructure rather than as foundational AI engines[7][9].
IT (Japan) · Hybrid · Native (own / self-hosted weights)
Builds Takane, its own enterprise Japanese LLM (with Cohere), for regulated/government use.
AI/LLM · Hybrid · Native (own / self-hosted weights)
Liquid AI builds and serves its own Liquid Foundation Models (LFM and LFM2) with a custom hybrid liquid/convolution/attention architecture, optimized for both data-center and fully on-device deployment across CPUs, GPUs, and NPUs.[1][3][4][9][11] Public materials emphasize hardware-in-the-loop training and edge/PC deployment, but do not expose a full production cloud stack, suggesting a mix of self-hosted/model-serving infrastructure plus OEM/partner integrations rather than a single public hyperscaler.[9][11]
Image AI · Hybrid · Native (own / self-hosted weights)
Midjourney runs a proprietary latent diffusion image model pipeline behind a Discord bot and web UI, with prompts flowing through a request-handling layer into GPU clusters for model inference, then storing generated images in large-scale object storage fronted by a CDN.[5][9] Public information focuses on model architecture and system-design patterns; specific cloud vendor, database products, and formal compliance regimes are not disclosed.[1][5][9]
Internet · Hybrid · Native (own / self-hosted weights)
NAVER runs its core portal and AI services primarily on **on-premise data centers** such as the GAK Sejong facility, increasingly augmented by NAVER Cloud’s sovereign AI infrastructure built with NVIDIA DSX and AMD EPYC/Instinct platforms for large-scale training and inference.[2][4][5][6][7] The production stack is vertically integrated—NAVER controls the data centers, cloud layer (NAVER Cloud), and proprietary foundation models like HyperCLOVA X, exposed as services to internal products and external partners.[2][5][7]
AI/LLM · Hybrid · Native (own / self-hosted weights)
OpenAI runs large GPU superclusters and Kubernetes-based orchestration across Azure and its own data centers in a hybrid setup, with Azure as the primary cloud and custom HPC clusters (e.g., Stargate) for training and serving frontier models.[15][16][19] Core application and API workloads use relational stores like PostgreSQL for accounts/settings and globally scalable databases such as Azure Cosmos DB plus Kafka streams for high-volume conversation, analytics, and event data.[1][8][12]
Telecom (EU) · Hybrid · Native (own / self-hosted weights)
European telecom partnering with Mistral for sovereign LLMs over its own network ML.
Robotics · Hybrid · Native (own / self-hosted weights)
Physical Intelligence runs a proprietary robotics foundation model stack with large-scale training and data infrastructure, using WEKA for high-performance data and Oracle Cloud Infrastructure for hosted compute, complemented by Kubernetes-based CI/CD and GPU-heavy cloud environments.[1][2][7][11][12] The architecture centers on Python/C++ robotics services, PyTorch/JAX-based model training on cloud GPUs, and data pipelines from robot teleoperation and simulation into foundation model training and evaluation.[11][12]
E-Commerce (Japan) · Hybrid · Native (own / self-hosted weights)
Japanese commerce/fintech ecosystem training its own Japanese-first Rakuten AI models.
Gaming · Hybrid · Native (own / self-hosted weights)
League/Valorant maker; in-house anti-cheat + matchmaking ML on its own infra; off the foundational-LLM map at the core.
Gaming · Hybrid · Native (own / self-hosted weights)
UGC gaming platform on its own data centers; trains its own generative models for 3D/code creation assistants.
Enterprise · Hybrid · Native (own / self-hosted weights)
Joule is multi-model: SAP’s own ABAP LLM plus a Generative AI Hub fronting OpenAI, Gemini, Anthropic (Claude powers Joule agents), Llama, and sovereign Mistral/Cohere on SAP cloud.
Defense · Hybrid · Native (own / self-hosted weights)
Builds Hivemind, its own autonomy foundation for GPS/comms-denied flight.
