Quantifiable results delivered through strategic Generative AI implementation.
The Challenge: A major enterprise client faced bottlenecks in their release cycle due to manual testing processes. Regression testing was labor-intensive, error-prone, and coverage was strictly limited by human capital.
The Solution: OneTPM deployed a custom Generative AI framework to modernize the QA lifecycle. We analyzed existing manual workflows to identify high-friction points. Our solution utilized an intent-based testing agent that allows non-technical stakeholders to execute and schedule custom tests using Natural Language.
The Challenge: High-priority data was siloed in complex warehouses. Business stakeholders were entirely dependent on data engineers for basic SQL queries, creating a bottleneck that slowed decision-making.
The Solution: We architected a GenAI Semantic Layer that indexes the client's Data Warehouse metadata. We built a conversational assistant capable of understanding plain English questions (e.g., "Show me Q3 churn rates by region") and retrieving accurate, governed insights. This successfully moved the client toward an "AI-First" data culture.
The Challenge: The client's support and engineering teams struggled with ticket misallocation. New team members lacked the institutional knowledge to route issues correctly, leading to high "ping-pong" rates and delayed resolutions.
The Solution: OneTPM integrated a predictive GenAI module within the client's existing project management system. The model automatically analyzes issue from various monitors, creates ticket with all required context and details, assigns priority levels, and routes the issue to the specific sub-team best equipped to solve it instantly.