ADVISORY_GO HOME OR GO GREEN

DASHBOARD

Inspiration

ADVISORY was inspired by the growthing demand for financial and insurance advisory services. As clients face more complex life situations such as family protectionInspiration

Advisory was inspired by the growing demand for financial and insurance advisory services. As clients face more complex life situations such as family protection, retirement planning, estate planning, business ownership, and wealth transfer, advisors are expected to provide more personalized and timely support.

However, we noticed that financial advisors often spend a lot of time on repetitive administrative tasks, meeting preparation, follow-up messages, learning materials, specialist referrals, and compliance records. They also need strong long-term memory because every client has different life stages, concerns, preferences, and follow-up needs.

We wanted to explore how AI can reduce this workload and support the daily operations of financial advisors without replacing the human advisor. This inspired us to build Advisory as an advisor-assistive productivity platform.

What it does

Advisory helps financial and insurance advisors prepare smarter and work more efficiently.

The platform provides:

A dashboard for priority clients, meetings, suggested actions, and audit activity.
A client memory page for viewing client life stages, needs, and preferences.
A meeting brief generator that helps advisors prepare agendas, questions, and planning gaps.
A follow-up assistant that drafts WhatsApp, email, and call scripts with compliance guardrails.
A learning recommendation feature that suggests relevant learning modules based on client needs.
A partner ecosystem feature that suggests specialist support such as tax, estate, or business succession experts.
An approval workflow where the advisor must review and approve AI-assisted actions.
An audit trail that records approvals and AI-assisted activity.
A manager view that gives agency leaders visibility into advisor activity, learning progress, referrals, and audit logs.

Advisory is not a robo-advisor. It does not give final financial advice or direct product recommendations. Instead, it helps advisors prepare, communicate, learn, refer, and maintain an audit trail.

How we built it

We built Advisory as a full-stack web application.

The frontend includes the advisor dashboard, client pages, client profile workflow, learning library, partner ecosystem, and manager view. We focused on making the interface clear, professional, and suitable for financial advisory teams.

The backend was built with Python and FastAPI. It provides API routes for client data, meeting brief generation, follow-up drafts, partner suggestions, and advisor approval actions.

The AI logic is organized into Python agent functions. These agents help summarize client context, generate meeting preparation briefs, draft human-touch follow-up messages, recommend learning modules, suggest specialist partners, and check for risky direct-advice wording.

Challenges we ran into

One of the biggest challenges was deciding the right product direction. At first, we considered many possible features, including note-taking, proposal generation, partner matching, learning content, automation workflows, and form autofill. Because of the limited hackathon time, we had to control the scope and focus on the features that best show advisor productivity.

Another challenge was positioning the AI correctly. In financial services, AI should not directly recommend products or replace the advisor’s judgement. We had to design the system carefully so that AI outputs are presented as drafts, preparation support, or suggestions, with advisor approval required.

Accomplishments that we're proud of

We are proud that Advisory became more than a simple chatbot. It is a workflow-focused platform that connects client memory, meeting preparation, follow-up communication, learning recommendations, partner support, approval records, and audit visibility.

We are also proud of the human-in-the-loop design. AI-assisted action is positioned as something the advisor reviews and approves, rather than something the AI executes automatically.

Another accomplishment is that we built a stable demo flow under limited time. The platform can demonstrate how an advisor moves from client context to meeting preparation, follow-up drafting, learning, partner suggestion, approval, and audit tracking.

What we learned

We learned that AI in financial advisory is not only about generating answers. It is about trust, workflow, compliance, and human responsibility.

The most important lesson we learned is that AI should work together with human advisors. AI can help reduce repetitive work, organize information, and prepare useful drafts, but the advisor should still decide what is appropriate for the client.

We also learned that a strong hackathon product needs a clear scope. Instead of trying to build every possible feature, we focused on showing a complete advisor workflow that is practical, safe, and easy to understand.

What's next for ADVISORY

Next, we would like to improve Advisory with deeper integrations and more realistic workflow automation.

Future improvements include:

Real calendar integration for approved follow-up tasks.
CRM integration for client records.
Speech-to-text or note import from existing meeting tools.
More advanced compliance checking.
Secure role-based access for advisors and managers.
More personalized learning recommendations.
More detailed partner referral tracking.

Our long-term vision is to make Advisory a secure and scalable productivity layer for financial and insurance advisory teams, helping advisors serve clients more personally while keeping human judgement at the center.