Introducing Nasiko: The Control Plane for AI Agents

AI is moving beyond chatbots. The current shift in the ecosystem is toward AI agents that can reason, use tools, access APIs, interact with databases, coordinate with other agents, and execute workflows autonomously. Frameworks like LangChain , CrewAI , OpenAI , Anthropic , Microsoft Agent Framework, and LangGraph AI are accelerating how quickly developers can build intelligent systems.

But while building agents has become easier, managing them in production is becoming harder. That is the problem Nasiko is solving.

Nasiko is building a control plane for AI agents. Instead of acting as another agent framework, Nasiko sits underneath the ecosystem and standardizes how agents are registered, discovered, routed, secured, deployed, and monitored across environments.

Nasiko positions itself as the missing operational layer for this new generation of software.

The platform works across frameworks like LangChain, CrewAI, Claude, and Custom Agent architectures, allowing teams to use their preferred development stack without locking themselves into a single ecosystem.

Nasiko focuses on four major infrastructure layers:

Registry and discovery for managing agent capabilities, versions, and workflows. Routing and orchestration for coordinating multi agent, multi user execution. Policy and security for centralized access control and runtime governance. Observability and monitoring for tracing workflows, debugging failures, and understanding agent behavior in production.

This aligns closely with the current direction of the AI industry. One of the biggest trends in 2026 is the rise of multi agent systems and agent orchestration. Developers are moving from single prompt applications toward distributed systems where multiple agents collaborate together. That shift creates operational challenges around reliability, visibility, and control.

Our Key focus is on the observability layer. Teams are realizing that AI agents cannot operate as black boxes in production. Developers need visibility into tool calls, execution paths, routing decisions, failures, and system behavior. Nasiko integrates observability directly into the platform with monitoring, tracing, analytics, and runtime visibility for AI systems.

Nasiko also follows an open source and self hosted approach. Developers can run agents locally, deploy through CLI workflows, integrate with CI/CD pipelines, connect APIs and vector databases, and scale workflows gradually into production environments.

The broader AI ecosystem is rapidly moving toward infrastructure for agent operations instead of isolated experimentation. The focus is no longer just building smarter models. The focus is building reliable systems around those models.

Nasiko is building that agent orchestration layer for the agentic era.