Kubernetes-native agentic AI platform where developers create agents in simple YAML configs. Infrastructure automation, data workflows, business processes — all self-hosted and scalable.
Every team wants to deploy AI agents for their specific use cases — infrastructure automation, data processing, customer support, business workflows. You need a platform that makes agent deployment as simple as any other Kubernetes workload.
Teams build agents in isolation without shared tools or knowledge. Managing agent lifecycle, scaling, and interactions becomes a nightmare across multiple use cases.
Per-token pricing from SaaS AI services makes scaling agents prohibitively expensive. Cost predictability becomes impossible as agent usage grows.
Regulated industries can't send business data to external AI services. Compliance requirements demand self-hosted, auditable AI systems.
Three core capabilities that make deploying agents as simple as deploying any other Kubernetes workload.
Create agents using simple YAML configurations — just like any Kubernetes resource. Define agent capabilities, tools, memory, and permissions. Deploy via GitOps alongside your other workloads.
Agents run on your infrastructure with self-hosted LLMs, security gateway, and agent memory. No external API calls, complete data sovereignty, cost-optimized with Kubernetes autoscaling.
Build complex workflows where agents collaborate via Model Context Protocol (MCP). Shared tools, knowledge bases, and agent memory enable sophisticated multi-agent systems.
Everything runs inside your infrastructure. Self-hosted platform, your cloud, your rules.
YAML-defined agents deployed via GitOps. Same change management you already use. Agents are version-controlled, auditable, and reviewable across all use cases.
Zero data sent to OpenAI, Anthropic, or any external API. LLMs run on your GPU nodes inside your VPC. PCI-DSS, HIPAA, SOC2 compatible.
Prompt guardrails enforced at the gateway layer. Every agent action logged with full audit trail. Rate limiting, content filtering, and access control built in.
Self-learning memory that enables agents to build knowledge over time. World Facts, Experience Facts, and Mental Models that improve agent performance.
No rip-and-replace. Plugs into the tools your team already uses.
Built for regulated industries where data sovereignty isn't optional.
Zero data sent to external AI providers. Models run on your GPU nodes in your VPC.
Every agent action is logged, timestamped, and attributable. Complete visibility for compliance.
Agents propose actions, humans approve — until your team is confident enough to enable autonomous mode.
Deployed via ArgoCD with the same change management, PR reviews, and rollback capabilities you already use.
If your MTTR doesn't improve by 40% or more within 60 days, you get a full refund. No questions asked.
Schedule a Demo →Proven at a Fortune 1000 company • Running in production for 6+ months