Daisy AI

Daisy AI builds an AI-based decision layer for food processors, with an initial focus on dairy and agri-food. The platform ingests scattered operational and market data — spot prices, customer orders, weather feeds, seasonal patterns and customer ERP records — and applies machine learning models that connect supply, demand and margin variables to produce recommendations on what to produce, when, and in what volume, with the associated margin impact. A co-founder interview describes the system pulling in over 30 live data points, ranging from milk protein levels to weather patterns, to forecast raw material intake with greater precision than the static historical averages processors commonly rely on.

The product is organised around four functional areas: procurement (anticipating incoming supply volumes and identifying purchasing gaps), production planning (cross-referencing forecasts, margins and inventory into adaptive weekly or monthly plans), S&OP and IBP preparation (compiling and structuring data breakdowns for planning cycles), and demand planning (predicting sales at SKU and account level). One funding write-up states the machine learning models achieve over 95% accuracy in milk supply forecasts and generate product allocation recommendations covering what to produce, where and when, addressing supply forecast errors of up to 10% that lead to wasted capacity, missed demand and lost revenue.

The company positions its origins on a fourth-generation Irish dairy farm and states this shapes both its team and its product focus; it advertises open positions and markets itself as building for the agri-food industry specifically.

Founding story

Public sources trace the company's origins to a fourth-generation Irish dairy farm, which the company says shapes its team and product focus. A blog post dated March 2026 by co-founder Andrew Moore is described as covering a broken collarbone, a Warren Buffett book, and the view that the problems worth solving are ones that require standing in a milking parlor to understand. Co-founder Chirag Joshi began the venture after graduating from Dublin City University and works on it full time, leading the technical side.

Business model

Daisy sells a software decision layer to food processors, integrating with customer ERP systems and external data feeds to deliver forecasts, production plans and S&OP/IBP preparation. Implementation is described as a structured onboarding sequence: data connection and model training on day one, model testing and gap-filling by day seven, and automated production scheduling with a tailored dashboard by day fourteen, with human planners retaining final decision authority. The sources do not state pricing or contract structure.

Not specified in the available sources beyond the sale of a software platform to food processors.

Traction

Reported traction includes pilots with industry players, a $250,000 funding round reported in August 2025, and a published case study with Kerry Dairy Ireland citing 10x faster forecasting and up to a 60% reduction in annual forecasting margin of error. A company profile lists 2-10 employees and total funding of €250,000, with Entrepreneurs First (Bridge programme) named among investors.

Latest developments

A $250,000 funding round was reported in August 2025, with proceeds earmarked for product development, refinement of the machine learning models, expansion of the decision engine's capabilities and increased operational capacity. The company website carries a customer story dated April 2026 describing results at Kerry Dairy Ireland and a founder blog post dated March 2026, and lists open roles.