Modernize fast, reduce integration work, and free up your team to focus on higher-value initiatives with CWAN.
Scale smarter, collaborate better, and stay ahead with technology built for modern investment operations.
Break down silos with automated ingestion, validation, and normalization across the front, middle, and back office — on a single cloud-native investment platform.
Enable secure, client collaboration with Snowflake-powered data sharing and one multi-tenant SaaS architecture powering every team, tool, and view.
Unify public, private, and securitized assets in a single system to monitor exposures, run stress tests, and analyze firmwide risk in real time.
Scale with confidence. Add asset classes, markets, and strategies with zero infrastructure overhead.
Customize models, workflows, and analytics with an open platform that’s extensible by design — no vendor lock-in, no code rewrites, just scalable control.
Connect CWAN to your existing tools and data ecosystem with open APIs, pre-built adapters, and data feeds — no custom plumbing required.
Support complex strategies, risk modeling, and regulatory reporting — all pre-configured in a scalable, cloud-native architecture.
CWAN combines GenAI with a cloud-native investment platform and Snowflake to unlock firmwide productivity, faster insights, and stronger decision support.
John Stecher Chief Technology Officer, Blackstone
Sophie Le Berre Technical and Accounting Director, GGVie
Dirk Manelski Managing Director, Chief Technology Officer, PIMCO
Modernize fast, reduce integration work, and free up your team to focus on higher-value initiatives with CWAN.
InvestOps attendees described a set of problems that will sound familiar to anyone running investment operations today. Validating data across systems that should agree but don’t. Accessing historical records back to inception for transparency requests and audits. Spending hours on manual cleanup before any downstream work can begin.
With the recent marriage of generative AI tools and software development, tasks that required significant manual effort are increasingly automated — enabling teams to shift their focus from repetitive implementation to higher-order design, architecture, and innovation.
Effectively adding AI trading technology to your risk conversations requires more than just a single agent operating as your AI Assistant. An effective AI team is made up of a variety of specialized agents that work together, designed, controlled and orchestrated by their human leader to tackle the multi-step and multi-role activities that are part of real-life trading and portfolio management.