NYSE Enterprise AI Innovation Sprint
72-hour enterprise AI sprint with the New York Stock Exchange
Ten Fortune 500 teams, 100% prototype delivery, and a repeatable model for AI adoption at scale.
Case study
Overview
With the NYSE, NativelyAI ran a structured 72-hour sprint so large enterprises could prototype and deploy AI-native solutions quickly — spanning finance, supply chain, customer intelligence, operations, and analytics.
10
Fortune 500 companies
72h
Sprint length
100%
Teams delivering prototypes
NYSE CEO, CTO, and executives sponsored participation. NativelyAI provided strategy, enterprise AI lab partners, and an AI-native build platform.
Case study
Highlights
Every team shipped a working AI-native prototype in 72 hours
Solutions included predictive models, workflow automation, and cross-system integrations
Prototypes moved into live enterprise testing for rapid validation
Case study
Top three innovations
1st — Team Astronomer · Project Zephyr
AI agent for Apache Airflow that detects and addresses failures — API, agent, and UI with ML-backed error resolution (automatic, proposed, or informational).
2nd — Team Kibernum · RAGenda
Meeting companion using Cohere connectors — agendas, live chat and sentiment, and post-meeting reports tied to company resources.
3rd — Team DXC Technology · Stock-Xpert
Conversational app for NYSE-listed companies: trends, news, insider trades, and ESG context.
Case study
Partners
Strategic support from LabLab, LangChain, and Weaviate — workshops, mentorship, and technical guidance.
The sprint validated a repeatable way for Fortune 500 companies to compress AI adoption cycles through structured collaboration and rapid deployment.