Tailored to your needs. 100% secure.
A 39 GB base model + 60 MB adapter, packaged in Docker, deployed via CI/CD to serverless H100 GPUs — or installed directly on your infrastructure. Choose the deployment model that fits your security posture. Upgrade when you are ready.
Docker · RunPod Serverless · H100 80GB · GitHub Actions CI/CD · <60s cold start
DEPLOYMENT MODELS
Which model fits your situation?
There is no wrong choice. Each model delivers the same Vector intelligence with the same domain depth. The difference is where it runs and who manages the infrastructure.
On-Premise
Your infrastructure. Your rules. Zero data leaves.
Run DBR77 Vector entirely on the client's own servers. Production data, transformation plans, and AI reasoning never leave the client's security perimeter.
Best for
Regulated industries, sensitive IP, strict internal security policies, and OT-governed environments.
- Complete control over model runtime, data, and access
- No external network dependency for inference
- Strongest alignment with legal, OT, and procurement requirements
- Ideal for plants with air-gapped or restricted networks
Private Dedicated API
Isolated environment. Enterprise-grade. Faster than on-premise.
A dedicated hosted environment exclusively for one client, with full isolation, predictable performance, and no shared infrastructure.
Best for
Companies that want isolation and security without managing the underlying infrastructure themselves.
- Dedicated compute and storage — no multi-tenancy
- Client-specific access controls and encryption
- Faster deployment than on-premise with comparable security
- Managed updates and scaling without internal DevOps burden
Shared API
Fast start. Low friction. Perfect for pilots.
A lower-friction entry path for pilot programs, workshops, and rapid experimentation — still governed by enterprise-grade security policies.
Best for
Fast evaluation, guided pilots, training workshops, and lower-sensitivity exploratory use cases.
- Fastest time to first value
- Lowest entry cost and simplest onboarding
- Enterprise security policies still apply
- Easy upgrade path to private or on-premise when ready
ARCHITECTURE
From your question to an expert answer.
Every query follows the same secure, serverless path. No data stored. Designed for controlled, auditable inference.
Your App
Frontend / API client
HTTPS POST
Encrypted + API key
Serverless Inference Layer
GPU orchestration
Elastic GPU Runtime
Scales on demand
Containerized Runtime
Portable inference stack
DBR77 Vector 120B
Full model inference
Structured Response
Secure result delivery
Your App
Frontend / API client
HTTPS POST
Encrypted + API key
Serverless Inference Layer
GPU orchestration
Elastic GPU Runtime
Scales on demand
Containerized Runtime
Portable inference stack
DBR77 Vector 120B
Full model inference
Structured Response
Secure result delivery
INFRASTRUCTURE
What runs under the hood.
Docker Runtime
DBR77 Vector runs inside a Docker container with PyTorch and a custom handler.py inference endpoint. The full 20B parameter model is loaded into GPU memory. Fully portable across any GPU infrastructure.
RunPod Serverless
Default cloud deployment uses RunPod Serverless on A100/H100 80GB GPUs. Scales to zero when idle — you pay only for GPU seconds during inference. No idle servers, no wasted compute.
CI/CD Pipeline
Automated via GitHub Actions. Code push triggers Docker build, pushes to Docker Hub, and deploys to RunPod. Every deployment is versioned, reproducible, and auditable.
Cold Start & Performance
When the GPU wakes from idle, the full model (39 GB) and adapter (60 MB) load into VRAM in under 60 seconds. Subsequent queries within the session are near-instant.
Not sure which model fits? Let us help.
Book a demo to see Vector running live, or start by trying it inside our products — no infrastructure decisions needed.