At the centre of the launch is a new agentic AI operating environment inside Nasdaq Calypso, the company's capital-markets platform used by financial institutions for front-to-back trading, risk management and collateral workflows.
The environment provides a contained, governed space where institutions can run, connect and scale AI agents.
An Orchestration Layer for Financial AI Agents
The environment acts as an orchestration layer: clients can access Nasdaq Calypso's own agents and connect their proprietary AI infrastructure through an integrated layer built on the Model Context Protocol (MCP), the emerging industry standard for linking AI agents to software.
The agents operate on the platform's system-of-record data — trading, risk and collateral records — and can be extended with enterprise, market and reference data sources. Nasdaq is also introducing a natural language assistant designed to automate analysis of that system-of-record data.
Guardrails for Regulated Markets
Built for regulated finance, the environment applies operational boundaries, live oversight and strict sandboxing, with no external data retention. Agents operate solely within an institution's perimeter and policies, and clients retain full control of their data.
The cloud environment is built on Amazon Bedrock, supplying the scalable services and governance controls required to run agentic AI in regulated environments. On-premises clients can connect to the same agents.
Chasing the Post-Trade Bottleneck
“For institutions to adopt AI agents at scale, they need a trusted, governed infrastructure inside the capital market platforms they already run, a place to connect agents from many different sources to real workflows, data, and controls,” said Magnus Haglind, head of Capital Markets Technology at Nasdaq.
“By integrating agentic capabilities and serving as the orchestration layer, we are evolving Nasdaq Calypso from a system of record into an intelligent platform that automates activity at every stage of the trade lifecycle.”
The timing reflects pressure inside the industry. A recent Nasdaq and Acuiti survey found almost half of respondents flagged manual intervention in post-trade operations as a challenge, while 56 percent said they risk losing ground to competitors if they do not integrate AI or machine learning into clearing operations.
Nasdaq says the agents can enhance risk controls, reduce settlement failures and transform operational data into automated actions — and plans to roll out a suite of governed agentic workers targeting operational friction from manual processes across capital-market workflows.
By Hamza Faisal
