David Hyman launches monō ai to scale enterprise AI

David Hyman has launched monō ai, which has begun trading with enterprise clients across seven sectors.

The business is designed to help established organisations apply artificial intelligence in day-to-day operations rather than confine it to trial projects. At launch, its clients span legal, financial services, fintech, creative and strategy, hospitality technology, deep-tech investment, and multi-brand consumer operations.

Hyman, a co-founder of Lendi Group, is leading the venture as chief executive officer. Technology partnerships with major cloud providers and enterprise partners are already in place.

monō has not taken venture capital or institutional backing. It is funded by Hyman, fellow Lendi Group co-founder Sebastian Watkins, and Archistar chairman Prabhat Sethi.

The founding team also includes Daniel Folb, formerly of Deloitte; Shoumo Thakurta, formerly of CBA; Olivia Braddick, formerly of EY; and Emilio Mattiuzzo, formerly of Valiant. Broader staffing has been drawn from companies including Salesforce, Accenture, Telstra, and American Express.

Market Pressure

monō is entering a market where many businesses have adopted AI tools but struggled to move from experimentation to broad deployment. Research it cited found that 95% of enterprise AI pilots fail to produce measurable business impact. While 88% of organisations report using AI, only one-third have scaled beyond pilots.

That backdrop has sharpened focus on the gap between established businesses and younger AI-focused firms. monō pointed to Cursor, ElevenLabs, and Lovable as examples of companies reaching large revenue numbers with relatively small workforces.

"We built monō to help organisations move beyond AI pilots and apply AI in everyday operations. The team brings experience from large, regulated businesses, which shapes how we design and deploy the platform. The opportunity is substantial, and our priority is helping organisations capture it in a way that works at scale," said David Hyman, chief executive officer of monō ai.

The advisory board includes former Atlassian executive Dominic Price as a founding advisory board member. He said the company was tackling a broad challenge in helping organisations adopt AI in a structured way.

"What excites me about monō is the scale of the opportunity and the intent behind it. This is about bringing together advanced technology and human systems in a way that actually delivers impact. If done well, it gives organisations a genuine opportunity to lead in how AI is adopted responsibly and at scale - and for Australia, that's a real chance to set the standard globally," said Price.

Lendi Experience

Hyman said the idea for monō was shaped by his work at Lendi after stepping back from day-to-day chief executive responsibilities. He focused on the mortgage group's AI-led changes across its engineering and operations teams.

That work reduced development cycles from weeks to days, improved customer conversion, and lifted operating efficiency across a workforce of 2,500 managing an AUD $105 billion loan book, according to the company.

"The gap between experimenting with AI and actually deploying it at scale is one of the biggest unresolved problems in business today. A new generation of AI-native companies is operating with fundamentally different economics, and established organisations are starting to feel that pressure across every sector. monō ai is built to help close that gap, and it's a reality every board needs to be confronting now," said Hyman.

Platform Model

The product is described as a platform that sits within an organisation's operating environment. Work begins with a fixed-scope proof-of-value deployment lasting between two and six weeks and focused on a single process, before expanding into broader workflows if the initial project delivers results.

Client data remains within each customer's cloud environment, with access controls in place, according to monō. The platform uses an inference-only model, meaning external AI providers do not train on or retain client data.

Hyman said monō was formed after he saw how operational change could follow when AI tools were embedded into the way teams work.

"I spent time working alongside the engineers and operations teams and rebuilding workflows with them. That experience showed what's possible when an organisation commits to using AI as part of how it actually operates, not just as a concept. It also highlighted how few companies have taken that step, which ultimately led to the creation of monō," Hyman said.