Your tenant. Your identity. Your data control.
Energy companies handle sensitive operational data, proprietary processes, and regulated information. Brightwire deploys private AI where you choose — in-tenant cloud / VPC, on-prem, or air-gap — so control stays with your security and identity boundaries.
Why Private AI Matters for Energy
When your AI tools process operational data through external cloud services, that data is outside your control. For energy companies, that's often a non-starter.
Regulatory Compliance
Energy companies operate under strict regulatory frameworks. When operational data, compliance records, or grid information gets processed through third-party cloud services, it creates compliance complexity that's hard to manage and harder to audit.
Intellectual Property
Your operational procedures, maintenance protocols, performance data, and institutional knowledge are competitive advantages. Sending them to external AI providers means trusting someone else to protect your IP — and hoping their terms of service don't change.
Operational Data Sensitivity
Real-time production data, equipment performance metrics, and grid information are sensitive by nature. Private AI ensures this data stays within your security perimeter — processed locally, stored locally, controlled by you.
How Brightwire Deploys Private AI
We set up AI inside boundaries you control. Sensitive workloads stay in your tenant, VPC, or on-prem environment — with your identity provider, logging, and data-handling rules. Hybrid is fine: private for proprietary ops data; public cloud only where you explicitly allow it.
We deploy models in your cloud tenant, private VPC, or on your hardware. Inference stays inside the boundary you choose — including air-gapped patterns when required.
Ingestion, indexing, and retrieval happen inside your chosen environment. Manuals, procedures, and reports stay under your control — not a multi-tenant vendor default.
For the most sensitive environments, we deploy systems that operate fully air-gapped — no external network connections at all. Updates and model improvements are delivered physically.
We help you spec and procure the right hardware, or deploy on equipment you already have. You own the infrastructure — we manage the software.
Cloud AI vs. Private AI
Cloud-Based AI
Your data is sent to external servers for processing
Provider terms of service may allow data use for training
Compliance audit trails are harder to maintain
Internet connectivity required — single point of failure
Costs scale with usage — API bills can surprise you as adoption grows
Latency varies with provider load and network conditions
Vendor lock-in — you're dependent on one provider's pricing, policies, and availability
Fastest access to latest models
No hardware investment needed
Private AI
RecommendedData stays inside your approved tenant / network boundary
Full control over data retention and usage
Simplified compliance — everything is auditable in-house
Works offline — no internet dependency
Predictable costs — fixed hardware investment, no per-query API bills
Consistent millisecond latency — no variability from network or provider load
No vendor lock-in — switch models freely, on your terms
Requires hardware investment
Model updates require manual deployment
Many of our clients use a hybrid approach: private AI for sensitive operational data, cloud AI for general-purpose tasks that don't involve proprietary information. Brightwire helps you draw the line and implement both.
What We Handle
Hardware Sizing
We spec the right hardware for your workload — GPUs, memory, storage — so you don't over- or under-invest.
Model Selection
We choose and configure the right open-source models for your use case — optimized for your hardware and your data.
Deployment & Config
Full deployment, security hardening, and integration with your existing authentication and access control systems.
Ongoing Support
Monitoring, updates, model improvements, and troubleshooting — we manage the platform so you don't have to hire AI engineers.
Choose the deployment that fits your risk model
Let's talk about private AI for your organization — in-tenant cloud, VPC, on-prem, or air-gap. We'll assess needs, recommend an approach, and show how it fits the broader roadmap.