Da2a: An Open-Source Multi-Agent Data Platform Prototype Using the A2A Collaboration Protocol
Traditional data platforms required deep technical expertise and specialized data engineering, creating bottlenecks that left business decision-makers waiting days or weeks for answers and entirely dependent on overloaded engineering teams.
The traditional approach required filing tickets with data engineering teams, building ETL pipelines, writing SQL queries, and waiting for reports — a slow sequential process where answers could become irrelevant before they arrived.
The Da2a prototype demonstrates that a multi-agent system using the A2A protocol can answer complex cross-domain business questions by delegating sub-tasks to specialized agents, abstracting the underlying engineering complexity.
Frequently asked questions
What did this team achieve with this AI workflow?
The Da2a prototype demonstrates that a multi-agent system using the A2A protocol can answer complex cross-domain business questions by delegating sub-tasks to specialized agents, abstracting the underlying engineering…
What tools did this team use?
Da2a, Agent-to-Agent (A2A) protocol, Agent Development Kit.
What results were reported?
Complex multi-step task handling: tackle complex, multi-step tasks that require synthesizing information from different domains; Engineering complexity abstraction: abstracts the underlying engineering complexity (source-reported, not independently verified).
What failed first in this deployment?
The traditional approach required filing tickets with data engineering teams, building ETL pipelines, writing SQL queries, and waiting for reports — a slow sequential process where answers could become irrelevant befo…
How is this back office ops AI workflow structured?
User asks orchestrator → Orchestrator plans and delegates → A2A inter-agent communication → Domain agents execute sub-tasks.