Kubiya

Transforms business KPIs into technical execution across the entire AI lifecycle, including planning, building, and operating.

Executes full engineering projects, from initial business intent to deployed outcomes, through an AI-driven system.

Guarantees verifiable and reproducible outputs for AI tasks, ensuring reliability over probabilistic text generation.

Manages the entire operational lifecycle, covering planning, deployment, maintenance, and day-2 operations for AI systems.

Provides policy enforcement, auditable execution, and proactive alerting for secure and compliant operations.

Standardizes and automates compliance and regulatory frameworks through policy definitions as code.

Incorporates zero-trust principles, isolated sandboxing with microVMs, and comprehensive auditability for all operations.

Offers a robust and scalable architecture with durable orchestration for managing long-running tasks efficiently.

Ensures secure and pollution-proof execution of tasks by isolating them within individual micro-virtual machines.

Allows dynamic scaling by adding distributed task workers across various environments (production, staging, dev, on-prem).

Provides a real-time, comprehensive understanding of all infrastructure, code, and data resources.

Continuously syncs live data from various sources like AWS, Kubernetes, GitHub, and Jira as systems change.

Understands complex relationships and dependencies across the infrastructure for informed agent decisions.

Seamlessly connects to virtually any system, API, or data source without requiring changes to existing infrastructure.

Supports a wide range of secure authentication protocols including AWS IAM, OAuth2, SAML, OIDC, and JWT.

Integrates with current technology stacks, including Kubernetes, without needing to replace or alter existing systems.

Asynchronously synchronizes with connected resources to maintain an always up-to-date context graph.