Deployment Options
Finally, AI deployment that works with your reality - not against it. Whether you're spinning up fast with public APIs or need everything locked down behind your firewall.
Supported Deployment Models
1. Cloud-Native API Access
Sometimes, the fastest path to value is just plugging into what already works. Use battle-tested models from the providers who’ve already figured out the scaling headaches:
- OpenAI (including Azure-hosted GPT)
- Google Cloud (Gemini)
- Anthropic
- Cohere
Benefits:
- Get your first AI agent running this week, not next quarter
- Zero infrastructure headaches – someone else handles the GPUs and updates
2. Self-Managed Cloud
Want the best of both worlds? You get enterprise-grade control without the hardware procurement nightmares. Perfect for teams who need to see under the hood but don’t want to become infrastructure experts.
- Containerized via Docker, orchestrated with Kubernetes
- GPU acceleration that scales up and down based on actual usage
- Fine-grained cost controls so you’re not surprised by your cloud bill
Best for:
- Companies that need complete visibility into what their AI is doing
- Teams running hybrid setups (mixing open-source models with API calls)
3. On-Prem / Air-Gapped
When compliance isn’t optional, and your data absolutely cannot leave your building. We help you run powerful AI models on your hardware with all the security controls your auditor’s demand.
- Deploy open-source models (LLaMA, Mixtral, Falcon) on your servers
- Built-in compliance features for healthcare, finance, and government requirements
- Custom monitoring, encrypted memory stores, local vector databases
Use cases:
- Industries where regulatory compliance isn’t negotiable (HIPAA, SOC2)
- Protecting sensitive IP and proprietary data workflows
Why Deployment Flexibility Matters
Here's what we've learned after deploying AI for dozens of enterprises: one size doesn't fit all. Your fast-moving marketing team might be pleased with OpenAI's APIs, while your legal department needs everything running on servers they can physically touch. That's why we built our platform to work everywhere - from the most permissive cloud setups to the most paranoid air-gapped environments because the best AI solution is the one that gets deployed and used.
Architecture & Isolation Layers
Regardless of where you deploy, security and observability become standard. Every setup includes the foundational pieces that enterprise IT teams expect:
Memory separation
Using proven solutions like Chroma, Weaviate, or Redis
Model sandboxing
With execution policies that prevent runaway processes
Comprehensive logging
And tracing so you can debug issues before they become problems
Enterprise integrations
With your existing SIEM, audit systems, and role-based access controls
Tooling Stack Compatibility
We don't believe in vendor lock-in. No matter which deployment option you choose, you get full compatibility with the tools your team already knows and loves:
LLMOps tools
Monitoring
Orchestration frameworks
Deployment Decision Matrix
Fastest prototype
Cloud-native APIs
Infrastructure control
Self-managed cloud
Highest security/compliance
On-prem / air-gapped
Multi-model hybrid workflows
Cloud + local model routing
Cost optimization at scale
Quantized self-hosted models