A Developer’s Guide to Integrating Neysa Aegis LLM Shield
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Reliably Deploy Models at Scale
Deploy and run open-source models seamlessly on dedicated inference endpoints built on Neysa’s AI-native, enterprise-grade GPU cloud infrastructure.
Built for Production
Scale Deployment
Inference Endpoints are purpose-built for live production environments and real-world AI applications. Easily deploy and scale open-source or open-weight models with dedicated resources that are custom built for your specific use-case — while maintaining full cost visibility and configuration control.
Full Control
Single-tenant deployments for complete control and isolation
Scalable
Flexible infrastructure that allows you to scale as your traffic spikes
Cost Efficient
Delivers best-in-class price-to-performance at scale
Fast
Low-latency, high-throughput inference powered by AI-native infrastructure
Access Leading
Open-Source and Open-Weight Models
Use our API to access models like DeepSeek, Llama, Mistral, Qwen, and more — all optimized for a wide range of use cases.
- Deploy within seconds.
- OpenAI-compatible endpoints
- Best model options for Chat, Image, Audio, Vision, Code, and more use-cases.
- GPU Usage-based pricing
Predictable Performance
Proven Results
Experience consistent, high-performance inference — more tokens per second, lower latency, and optimized throughput even under heavy workloads. Neysa’s endpoints let you do more with less.
Qwen/Qwen3-Coder-30B-A3B-Instruct
Output throughput: 351 tokens per second Time to first token: 108 (ms)
Endpoint configuration:
- Context length: 256k
- GPU used: 1X H100
- Parallel queries: concurrency of 10 requests at a time
- Quantization: fp8
Openai/gpt-oss-120b
Output throughput: 386 tokens per second Time to first token: 188(ms)
Endpoint configuration:
- Context length: 128k
- GPU used: 1X H100
- Parallel queries: concurrency of 10 requests at a time
- Quantization: fp8
Meta-llama/Llama-3.3-70B-Instruct
Output throughput: 127 tokens per second Time to first token: 390(ms)
Endpoint configuration:
- Context length: 256k
- GPU used: 2X H100
- Parallel queries: concurrency of 10 requests at a time
- Quantization: fp8
Built for Full Control and Customization
Get dedicated single-tenant inference endpoints running on vLLM, deployed on reserved monthly GPUs for guaranteed availability and security and ability to customize every aspect of your endpoint
- Enterprise-grade security with full isolation
- Flexible GPU configurations to match workload requirements
- Firewall and context length controls for access and performance tuning
- Workspace-based access management for AI/ML teams
Customize with the Power of Top NVIDIA GPUs
Choose from a wide range of NVIDIA GPU configurations, including the latest H100 series and more. Neysa’s AI-optimized infrastructure ensures guaranteed uptime, low latency, and high availability — no matter your deployment scale.
- Comprehensive GPU configuration options
- Enterprise-grade reliability and uptime
- Optimized for AI and inference workloads
Security and Privacy-First Design
Security and compliance are embedded into every layer of Neysa’s platform — both at the cloud infrastructure and model level.
Cloud & Infrastructure Security
Strict compliance and security controls ensure your data remains protected. Includes RBAC, audit logs, policy enforcement, encryption, and zero-trust access.
Model Security
Your AI models are secured by default, enabling safe deployment of AI/ML projects across cloud and on-premises environments.
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ISO 27001:2022
ISO 27017:2015
ISO 27018:2019