Questflow Raises $6.5M to Power the Next Generation of On-Chain AI Agent Workflows

Questflow, a platform designed to orchestrate the growing multi-agent AI economy, has secured $6.5 million in seed funding. The round was led by CyberFund and joined by notable investors including Delphi Labs, Systemic Ventures, Eden Block, White Star Capital, Web3.com, Animoca Brands, HashKey Capital, Wagmi Ventures, ElizaOS, the Tezos Foundation, and CatcherVC. Additional grants came from Aptos, Coinbase Developer Platform, and Virtuals Protocol.

With this funding, Questflow aims to build an always-on AI workforce that automates any workflow for individuals and businesses—operating 24/7 on-chain while preserving human oversight for essential decisions.

Introducing MAOP: The Multi-Agent Orchestration Protocol

At the core of Questflow’s platform is the Multi-Agent Orchestration Protocol (MAOP). This protocol allows multiple AI agents to communicate, coordinate, and transact autonomously on-chain, unlocking real-time collaboration between agents.

Our mission is clear: create an AI agent economy for every workflow,” said Bob Xu, co-founder and CEO of Questflow. “From freelancers to large enterprises, everyone needs an AI team that works tirelessly while still being transparent and controllable.”

From Siloed AI to Orchestrated Agents

Today, most AI agents operate in silos—stateless, off-chain, and disconnected. Questflow solves this by enabling two forms of orchestration:

Task Orchestration – AI swarms can handle multi-step workflows across popular Web2 tools like Google Workspace, Notion, and Airtable, as well as Web3 applications and protocols.

Token Orchestration – Each AI agent is assigned its own on-chain wallet, making agent-to-agent micropayments and real-time value exchange possible.

This hybrid approach merges the worlds of Web2 and Web3, giving AI agents the ability to function as active participants in the digital economy.

Strong Early Traction and Ecosystem Expansion

Questflow has already built strong momentum. It has been recognized by a16z, Cohere, and MongoDB, selected for Google for Startups, and earned the title of Product of the Day on Product Hunt.

Its growing partner network spans Web2 and Web3, with integrations and collaborations with Google, Coinbase Developer Platform, Circle, Aptos, Near, CoinGecko, and Jambo Phone—all contributing to a broader AI agent ecosystem.

Building the AI Economy Flywheel

Questflow’s on-chain flywheel is designed to grow a scalable AI agent economy through four interconnected steps:

  1. Create – Developers and creators can build and monetize AI swarms using a no-code editor and SDK, each paired with an on-chain wallet for identity and earnings.
  2. Use – End users can deploy these AI swarms to automate workflows autonomously with full control over critical decisions.
  3. Pay – Real-time, transparent micropayments ensure AI agents are compensated instantly and fairly.
  4. Tokenize – Communities can launch and govern AI swarms via tokenization, allowing collective participation and shared ownership.

“Giving every agent a wallet is only the beginning,” said Xu. “The real vision is an AI workforce that can earn, collaborate, and pay other agents automatically, creating a truly self-sustaining ecosystem.”

Scaling the Future of AI-Agent Collaboration

With its new funding, Questflow plans to enhance orchestration capabilities, launch ecosystem incentives, and open the MAOP protocol to partners and developers.

As AI and blockchain technologies converge, Questflow is positioned to bridge the gap between isolated AI systems, allowing anyone to deploy an adaptive, on-chain AI workforce that’s as consistent as software but as flexible as a human team.

By enabling permissionless creation, coordination, and monetization of AI agents, Questflow is setting the stage for a decentralized AI Agent Economy, where intelligent agents act as independent, value-generating economic actors on-chain.

Learn more: https://www.questflow.ai

Contact Email: [email protected]

X: https://x.com/questflow

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