Author: momo, ChainCatcher
Recently, the multi-AI agent scheduling platform Questflow announced the completion of a $6.5 million seed round, led by CyberFund (an institution under Lido's co-founder), with participation from top institutions and project parties such as Delphi Labs, Systemic Ventures (supported by Ethereum co-founder Joseph Lubin), Animoca Brands, HashKey Capital, ElizaOS, and receiving ecosystem grants from Aptos, Coinbase, and Virtuals Protocol.
In July last year, Questflow had previously received a $1.5 million angel round investment from Qiji Chuangtang and PAKA.
In addition to gaining investment support from top institutions and project parties, Questflow has recently established strategic partnerships with top Web2 and Web3 platforms including Circle, Coinbase, Google, Near, and CoinGecko.
Why has Questflow gained favor from top institutions and project parties? What problems does its multi-AI agent scheduling platform solve? How is Questflow positioning itself in the AI track amid the wave of AI and blockchain integration?
In the Era of AI Agents, Workflows Will Be Restructured
The rise of AI Agents is reshaping traditional work modes, and collaboration between humans and AI Agents may become the future work norm.
For individual workers, AI Agents will become powerful "digital assistants", handling repetitive and process-based basic work such as schedule management, email filtering, and meeting records. This will release individual workers' productivity, allowing them to focus on more creative and strategic high-level tasks.
AI Agents will also become "digital employees" for enterprises, helping to reduce costs and increase efficiency. Enterprises need to establish an AI Agent pool, deploying specialized Agents for finance, customer service, data analysis, and other areas for employee collaborative scheduling. Employees only need to make requests, and intent-driven automation can mobilize Agents to execute efficiently, with employees only needing to review key content.
However, there are currently no mature enterprise service solutions for the workflow revolution brought by AI Agents.
Although there are AI tools like ChatGPT, DeepSeek, and Midjourney for executing specific tasks, each model has its own user interface, payment structure, and API syntax, resulting in a very fragmented user experience.
Moreover, enterprise needs vary greatly, and existing general AI tools are expected to have difficulty fully adapting to specific business scenarios. For most employees without a technical background, how to schedule and operate multiple AI Agents in the future also presents a pain point.
In the era of human-AI Agent collaboration, how to help enterprises customize AI Agent functions and coordinate multiple AI Agents to handle complex cross-departmental and cross-scenario tasks will face enormous market demand.
A Jiazi Guangnian think tank report predicts that by 2026, 60% of enterprises will deploy AI Agents, and by 2027, 40% of enterprise services will be delivered by AI Agent combinations.
Under this trend, Questflow is committed to building a flexible, composable multi-AI agent scheduling platform that allows AI Agents to collaborate like employees, helping individuals and enterprises adapt to new workflow modes.
(Translation continues in the same manner for the rest of the text)Currently, Questflow's core protocol and products have been recognized by top-tier institutions. While most AI projects are still competing on single-point technologies, Questflow has completed initial practice from technical protocol to business ecosystem by binding with leading projects like Circle and Coinbase. In the future, it is expected to further expand from the Web3 domain to a larger Web2 ecosystem.
Moreover, Questflow's team genetics also provide support for long-term product development and commercial implementation. As the AI Agent network continues to expand, Questflow is expected to become the App Store of the AI era, managing the traffic and economic distribution of AI Agents.
