Elysian Softech announced Mastermind at the AI Agent Conference 2026 in New York on May 4, a platform that generates complete AI agent infrastructure from natural language descriptions of business processes. A medical clinic, real estate chain, or hotel describes its workflows in plain English, and Mastermind builds the agents, data pipelines, testing frameworks, and system integrations without code, according to the company’s announcement.
The Israeli startup is raising $15 million to accelerate Mastermind’s development and expand deployment in the U.S. market.
What Mastermind Actually Does
The platform takes a text description of a business need and produces a multi-agent architecture: individual agents, defined workflows, connections to existing systems, and a complete infrastructure layer. It is designed to work alongside Elysian Softech’s existing Plexa omnichannel product, currently used by hundreds of customers.
“What an entire development team would do in three months, Mastermind achieves based solely on a description that the client writes in words,” Tomer Paz, CEO and CTO of Elysian Softech, said in the announcement. “It’s not just another AI tool, it’s an infrastructure that replaces an entire R&D department for custom AI applications that aligned with regulatory, security, and visibility requirements.”
The company was co-founded by Paz and Yuri Paikin.
The No-Code Agent Market
Mastermind targets the mid-market segment that cannot afford custom development teams. Until now, building a custom AI agent system required developers, product managers, QA, and integration teams, with costs often reaching hundreds of thousands of dollars and timelines stretching to months.
The announcement arrives as the enterprise AI agent market consolidates around two tiers: large-scale deployment ventures (OpenAI’s $4B Deployment Company, Anthropic’s Blackstone partnership) serving Fortune 500 companies, and no-code platforms targeting the long tail of businesses that want agent automation without engineering headcount. Mastermind positions itself in the second tier, betting that prompt-to-infrastructure generation can compress what was previously a multi-team, multi-month project into hours.