The platformto build
The Enterprise
AI Platform.
Unified API for all models, intelligent routing, credit-based pricing, and output guardrails — built for teams that need reliability and cost control.
Unified API
One API key for 1000+ models — Claude Opus 4.6, GPT-5, Gemini 3.1, DeepSeek V3.2, Qwen 3.5, and more. Text, image, video, audio. No juggling providers.
Get your.Deploy.Scale.

Heterogeneous
by design.
Our inference cloud slices and executes across NVIDIA, AMD, ARM, and custom accelerators. Sub-50ms latency. SLA-aware scheduling at machine speed.
Heterogeneous compute nodes — NVIDIA, AMD, ARM, and custom accelerators for maximum throughput per watt.
Performance you
can measure.
One API,
every model.
1000+ models from every major provider. One API key, one billing dashboard, zero vendor lock-in.
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Trust is
non-negotiable.
Agentic workloads operating across heterogeneous hardware demand zero-trust security at every layer — not bolted on, built in from day one.
Isolated execution
Each workload runs in sandboxed environments with zero cross-contamination.
End-to-end encryption
AES-256 encryption at rest, TLS 1.3 in transit. Zero plaintext exposure.
Full audit trails
Every request logged, every decision traceable. Complete observability.
Permission boundaries
Granular API key scoping. Models, endpoints, and usage limits per key.
Programmatic-first.
Research-grade.
OpenAI-compatible API backed by multi-silicon inference. Change your base URL, keep your SDK. Every request is routed to optimal hardware.
OpenAI-compatible
Drop-in replacement. No rewrites.
Streaming support
Full SSE streaming across every provider.
Multi-silicon routing
1000+ models optimized across heterogeneous hardware.
Credit-based billing
100 credits = $1 USD. Pay only for usage.
Trusted by teams worldwide.
Moving to NeoLab's multi-silicon inference cut our per-token costs by 60% while actually reducing latency.
David Park
CTO, Lumino AI
Pay for
results.
All packages include API access and all 35+ models. Claude Opus 4.6 requires $99.99+ cumulative spend.
Stop leaving
performance on the table.
Heterogeneous execution slices your models across the most optimal silicon for each workload. One API, every model, every chip — inference at machine speed.










