OwnAI — one intelligent platform for every open-weight model
OwnAIOpen multimodal intelligence platform
Llama
Kimi
FLUX
Hugging Face
NVIDIA
Qwen
DeepSeek
Mistral
Hunyuan
Phi-4
Whisper
Stable Diffusion
Nomic
Neo4j
MongoDB
Red HatLlamaKimiFLUXHugging FaceNVIDIAQwenDeepSeekMistralHunyuanPhi-4WhisperStable DiffusionNomicNeo4jMongoDBRed HatLlamaKimiFLUXHugging FaceNVIDIAQwenDeepSeekMistralHunyuanPhi-4WhisperStable DiffusionNomicNeo4jMongoDBRed HatOne workspace
Introducing unlimited tokens.
One workspace.
Chat, drafting and long-form generation.
Analysis, planning and multi-step problem solving.
Write, review, debug and build software.
Investigate, compare and synthesize sources.
Read, transform and work across project files.
Generate, edit and transform visual assets.
Prompt, generate and process moving media.
Speech generation, recognition and language control.
Generate and compose audio in the same workspace.
Build workflows that act across models and tools.
One intelligent platform.
Every open-weight model.
Cloud or local. Run anywhere.
Annual cost model
Complete AI stack over 12 months.
Blended annual cost of a mid-size AI workload across four stacks. In this illustrative model, OwnAI + OwnCloud is materially lower than proprietary paths.
Multiple AI subscriptions
$0
Proprietary APIs
$0
Open models on hyperscaler
$0
OwnAI + OwnCloud
$0
Capability matrix
One platform. More choice across both layers.
| OwnAI | ChatGPT | Claude | Gemini | Kimi | Hugging Face | |
|---|---|---|---|---|---|---|
| Text & reasoning | Yes | Yes | Yes | Yes | Yes | Models available |
| Coding | Yes | Yes | Yes | Yes | Yes | Models available |
| Image generation | Yes | Yes | No native | Yes | Limited | Models available |
| Video generation | Yes | Sora ecosystem | No | Yes | Limited | Models available |
| Voice & audio | Yes | Yes | Limited | Yes | Limited | Models available |
| Music generation | Yes | Limited | No | Limited | Limited | Models available |
| Multiple open-model choice | Yes | No | No | Limited | Primarily Kimi | Yes |
| Automatic model selection | Yes | Closed routing | Closed routing | Closed routing | Closed routing | Manual |
| Model + infra optimization | Yes | No user control | No user control | Limited | No user control | Partial |
| Provider choice | Yes | No | No | No | No | Yes |
| Region & hardware choice | Yes | No | No | Limited | No | Yes |
| Dedicated deployment | Yes | Enterprise | Enterprise | Enterprise | Limited | Yes |
| Model hosting | Integrated | APIs | APIs | Vertex ecosystem | APIs | Yes |
| Visual agent builder | Yes | Partial | Partial | Partial | Agent tools | External |
| Compute cost visibility | Yes | No | No | Separate bill | No | Yes |
| Stablecoin payments | Supported | No | No | No | No | No |
| Shared multimodal workspace | Yes | Yes | Partial | Yes | Partial | No unified studio |
ChatGPT
Claude
Gemini
Kimi
Hugging FaceWhy OwnAI
Four reasons OwnAI is different.
AI Model Accessibility
10.0/10
Access across every major modality
AI Model Privacy
9.2/10
Greater model and deployment control
AI Cost Reduction
9.3/10
Model + infrastructure cost optimization
User Savings
8.5/10
Total value delivered to the user
Execution control
Privacy begins with control.
Where the work runs is part of the AI decision. OwnAI lets the user choose the execution zone, model, provider, region, infrastructure type and retention policy instead of making infrastructure invisible and fixed.
Own 1
Private local execution for work that should remain on hardware the user owns.
- Mode
- Private
- Network required
- No
- Data route
- Local
Your infrastructure
Deploy to a private server or organization-controlled infrastructure.
- Mode
- Sovereign
- Provider
- User selected
- Region
- User selected
OwnCloud
Scale onto competitively selected infrastructure when the workload needs more compute.
