Three integrated platforms.
Each platform is production-grade on its own. Together, they form the operating fabric for AI-native enterprises — cloud operations, governed data and agents that act on both.
Cloud Platform
Cyberia Cloud is the single entry point to the platform: a unified web console where every product runs behind shared sign-in, one navigation panel and pinned tabs. From the portal home teams see notifications, releases, security advisories and training, then jump straight into identity, container fleets, secrets or data — with the same Kubernetes-native control planes, policy-as-code and zero-trust networking underneath.
- Auth Manager — orgs, apps, SSO, email branding
- MicroServicesOps — hosts, projects, visual designer
- SecretOps — vaults, environments, rotations, CLI
- Data Studio — buckets, catalogs, queries
- Kubernetes-native control planes
- Policy-as-code and zero-trust networking
- GitOps delivery and environment promotion
- FinOps budgets, quotas and cost attribution
Data Platform
Cyberia Dataspace treats every dataset as a product. Raw imaging, LiDAR, genomic, tick and graph data lands in an open lakehouse, is catalogued, lineage-tracked and published as governed data products that feed Power BI, Looker, Tableau, Excel, notebooks, agents and downstream ML — without copies or drift.
- Tables, files and object storage
- Imaging, LiDAR and genomic arrays
- Tick and time-series streams
- Property graphs and knowledge graphs
- Open table formats: Iceberg, Delta, TileDB
- Versioned, governed data products
- End-to-end lineage and impact analysis
- Feeds for Power BI, Looker, Tableau, Excel, agents
Agentic Platform
We build agentic systems that do real work: planners and specialised agents coordinating over your APIs, databases and documents through typed tools and MCP servers. Every run is grounded by retrieval and memory, constrained by policy guardrails and human approvals, and measured with evaluation suites, tracing and per-token cost budgets — so autonomy ships to production without losing control.
- Task and workflow agents over your APIs
- Data-product and ML forecasting agents
- Research agents — drug discovery, molecule search
- Assistants with skills, playbooks and libraries
- Typed tools and MCP server integrations
- Retrieval, memory and knowledge graphs
- Guardrails, evals and human-in-the-loop
- Tracing, cost budgets and observability
