Managed cloud
For teams ready to start a programme
- Opsin-operated infrastructure
- Isolated customer data and model access
- Scientific onboarding and ongoing support
Your science. Your environment. Your control.
Bring Octopus to the environment your research demands. From managed cloud to your own infrastructure, your compounds, results and private models stay under your control.
Your intellectual property stays yours
You own the data you bring and the outputs produced from it. Your compounds, assay history and programme-specific models remain private to your organisation.
Learning from your assays improves your models. Customer data is never used to train shared models or another customer’s models without your explicit written consent.
From requirements to the first programme
Data location is part of the deployment design. Before the first programme runs, we agree where compounds and assay history, private model versions, inference and audit records live, and how approved services connect.
Access, data flows and external integrations stay governed by your deployment policy.
01
Scope the environment
Align scientific goals, hosting and identity, then set the boundary around application data, inference and backups. The operating model is the first decision, and the rest of the deployment follows from it.
orDedicated environment
For organisations with specific IT requirements
- Dedicated compute and storage
- Agreed hosting region and network boundaries
- Organisation-specific identity and access policies
orYour infrastructure
For programmes that stay inside your perimeter
- Customer cloud or on-premise installation
- Inference and private models inside your environment
- Deployment and update plans agreed with your IT team
02
Connect data and models
Bring in historical assays, private model endpoints and the compute resources your programme needs.
- Historical assays and compound data
- Private model endpoints
- Programme compute resources
- Your identity provider
03
Validate together
Review access, data handling and representative analyses with your scientific and IT teams.
- Access
- Roles and permissions against your own directory
- Data handling
- Retention, export and deletion under your policy
- Analyses
- Representative runs on your data, not a demo set
- Operations
- Escalation paths and named technical contacts
04
Launch with support
Train your researchers and agree scientific reviews, support contacts and operating responsibilities.
Security that supports the way you work
Give researchers room to collaborate while your organisation controls access, operations and the lifecycle of its data.
Identity & permissions
Connect enterprise single sign-on, enforce multi-factor authentication and assign role-based permissions to the people working on each programme.
Encryption & isolation
Protect data in transit and at rest. Separate customer data, model artefacts and compute access across the deployment.
Audit & provenance
Trace access and changes alongside the scientific record. Every result links to the model, dataset and run that produced it.
Retention & deletion
Define how long programme data is retained, export it when needed and request deletion under an agreed data lifecycle.
Backup & recovery
Agree backup location, retention and recovery objectives with your team, with recovery procedures tested against the deployment plan.
Controlled operations
Manage updates, privileged access and incident response through an agreed operating model, with named technical contacts.