Conglomerate (Japan) · Hybrid · Native (own / self-hosted weights)
Telecom/investment group building its own Japanese LLMs (Sarashina) plus partner models; major AI-infra investor.
Automotive · Hybrid · Native (own / self-hosted weights)
Tesla runs a vertically integrated, edge-first architecture where custom FSD hardware in vehicles and robots performs real-time inference, while a hybrid cloud (including AWS and in-house GPU clusters) ingests telemetry into Kafka/Flink streams, S3/LakeFS lakes, and Snowflake/BigQuery warehouses for continuous model training and OTA updates.[1][7][8][10] Production for cars, energy products, and robots is tightly coupled to this AI and data infrastructure, effectively making Gigafactories and AI clusters part of a single closed-loop manufacturing and autonomy system.[2][6][7]
AI Infra · Hybrid · Native (own / self-hosted weights)
Together AI operates its own GPU cloud and managed Kubernetes clusters as an AI-native infrastructure layer, while also integrating with external cloud storage and streaming services for data and analytics workloads.[2][11][12] The production stack is centered on open-weight models deployed as containerized workloads on Together-managed GPU clusters, exposed via serverless inference APIs and voice/agent pipelines.[3][4][9][11][16]
Telecom · Hybrid · Native (own / self-hosted weights)
Telecom running its own network ML; customer/agent assistants on Google Cloud Gemini.
HR · Hybrid · Native (own / self-hosted weights)
Runs Illuminate, its own ~800B-parameter LLM trained on HR/finance data from 10,500+ customers (800B transactions/yr) for privacy + enterprise fit; acquired Sana (2025) for custom AI agents.
Communications · Hybrid · Native (own / self-hosted weights)
Runs its own global data centers for real-time media, bursting to AWS/Oracle Cloud at peak. AI Companion uses a 'federated' approach blending its own models with Anthropic and OpenAI.
Productivity · Hybrid · Direct API
Asana runs a large-scale, stateful, microservice-style backend with autoscaling infrastructure and a dedicated Production Infrastructure pod for observability and platform reliability, layered behind a multi-region, hybrid cloud deployment. Its data stack separates transactional MySQL/Aurora stores from analytical event pipelines and a cloud data warehouse used by growth and analytics teams.
FinTech (EU) · Hybrid · Direct API
European neobank; Finn AI assistant on OpenAI over account data.
Healthcare (EU) · Hybrid · Direct API
European health-booking platform; AI assistants built on Mistral for EU data-sovereignty.
Storage · Hybrid · Direct API
Famously repatriated bulk file storage off AWS onto its own 'Magic Pocket' exabyte infrastructure while keeping some cloud for edge/compute. Metadata in sharded MySQL (Edgestore). Dropbox Dash AI uses OpenAI.
Defense · Hybrid · Direct API
Helsing operates a hybrid of secure cloud and sovereign/on‑prem defense environments built around Python/C++/Rust, PyTorch, and Kubernetes for AI workloads and telemetry/simulation data processing, integrated into physical Resilience Factories for production of autonomous and EW systems.[1][3][4] Their core software stack ingests multi‑sensor and weapons‑system data to provide real‑time battlefield insights and decision support rather than public, consumer-facing LLM services.[5][6]
Website Builder · Hybrid · Direct API
Website/commerce builder historically on its own data centers, increasingly cloud-hybrid; polyglot persistence (MySQL/MongoDB/Cassandra). AI site-generation and copy use OpenAI.
Website Builder · Hybrid · Direct API
Site builder; AI site/content generation on OpenAI.
Healthcare · Hybrid · Cloud-hosted (Bedrock/Vertex/Azure)
Dominant EHR on its own InterSystems stack; generative features run on Azure OpenAI via the Microsoft partnership.
