Case Study: IGT Solutions accelerates Gen AI time to market with MongoDB Atlas

IGT Solutions boosts productivity 20% and cuts time to market 25% with MongoDB

IGT Solutions, a future-facing IT services provider, needed to modernize its data platform to support rising demand for its generative AI offerings. The company's legacy systems, built on relational and separate vector databases, led to slow response times, high operational costs, and labor-intensive workflows. To build a competitive advantage, IGT required a solution from a vendor like MongoDB that could store large data volumes, simplify architecture, and handle both operational and vector data to support large language models across multiple clouds.

By implementing MongoDB Atlas and MongoDB Atlas Vector Search, IGT Solutions gained a unified platform for operational and vector data. This solution from MongoDB provided the flexibility, scalability, and multi-cloud support needed. The results included a 20% rise in productivity, a 25% improvement in time to market, and specific AI applications delivering drastic efficiency gains, such as a 90% reduction in finance query response times for one client. MongoDB enabled IGT to scale its generative AI platform globally for a diverse user base.

IGT Solutions