- Mode
- Scale
- Provider
- Optimized / manual
- Hardware
- Workload matched
Model
AutoRoute or manual
Provider
Optimized or selected
Region
User selected
Infrastructure
Shared or dedicated
Retention
Configurable
Logging
Configurable
Storage location
User selected
Project export
Available
Local execution
Available
Compute cost
Visible
Ten into one
Replace the stack.
Stop switching between AI tools. The same project should not require separate subscriptions, separate context, separate model APIs and separate deployment workflows.
Fragmented AI stack
Many products. Many bills.
- Chat subscriptionSeparate
- Coding subscriptionSeparate
- Image toolSeparate
- Video toolSeparate
- Voice toolSeparate
- Agent platformSeparate
- Model APIsSeparate
- Cloud hostingSeparate
OwnAI
One project. One shared AI stack.
- Text + reasoningIncluded
- Code + researchIncluded
- Image + videoIncluded
- Voice + musicIncluded
- AgentsIncluded
- Model selectionAutoRoute
- ComputeOwnCloud
- DeploymentBuilt in
Double optimization
Every workload is optimized twice.
OwnAI first finds the best qualified intelligence for the job. Then OwnCloud finds the most efficient infrastructure underneath it.
01 · Model optimizer
Choose the intelligence.
- QualityTask fit
- SpeedLatency / throughput
- CostSuccessful outcome
- ContextWindow / memory
- ModalityText · image · video · audio
- LicenceUsage fit
- PrivacyExecution requirements
- HardwareRuntime efficiency
02 · Infrastructure optimizer
Choose the machine.
- GPUQualified hardware
- ProviderMarket choice
- RegionJurisdiction / latency
- MemoryWorkload requirement
- AvailabilityLive capacity
- LatencyRoute quality
- PriceMarket efficiency
Illustrative AutoRoute
Best cost / quality with region privacy.
- Selected modelOpen · 70B chat
- InfrastructureOwnCloud · A100 80GB · EU-West
- PrivacyDedicated · retention off
- Est. model cost$0.42 / 1M tokens
- Est. infra cost$1.86 / hour
- Est. saving-64% vs proprietary API
Benchmark programme
OwnAI does not need one model to win.
As new models appear, OwnAI discovers them, benchmarks them and learns which workloads they are genuinely qualified to run.
0
Models benchmarked
Across the current internal benchmark programme.
0
Benchmark runs
Published internal test history.
0
Modalities benchmarked
Across the referenced benchmark dataset.
0
Execution zones
Own 1 · your infrastructure · OwnCloud.
0
Frontier models trained
OwnAI optimizes access rather than training a proprietary frontier model.
Research engine
The open-model market becomes OwnAI’s research engine.
New open and open-weight models can move from release to benchmark to deployment without forcing the user to rebuild their AI environment around a new vendor.
Released
A new model enters the market.
Discovered
OwnAI adds it to the candidate registry.
Benchmarked
Real workloads test capability and efficiency.
Hosted
Qualified models become deployable through OwnCloud.
Available
Users can select it manually or through AutoRoute.
Routed
The right model is selected when a task needs it.
Workspace & execution platform
Create with AI. Build on AI. Deploy AI.
The same environment can create content, build agents, host models, expose endpoints and deploy AI-powered applications.
Visual agent builder
Compose model and tool workflows in the same environment.
Model hosting
Host qualified models through connected infrastructure.
Fine-tuning
Adapt models where customization is needed.
API endpoints
Expose models and workflows as callable services.
Application deployment
Move from prototype to running AI application.
Workflow automation
Trigger multi-model workflows from events and schedules.
Agent budgets
Bound how much autonomous workflows may spend.
Payments
Support machine-readable payment paths where enabled.
Service publishing
Turn AI capability into a reusable service.
Inside OwnX
OwnAI is the intelligence layer of the stack.
It sits between the compute market below and the user-owned operating environment above.
Earth Compute discovers it. OwnCloud powers it.
OwnAI chooses and creates with it.