B.O.S.S. Retirement Solutions

Enhancing Retirement Planning Efficiency with Generative AI

From Hours to Minutes with GenAI-Powered Blueprint Builder

The Partnership

B.O.S.S. Retirement Solutions enlisted BlueLabel's expertise to enhance their lead generation process. To attract and engage potential clients, B.O.S.S. introduced the B.O.S.S. Retirement Blueprint™—a concise, one-page document that provides a personalized summary of retirement strategies tailored to each client's unique needs. In order to increase efficiency and adoption of the blueprint process, BlueLabel developed the Blueprint Builder tool. Within eight weeks, we deployed a prototype which can produce Retirement Blueprints in minutes instead of hours.

Services

Business Process Optimization Mapping

AI Product Strategy & Discovery

GenAI Application Development

Data Engineering and Pipeline Automation

Web App Development (FE/BE)

Outcomes
& Value Created

1 ^day/wk

Saves an average of 1 hour per blueprint, allowing advisors to reclaim approximately 8 hours—or a full workday—each week.

70^%

Elevated the retirement blueprint completion rate from 25% to 100% by making it a standard, easily adoptable process for all advisors.

5+^%

By increasing blueprint adoption, and standardizing the quality of reports, the automated blueprints can increase close rates by 5+%

Reduced blueprint preparation time, allowing advisors to efficiently service and support a larger client base in less time.

Improved transparency in the calculations behind each blueprint value, ensuring greater accuracy and enabling advisors to audit the provided information.

Enabled faster value delivery using AI-generated strategies, empowering clients to confidently take the next steps in their retirement planning.

HTML version of the blueprint allows advisors to effortlessly export data into a B.O.S.S.-branded PDF with just a click.

Utilizing AnythingLLM for the initial concept paved the way for offering more tailored strategies, as well as the development of a GenAI advisor copilot.

Objective & Challenges

BlueLabel partnered with B.O.S.S. to overhaul their lead generation process centered around the B.O.S.S. Blueprint. Through in-depth interviews, advisor surveys, and a thorough analysis of the existing blueprint generation process, we identified key opportunities for automation and AI integration. Our objective was to develop the B.O.S.S. Blueprint Builder, a tool that seamlessly extracts data from financial reports and utilizes GenAI to produce customized blueprints for prospective clients. This innovation not only streamlines the workflow for advisors but also enhances client engagement and increases deal closure rates.

Key Challenges

Balancing the variations in advisors' workflows, existing rules for blueprint completion, and the limitations of organizational tools to map an efficient process flow.

Converting PDFs into vectors, extracting data, and performing calculations consistently across diverse document types required a standardized approach.

Developing a lightweight proof of concept to demonstrate that GenAI could effectively generate initial strategies using advisor-like language and recommendation frameworks.

B.O.S.S. BLUEPRINT BUILDER Wireframes

Built to Scale

To ensure the B.O.S.S. Blueprint Builder’s long-term success, we initially used AnythingLLM during the prototype phase to refine prompts and assess how well the LLM could parse client documents. This tool also accelerated development by managing interactions with the LLM and vector database through a simple interface. As we scale the product, we are upgrading AnythingLLM to a custom solution that better handles client data at scale, ensuring seamless integration and continued efficiency in generating personalized retirement strategies.

Tech Stack & Integrations

How We Delivered Value

Our
Approach

GenAI Vision &
Opportunity Analysis

Consumed existing content on the B.O.S.S. retirement advisement process and conducted surveys and interviews with stakeholders and advisors to identify gaps.

Mapped out existing advisor journey to propose AI-driven automation solutions that standardize and simplify the blueprint generation process, encouraging greater advisor adoption and delivering a more consistent client experience, ultimately boosting conversion rates.

Developed hypotheses on how AI could address identified pain points and opportunities.

Developed a comprehensive AI vision for B.O.S.S. Blueprint Builder, including prioritized opportunities and use cases.

GenAI Product Discovery & Requirements

Created a GenAI Product Requirements Document outlining goals, success criteria, and prototype feature requirements, based on high-priority use cases.

Designed key user flows in a Figma prototype to visualize and refine the user experience.

Conducted technical feasibility studies to evaluate the implementation challenges of proposed AI solutions, ensuring that they are practical and align with business objectives.

Created a strategic roadmap for the integration of AI capabilities into the B.O.S.S. Blueprint Builder, prioritizing features that address the most pressing user needs and market demands.

GenAI Prototype Development & Validation

Architected a Retrieval-Augmented Generation (RAG) based solution that leveraged AnythingLLM alongside a Milvus vector database for dynamic referencing of financial report data.

Created and deployed custom prompt chains with dynamic, financial-specific data to deliver relevant and accurate retirement strategies.

Trained a LLM for dynamic analysis of financial documents pertinent to the prospective client.

Developed additional features, including versioning, note-taking, and exporting, to enhance the advisor experience in creating and managing blueprints.

Conducted stakeholder testing to ensure product accuracy, validate hypotheses, and prepare the prototype for internal team use.

“One of our top advisors, who consistently converts at high rates and is a key influencer within our organization, has been testing the B.O.S.S. Blueprint Builder. The feedback from this testing has been very positive, aligning with our goals to create a usable capability that enhances the client journey throughout the entire process."

Stakeholder at B.O.S.S. Retirement Solutions

Key Activities
& Takeaways

BlueLabel tackled the challenge of streamlining the retirement planning process for B.O.S.S. by integrating AI-driven automation into their workflow. We developed the B.O.S.S. Blueprint Builder, a tool that leverages Generative AI to automate the creation of personalized retirement blueprints, extracting data from financial reports and generating strategies tailored to each client. Here’s how we achieved this:

Uncovered Workflow Opportunities

By conducting a detailed mapping of advisor workflows, we identified gaps between the intended customer journey and actual practices. This allowed us to uncover both AI automation and general workflow improvements, such as incorporating note-taking within the blueprint tool to enhance consistency and reduce manual effort.

Flexible Data Extraction & Analysis

Our team analyzed reports from Stonewood Financial, Nitrogen, Retirement Analyzer, and Social Security Analyzer to determine key data for extraction. This data was then used for automated calculations and GenAI prompts, streamlining the creation of personalized retirement strategies.

Real-Time Processing

We deployed a Retrieval-Augmented Generation (RAG) process using Langchain and OpenAI models to deliver real-time AI responses for large financial datasets. This approach ensured that the generated strategies aligned with the criteria and decision-making frameworks used by advisors today.

Scalability and Performance

By containerizing services and optimizing data processing workflows, we ensured that the Blueprint Builder could scale efficiently without sacrificing performance. This approach enabled the system to handle high volumes of financial data and support a growing number of users seamlessly.