Agent layer for SaaS with grounded answers, sandboxed tools, and per-customer isolation
Stage
Not given
Not given
Founded
Not given
Not given
Based in
US
Not given
Pricing model
Paid
Free
Pricing
Usage-based pay-as-you-go pricing with hourly compute charges; committed contracts available for volume discounts. Hosted option with Anyscale-managed infrastructure or Bring Your Own Cloud deployment available.
Free during launch period. Customers pay their LLM provider directly for model usage at provider rates; Oberik does not markup or resell tokens. No credit card required, no usage meters tracked by Oberik itself.
Key features
Multimodal data curation at scale
Distributed model training with elastic scaling
Batch embedding generation at scale
Multi-cloud deployment and orchestration
Cluster-backed development environments
Workload-specific observability and debugging
Production-grade managed Ray clusters
Access control and governance
GPU budget controls and cost attribution
Post-training with SkyRL and veRL support
Document-grounded answers with page and quote citations
Linux sandbox environment for agent execution
Per-customer cost tracking and billing
Memory and wiki persistence across sessions
Scheduled and recurring work with durability
Capability-scoped JWT tokens enforced per-request
Support for custom tools and MCP servers
Multi-model support with bring-your-own-keys
Server-side prompt injection and PII screening
SSH dashboard interface for programmatic configuration
What makes it different
Built by creators of Ray, the world's most widely adopted AI compute engine
Multi-cloud deployment without code changes
Feels local but runs distributed
Unified GPU pooling across clouds and regions
Hard isolation between customers with no shared state or tenant leakage
Citations with document, page and quote provided automatically with every answer
Only two API calls needed to integrate grounded AI into any SaaS product
Customers never charged by Oberik; direct billing from their own LLM provider keys
Oberik