AI Development Case Studies

WhatsApp Chatbot

Squareboat’s WhatsApp Chatbot was developed to handle a growing volume of incoming messages related to hiring and sales. The chatbot operates through a structured decision flow, first identifying the nature of the query — whether it concerns careers or sales and then dynamically adjusting the conversation path. The chatbot automates the first level of interaction, significantly reducing the need for manual intervention. This improves the user experience by offering fast and reliable communication on a familiar platform. This is just one example of how chatbots are revolutionizing market research and operational automation across industries.

Applicant Tracking System

To modernize and streamline the recruitment process, we built a comprehensive web-based Applicant Tracking System (ATS). Solving the problems of inefficiencies of traditional spreadsheet-based tracking and creating a centralized system for all hiring activities. The application brings together the various pieces of the hiring journey, candidate progress, team communication, and approval cycles into a single intuitive interface. It provides a unified workspace where all roles involved in hiring can access the information they need without switching between tools or chasing updates. This improves both the internal hiring workflow and the overall experience for interviewers.

My Sustainability Score ESG Platform

My Sustainability Score is built to deliver ESG reports that stand up to scrutiny. From initial data ingestion, where we pull in gold-standard documents, internal policies, and online disclosures, to the construction of a custom ESG knowledge base using Neo4j, we ensure no detail is missed. We structured the system by industry, then defined relevant indicators and mapped them to a dynamic questionnaire. Starting with AI integration services, we implemented a pipeline that ingests company documents, scrapes ESG-related data from public sources, and processes everything through an intelligent backend.Drawing from advancements in LLM-powered assistants, the tool transforms this data into structural ESG insights. It then evaluates each question, highlights strengths, detects areas for improvement, and calculates an indicator-wise and overall ESG score. The final report breaks down ESG performance by category, bringing together scores, strengths, gaps, and improvements in an organized structure.