Architecture

Dataworkz Agentic AI Architecture.

Connectors. AI-optimized information extraction, storage, and retrieval. A full agentic AI framework. Managed agent ops from prototype to production. Underpinned by managed authentication and observability across every layer.

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The stack

One integrated stack.

Every Dataworkz agent runs on the same foundation — connectors, an AI-ready information layer, a full agentic framework, and managed ops, with governance throughout. Watch a single run move through the whole stack.

Dataworkz Platform z 100%
Platform
one stack
Layer 01
Connectors
100+ sources
Layer 02
Information Layer
AI-ready
Layer 03
Agentic Framework
tools · memory
Layer 04
Managed Ops
governed
Structured
Unstructured
Vector RAG
Knowledge graph
Skills · MCP
Eval
Deploy
Trace · audit
Layer 01

Connectors

100+ sources
StructuredUnstructured
Layer 02

Information Layer

AI-ready
Vector RAGKnowledge graph
Layer 03

Agentic Framework

tools · memory
Skills · MCPEval
Layer 04

Managed Ops

governed
DeployTrace · audit
dataworkz / your-stack

Layered by design — every agent runs on the same connectors, information layer, framework, and ops. Build one workflow, reuse the whole foundation for the next.

Governed end to end — chunk-level RBAC, full traces, and audit at every layer. Nothing runs without the controls your production teams require.

Fully extensible — connect MCP, custom APIs, custom skills, or your own codebase. The stack adapts to how your team already builds.

Across every layer Observability & traces Managed authentication Chunk-level RBAC Full audit trail
Anatomy of an agent

Four components per agent.

Every Dataworkz agent is composed of four building blocks. Tools and memory are configured in the Agent Designer. Plans are generated dynamically by reasoning, or pre-defined as deterministic execution.

01
Tools

Configured by the Agent Designer. The set of capabilities the agent can call: system actions, retrieval, external APIs.

02
Memory

Short-term and long-term context the agent carries across steps and sessions. Inherited governance from the Information Layer.

03
Dynamic Reasoning Plan

Created on the fly by a Reasoning LLM. The agent picks tools, executes them, feeds results back, and decides what to do next.

04
Deterministic Execution Plan

Pre-defined workflow authored once by your team. Same input, same path, same output, every run. Audit-traceable end to end.

Integration

Dataworkz agents are open and embeddable.

Built on standard protocols. Composable across vendors. Yours to walk away with whenever you want.

Open
Standard protocols. No lock-in.
  • A2A protocol support. Agent-to-agent handoff across the platform and external agents built on the A2A standard.
  • MCP compatible. Model Context Protocol, your agents call tools exposed by other systems, and your tools can be called by external agents.
  • REST APIs for all platform capabilities. Trigger, configure, observe, and audit every agent programmatically.
  • Export agents as standalone containers. Your agents are yours, including when you take them with you.
Embeddable
Surface agents where work actually happens.
  • Embed agents in any web or mobile app. SDK-based integration with your existing experience.
  • White-label chat and workflow UIs. Your brand, your design, our agent runtime.
  • Integrate with existing enterprise tools. Slack, Teams, Salesforce, ServiceNow, drop the agent in where your team already is.

One stack. Every agent your team ships.

Connectors, information layer, agent framework, and managed agent ops, running on the same DSL with managed authentication and observability across every layer.

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