Market Research and Consulting
4 months
US
Our client, David Milward, was with a data governance and management company, where creating Total Addressable Market (TAM) reports for various industries and markets was a routine task. The manual process involved extensive research and analysis, leading to time-consuming report creation. To improve efficiency, David sought a solution for TAM report automation.
Tezeract collaborated with David to develop a cutting-edge LLM-powered market analysis tool. This AI-driven solution automates the creation of TAM reports, significantly reducing manual effort and streamlining the process.
David partnered with Tezeract to develop an AI-powered Excel plugin designed for automating TAM report creation with AI. This innovative plugin simplifies the TAM report automation process by allowing users to input key details such as market industry, year, region, and other relevant information. The tool then automatically generates comprehensive TAM reports, eliminating the need for manual research.
To ensure the solution met their specific needs, we collaborated closely with David’s team to understand their reporting methods and processes. The plugin leverages multi-agent LLMs for business automation, including advanced models like Claude, Gemini, and GPT, as well as web scrapers to gather data from the web. These LLM-powered market analysis tools perform tasks such as trend analysis, forecasting, and other market insights, seamlessly transforming raw data into actionable TAM reports.
This multi-agent LLM case study highlights how integrating sophisticated AI models can revolutionize business reporting and analysis.
Developing an optimized API was essential for integrating the AI plugin with external data sources. We focused on fine-tuning the API to handle detailed inputs such as market industry, year, and region, ensuring efficient and accurate real-time processing for TAM report generation.
Designing an intelligent, optimized scraper required crafting algorithms to extract relevant market data, including industry-specific insights and regional information. This enhancement allowed for precise data collection and better-informed TAM reports.
We prioritized optimizing the extraction of web data to accurately reflect market industry trends and regional specifics. This refinement improved the quality of the data used, ensuring that the AI models provided actionable and insightful TAM reports.
First, we collaborated with the FN-AD team to understand their business and goals, developing a detailed project brief with market research and competitor analysis. We then created a concrete plan, outlining key features like automated brand classification, profile creation, and lead management CRM to validate the MVP assumptions.
We started by designing the key screens to show the client the product’s look. After refining the UX/UI through client feedback. Once these primary screens were finalized, we expanded the design to cover all additional screens and delivered the complete UX/UI for the product.
At this stage, our focus shifts to developing the AI solution for fashion brands by designing the architecture of the AI model and training it.
After the product launch, we collected feedback from end-users to refine and enhance the product. We introduced new iterations and features concurrently to ensure an optimal user experience.
The TAM plugin utilizes intelligent crawling as part of its LLM-powered market analysis tool to automatically collect data from diverse sources. By focusing on industry-specific and regional information, this feature enhances TAM report automation, ensuring comprehensive and accurate data for generating detailed TAM reports.
The plugin employs advanced forecasting techniques powered by multi-agent LLMs for business automation. By analyzing historical market data, it predicts future trends, adding strategic insights to the automating TAM report creation with AI and improving the overall accuracy and usefulness of the reports.
As a hosted Excel plugin, the solution integrates seamlessly with Excel, offering a user-friendly platform for automating TAM report creation with AI. This multi-agent LLM case study demonstrates how the plugin simplifies TAM report generation, allowing users to efficiently input data and receive automated, actionable insights.
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