AI Product Manager and Business Analyst Platform

The platform is designed to provide business users with the most accurate predictive analysis of sales, cost-effectiveness of product functionality, user behavior by gathering the original company’s uploaded data using artificial intelligence and machine learning algorithms.

Project Overview

Year	2025
Industry
Duration	1.5 year
Services	Backend development Front end development Product design Project management QA

Technology Stack Used

Django

React

Angular.js

Challenge

Our client — a medium-sized business — struggled to optimize their product line and lacked the resources to hire a skilled product manager or business analyst. This became the foundation for building an AI-powered tool that would solve this same problem for other SMBs and startups, offering affordable, automated product insights and UX analysis.

• Designing AI systems for UX/CJM analysis, conversion forecasting, and growth recommendations. • Ensuring data security via isolated CRMs for each client. • Processing highly varied and unstructured datasets (B2B, B2C, or hybrid). • Balancing prediction accuracy with inconsistent input data across industries. • Developing a preprocessing microservice to clean, validate, and standardize client datasets. • Supporting product ROI analysis, behavior mapping, and synthetic data generation. • Creating separate modules: Virtual BA Assistant, PM Assistant, and Start-Up ROI Evaluator.

Solution

Results for the client: The solution enabled the client to optimize their own growth path — and to productize that capability for others. It’s now a full SaaS platform with modular, AI-driven assistants tailored to different business sizes.

• Virtual BA Assistant analyzes CRM data, maps customer drop-offs, and forecasts lead conversions. • Virtual PM Assistant evaluates new product ideas or features, predicts ROI, and suggests improvements. • Start-Up ROI Evaluator forecasts early-stage product success using synthetic data. • Microservice architecture handles data cleaning and normalization across client CRMs. • Each user gets a secure, isolated CRM instance with smart AI integrations. • Business-specific value delivery: from early-stage validation to mid-size optimization.