The future of AI in capital markets is purpose-built agent systems that cater to user-specific requirements and use cases, built by in-house tech teams or the domain experts (analysts) themselves.

While the space is saturated with AI analyst co-pilots and assistants, a closer look reveals a a critical gap between expectations and reality: retention remains low, churn rates are high, and analysts consistently report limited tangible value.

At its core, this issue stems from AI co-pilots being overly generalized and poorly integrated into the bespoke workflows of individual analysts and teams. These point solutions often fail to seamlessly plug into existing systems, ultimately devolving into a common denominator - the chatbot.

As an executive at a large asset manager told us:

"Every AI analyst app caters to general use cases. If I could onboard 20 vendors, they could maybe cover ours. I can't do that, so we are investing in building internally."

This quote captures the feeling of technologically capable financial institutions. 

Rather than attempting to retrofit generalized AI tools into specialized workflows, these firms are increasingly prioritizing the development of custom solutions that accurately reflect their operational requirements.

Quantly is precisely aligned with this strategic shift. We’re constructing the essential infrastructure to empower financial institutions to build and deploy their own hyper-personalized agent workflows. Our goal isn’t to replace internal GenAI initiatives or compete with them; instead, our mission is to accelerate, enhance, and reliably support these internal projects, ensuring they meet the highest industry standards.

We provide all the core requirements and capabilities needed to ensure explainability, accuracy, and overall quality of output that meets analyst standards and builds trust. 

Quantly v2

To achieve this, we’ve completely reimagined Quantly’s underlying architecture. Our Financial Analysis Operators (FAOs) - modular, domain-specific micro-agents - are dynamically orchestrated to produce analyst-grade, fully explainable outputs. This modularity delivers unmatched flexibility, enabling precise customization to meet exact workflow specifications, something generic LLM co-pilots simply can’t replicate.

Today, Quantly already serves as the foundational infrastructure powering GenAI workflows for several prominent clients. Technical teams are leveraging Quantly’s API to build tailored solutions, and soon, analysts will have the same capability through our no-code interface.

Our updated website clearly communicates this evolution, and we’re excited to announce the forthcoming release of Quantly v2, featuring our new no-code UI, designed to empower analysts to independently create powerful, personalized AI workflows.