Govtech/Data · Hybrid · Cloud-hosted (Bedrock/Vertex/Azure)
Palantir runs three tightly integrated proprietary platforms—Foundry (data operations), AIP (generative AI), and Apollo (continuous delivery)—as a managed SaaS that can be deployed across public clouds and on-prem/sovereign infrastructure, with customers bringing their own data platforms and ML tooling into Foundry’s integration and ontology layers.[1][5][7][8] Operationally, this yields a hybrid architecture: Palantir provides the application/AI stack while underlying compute, storage, and some databases reside in customer-selected environments (AWS/GCP/Azure/OCI/private/on-prem) including recent NVIDIA and Dell sovereign AI reference architectures.[2][3][4][6]
Cybersecurity · Hybrid · Off the LLM map (in-house non-LLM ML)
1Password’s production architecture is centered on a zero-knowledge, end-to-end encrypted vault service, where plaintext is encrypted on the client before reaching 1Password’s servers. Publicly available sources confirm hybrid cloud deployment patterns for components such as the SCIM bridge, but they do not reliably expose the company’s full internal database stack or all backend infrastructure details.
Defense · Hybrid · Off the LLM map (in-house non-LLM ML)
Anduril’s production architecture is built around its proprietary **Lattice** autonomy platform as the software backbone for autonomous systems and the **Arsenal** software-defined manufacturing stack, integrating sensor fusion, decision logic, and production control across a mix of cloud and tightly controlled on‑prem deployments.[10][12][13] Public material focuses on capabilities and manufacturing rather than concrete cloud/database vendor disclosures, so specific underlying services (e.g., exact clouds and DB engines) remain intentionally opaque.[3][10][12]
FinTech · Hybrid · Off the LLM map (in-house non-LLM ML)
Global payments processor on its own infrastructure; large in-house fraud/risk ML; off the foundational-LLM map at the core.
Streaming Media · Hybrid · Off the LLM map (in-house non-LLM ML)
Netflix runs a cloud‑native microservices control plane almost entirely on AWS (EC2, RDS/MySQL, DynamoDB, Cassandra, CockroachDB, Kafka, S3, etc.) while its proprietary Open Connect CDN appliances form a separate data plane deployed at ISPs for video delivery.[2][3][6][12] Client apps (web, mobile, TV) talk to backend microservices via APIs/GraphQL, with extensive use of in‑house open‑source tooling (Zuul, Eureka, Spinnaker, EVCache) and AWS services for storage, streaming, and analytics.[3][6][8][12]
FinTech · Hybrid · Off the LLM map (in-house non-LLM ML)
Massive in-house fraud/risk ML on its own infrastructure; off the LLM map at the core.
Aerospace · Hybrid · Off the LLM map (in-house non-LLM ML)
Rockets + Starlink; massive in-house autonomy/vision/control ML; off the foundational-LLM map at the core.
Mobility · Hybrid · Off the LLM map (in-house non-LLM ML)
Uber runs thousands of microservices on a hybrid cloud with multiple active data centers, using Docker on Mesos/Aurora, Kafka + Flink/Spark + Pinot/Presto/HDFS for real-time and batch data, and in-house layers like Michelangelo AI as a model gateway on top of this foundation.[11][16][3][9][6] Core operational data lives in Schemaless/Docstore on MySQL plus Cassandra/Riak, with extensive self-hosted open-source infrastructure (Kafka, Flink, Pinot, Spark, Presto, HDFS, Elasticsearch) augmented by proprietary platforms such as Michelangelo and Zero Growth Stack.[11][3][9][13][6]
Retail · Hybrid · Off the LLM map (in-house non-LLM ML)
Walmart’s production architecture is hybrid and multi-cloud: public-cloud workloads run across Azure and Google Cloud, while core infrastructure and brokers remain within Walmart-controlled private cloud environments.[1][2][7][10][15] The platform is heavily event-driven and containerized, with Kafka as a central backbone and WCNP/Kubernetes used for consumer workloads across clouds.[1][4]