Governed autonomy: The path to enterprise Agentic AI

We stand at the cusp of Agentic AI reshaping the modern enterprise. AI Agents promise an efficiently replicated digital workforce with superhuman capabilities. Tasks that were previously tedious, expensive, or simply impossible for a human-only enterprise are now suddenly within reach. 

However, this new digital workforce brings novel challenges: although AI Agents today are already extremely capable, they are also woefully unpredictable. This chaotic nature demands an evolution in how we connect and govern our private data and systems. The question is no longer, “Can we build intelligent agents?” But, “How can we govern, scale, and trust them?” 

At Redpanda, we believe the answer lies in a new kind of data architecture: the Agentic Data Plane (ADP).

The missing layer for the Agentic era

As AI agents rapidly progress from simple copilots into autonomous digital workers, the systems beneath them — data pipelines, governance policies, access controls — must mature in unison. The Agentic Data Plane is that evolution: a managed, governed data control plane that connects agents with enterprise data safely and seamlessly. 

To build the ADP, we intertwined three foundational architectural pieces with a single uniform governance layer: 

• Redpanda Streaming - wicked fast distributed log
• Redpanda Connect - broad connectivity suite
• Oxla - recently acquired, nimble, high-performance SQL query engine 

With open standards like MCP and A2A, the ADP lets agents run inside the plane or via governed proxies and exposes focused MCP servers for context while keeping every prompt, tool call, and action inside a unified audit and lineage envelope.

The path to governed connectivity

An effective agentic workforce requires access to every private data source and system in the enterprise. Agents must meet data and systems where they are, within the private networks they exist in; forklifting all of that data into an external walled garden is a non-starter for many.

The ADP takes our broad connectivity suite and adds the ability to create lightweight MCP servers on top. “Pshaw!” you say. “Everybody and their brother has an MCP server these days. How is that interesting?” On the surface, it’s not. But adding MCP to the ADP’s interconnectivity layer transforms it into an agentic governance layer between all the data systems and agents connecting through it. And that, my friend, is very interesting indeed, as effective governance is the key to unlocking enterprise agentic workforces.

A transformative acquisition

Context starts with connectivity, but it doesn’t stop there. Transformation and querying are required as well. To that end, Redpanda has acquired Oxla, a next-generation distributed SQL engine purpose-built for high-performance federated analytics. Oxla’s C++-based engine will power low-latency, massively parallel, agentic SQL access across live streams and point-in-time data. This acquisition transforms the ADP into a truly agent-ready query platform, supporting materialized views for streaming transformations and federated queries spanning Apache Iceberg^™, Apache Kafka^® topics, and a broad suite of legacy data sources.

Agents can reason over unbounded, real-time datasets with warehouse-grade precision using SQL as their universal interface and access context through lightweight MCP servers. They can also integrate with external vector databases or use the ADP’s built-in knowledge base. This flexibility allows enterprises to use the best models and tools — OpenAI, Anthropic, OSS, or fully bespoke — without re-plumbing their data or compromising on governance.

The key to enterprise Agentic AI: governance

The ADP treats every agent interaction as a first-class durable event: prompts, inputs, context retrieval, tool calls, outputs, and actions are captured for analysis, compliance, and replay. These events allow platform teams to reproduce behavior, diagnose drift, and prove outcomes.

With this foundation, platform teams can:

• Rewind and replay agent runs to debug or validate behaviors.
• Enforce service-level objectives for latency, accuracy, and cost.
• Trace agent decisions end-to-end — from input to action to outcome.
  

The result is trustworthy autonomy — intelligence that can be proven, audited, and trusted. All powered by a durable, queryable event log to capture every agent decision, enable replay, enforce backpressure, and uphold exactly-once processing across tool chains. Streaming turns opaque agent behavior into governed, provable workflows.

From Agentic chaos to autonomous order

At its core, the Agentic Data Plane is a managed, governed access layer built to meet enterprises where they are. It interconnects every data modality — APIs, events, vector databases, and tables — under one control plane.

But connectivity without control is chaos. That’s why the ADP embeds Agentic Access Control (AAC), an evolution of modern access control concepts tailored to the needs of an agentic workforce. Agents never hold long-lived credentials. Every prompt, action, and output is auditable, replayable, and policy-checked before and after I/O, empowering enterprises to grant AI agents fine-grained, temporary access to sensitive data without losing oversight — a critical milestone on the path to Enterprise AI.

Agentic AI that meets you where you are

Deploy ADP the way your risk model demands: VPC/BYOC, on-prem/air-gapped, or fully managed cloud. Keep data resident, satisfy regional controls, and bring AI to your private systems — not the other way around. Agents can run inside ADP or via proxy in your environment.

Calling enterprise AI builders

AI agents promise efficiency gains once thought impossible, but without control, they introduce new forms of operational and compliance risk.

Enterprises adopting the Agentic Data Plane gain:

• Governance at scale: unified policies, short-lived credentials, and complete lineage.
• Observability by design: tracing, metrics, and replay across all agents.
• Connectivity without compromise: multi-modal data access with regional and regulatory controls.
• Sovereignty and choice: deploy in your own cloud, on-premises, or multi-cloud environments.
  

This is how organizations can finally tame the chaos of autonomy — not by limiting AI, but by giving it a governed foundation to grow on. The Agentic Data Plane is that foundation. It’s how enterprises will connect and control AI agents acting across their global data estates, and how they’ll prove those agents act responsibly.

Join us in defining this new frontier. Contact Redpanda to get early access to the Agentic Data Plane.