Bothra Solutions partners with organizations at different stages—from pre-product startups to established enterprises. Below are examples of the types of challenges we solve.
A financial services company processed thousands of contracts monthly using manual review—slow, error-prone, and expensive.
We built a document analysis pipeline using fine-tuned language models to extract key terms, flag risks, and generate summaries. The system integrated with their existing case management platform and included human review workflows for high-stakes decisions.
A SaaS company's support team couldn't scale with user growth. Response times were increasing and satisfaction scores declining.
We developed an AI agent that handled tier-1 support queries, accessed documentation, searched past tickets, and escalated complex issues. We integrated it with their existing CRM and trained it on company-specific knowledge.
An enterprise innovation team spent weeks gathering competitive intelligence, synthesizing reports, and tracking industry trends—manual, repetitive, and inconsistent.
We built an AI research system that monitored sources, extracted insights, generated summaries, and delivered weekly reports. The system learned from user feedback and prioritized relevant information.
An e-commerce platform had product recommendations based on simple rules—resulting in low click-through rates and missed revenue opportunities.
We developed a recommendation system using collaborative filtering and deep learning, incorporating browsing behavior, purchase history, and seasonal trends. We A/B tested approaches and optimized for conversion.
A healthcare startup needed to process unstructured clinical data from multiple formats while maintaining compliance and data quality.
We built an ETL pipeline with AI-powered data extraction, entity recognition, and quality validation. We implemented HIPAA-compliant infrastructure and created audit trails for all transformations.
A logistics company manually planned delivery routes, resulting in inefficient fuel usage and missed time windows.
We developed an AI system that optimized routing based on traffic patterns, delivery constraints, and historical performance. We integrated real-time updates and driver feedback mechanisms.