Micropredictions LLC, a subsidiary of Intech Investments, is pioneering the world’s first open, real-time prediction network. By allowing competing state-of-the-art algorithms to converge on optimized predictions, the platform makes low-cost, high-quality forecasting accessible for organizations of all sizes. However, widespread adoption depends on helping organizations understand how to integrate this novel technology into their daily decision-making and operational processes.

Currently, many potential users lack clarity on how to frame real-world business problems as prediction challenges, deploy live data streams to the Microprediction network, or apply resulting forecasts to drive automated decisions. There is also an untapped opportunity to demonstrate the power of the platform through tangible proof-of-concept applications—such as forecasting electricity usage, cryptocurrency price movements, or other high-frequency data streams that impact strategic and operational decisions.

This project offers students the chance to work at the cutting edge of applied AI and predictive analytics. The team will help Micropredictions expand its ecosystem by exploring real-world business use cases, testing the platform’s APIs, developing turnkey demo applications, and creating best-practice documentation for organizations seeking to use prediction as a core business optimization lever.

Landscape Analysis – Investigate how organizations across industries use prediction and real-time data to improve operations, highlighting successful case studies and gaps Micropredictions could address.

Technical Exploration – Learn to use the Micropredictions API and submit live data streams, while benchmarking performance on example challenges (e.g., electricity usage, cryptocurrency prices).

Use Case Development – Design and validate 2–3 real-time prediction use cases that could provide measurable business value for different types of organizations.

Prototype Applications – Build simple web-based or data-driven demo tools that showcase the practical application of the Microprediction API in solving business problems.

Implementation Framework – Develop best-practice documentation and a playbook outlining how organizations can adopt and operationalize Micropredictions within their workflows.

Launch at least 3 real-time forecasting models using the Micropredictions network by the end of the fall semester.

Achieve a minimum 15% accuracy improvement over baseline heuristics on at least two models.

Deliver a functional demo web app that integrates the prediction API and produces actionable outputs by mid-spring semester.

Conduct 5+ stakeholder interviews with potential business users to validate real-world use cases and adoption potential.

Produce a comprehensive final report and presentation outlining technical performance, business applications, and go-to-market recommendations.