Keep AI where your data already lives.
For some organizations, cloud deployment is not an option.
Security requirements, regulatory obligations, operational risk, network constraints, and internal policy may require AI systems to run entirely within controlled infrastructure.
Backboard enables teams to build and operate advanced AI applications without sending sensitive data, prompts, documents, or workflows outside their environment.
Deploy inside your own data center or private network
Keep sensitive data within your infrastructure
Run approved models locally
Control access, logging, retention, and governance
Integrate with internal identity and security systems
Support isolated and restricted network environments
Reduce dependence on external APIs and shared platforms
AI infrastructure built for controlled environments.
Backboard provides the core systems required to operate useful AI applications on-premise.
Instead of assembling separate tools for models, memory, retrieval, orchestration, and governance, teams can run a unified AI foundation inside their own environment.
Built for internal deployment
Private model access and routing
Persistent memory across users and workflows
Retrieval over internal documents and knowledge systems
AI assistants and workflow automation
Controlled tool access and permissions
Integration with internal databases and applications
Environment-specific security and governance policies
Your teams can build capable AI systems without creating new external data paths.
Run the models that fit your hardware and policy requirements.
On-premise deployment gives organizations more control over the models they use and how workloads are processed.
Backboard supports flexible model strategies across open-weight, optimized, and custom models that can run inside your environment.
Build around your own requirements
Run approved open-weight models locally
Use quantized models for efficient deployment on available hardware
Support custom or post-trained models for specialized use cases
Route workloads based on latency, cost, performance, and sensitivity
Keep applications portable as models improve
Reduce reliance on centralized model providers
This makes it possible to build AI systems that align with your infrastructure, not the other way around.
Designed for sensitive and mission-critical use cases.
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Government and Defense
Operate AI systems in secure, restricted, or disconnected environments where data control and operational resilience are essential.
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Financial Services and Insurance
Keep confidential customer, transaction, and internal operational data within tightly controlled systems.
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Healthcare and Life Sciences
Use AI for research, operations, and knowledge workflows while maintaining control over regulated and proprietary information.
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Critical Infrastructure and Industrial Operations
Deploy AI close to operational systems where latency, reliability, privacy, and local control matter.
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Enterprise Engineering Teams
Build internal copilots, document intelligence, software development tools, and workflow automation without relying on public AI platforms.
Build once. Operate with confidence.
On-premise AI does not need to mean building everything from scratch.
Backboard gives organizations a practical foundation for running modern AI inside their own infrastructure while maintaining flexibility as models, hardware, and requirements evolve.