AI compatibility, infrastructure-first
Opsphere works with your existing AI stack — OpenAI, Mistral, or custom models — without making AI the centre of the story.
THE AI STACK PROBLEM
AI models change faster than your operations toolchain
Teams adopt OpenAI, Mistral, Anthropic, and custom models in parallel — but operational context rarely follows the model layer.
Bolt-on AI dashboards treat models as the product story. Infrastructure teams need intelligence that respects existing topology, incidents, and runbooks.
The result: model lock-in, fragmented context, and AI experiments that never reach production reliability workflows.
Model churn breaks integrations
Every new model endpoint means new adapters, new credentials, and new failure modes — without a unified operations layer.
No infrastructure-native context
Generic AI tools do not understand your service graph, deployment history, or incident patterns when generating recommendations.
AI hype without operational grounding
Experiments stay in sandboxes because there is no bridge between model output and the systems your SRE team actually runs.
MODEL COMPATIBILITY
Plug models in without rebuilding ops
Opsphere sits between your infrastructure graph and the models you choose — infrastructure context flows in; operational output stays consistent regardless of provider.
Bring Your Keys
Connect OpenAI, Mistral, or custom endpoints with your own API keys on Team and Enterprise plans. Credentials stay in your control; Opsphere never resells tokens by default.
Inject Infrastructure Context
Every model call receives live topology, incident history, and resource state — not generic system prompts disconnected from what actually runs in production.
Route & Govern Output
Policy-controlled routing picks approved models per environment or data class. Runbooks, summaries, and remediation drafts use the same Opsphere data model no matter which engine generates them.
COMPATIBILITY
Engineered for multi-model operations
Swap models without rebuilding your operational intelligence layer.
Provider-agnostic connectors
Native integrations for OpenAI and Mistral with an extension path for custom and on-prem models.
Infrastructure context injection
Model prompts receive live topology, incident history, and resource state — not generic system messages.
Policy-controlled model routing
Route workloads to approved models per environment, team, or data classification without code changes.
Consistent operational output
Runbooks, summaries, and remediation steps use the same Opsphere data model regardless of which model generates them.
Future-proof model slots
Add new model providers through configuration — the platform UI and incident workflows stay stable.
AI Compatibility Specifications
- Supported model providers
- OpenAI · Mistral
- Custom model slots
- Enterprise
- Key management
- BYO default
- Managed token packs
- Optional add-on
- Routing policy
- Per environment
- On-prem model support
- Enterprise
- Prompt audit trail
- 90 days
- Data residency options
- Enterprise
- Model failover
- Configurable
MULTI-MODEL FLOW
Models swap; operations stay stable
AI-Compatible Opsphere Stack
Infrastructure context is the constant — the model layer is interchangeable.
Model Provider Layer
OpenAI · Mistral · Custom endpoints · On-prem inference — selected per policy, not hardcoded in product UI.
Opsphere Intelligence Core
Topology graph · Incident history · Runbook schema · Token governance — unchanged when you add or swap a model.
Read-Only Infrastructure Connectors
AWS · Kubernetes · CI/CD · Observability — the signals that ground every model response in production reality.
Your Production Stack
The systems your SRE team runs — not the models marketing slides talk about.
GET STARTED
AI-compatible, infrastructure-first operations.
Connect your AI stack to Opsphere and bring intelligence to your operations.