Blogs and Insights

Explore our regularly updated blog for the latest articles on industry trends, data management tips, and company updates.

Taming the LLM: How Domain Specific Languages (DSLs) Reduce Hallucinations and Boost AI Reliability

One of the biggest challenges in using Large Language Models (LLMs) in real-world applications is keeping them accurate, efficient, and predictable—especially when they’re interfacing with structured systems and business processes.At Dataception, we’ve fo...

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Case Studies

Read detailed success stories showcasing how Dataception has transformed businesses with our tailored AI and data solutions.

Data Mesh for Retailer and Manufacturer

Implemented a self-service Data Mesh platform, enabling business D&A teams to build and deploy reports, ML models, and data-driven services, reducing duplication and enhancing capabilities.

Data Mesh fo Operations in Global Bank

Developed a distributed data mesh platform providing real-time reporting on 2000+ metrics across 30 departments, handling 50TB of data with 120 million daily updates.

Data Layer for Commodities House

Created a real-time data architecture for commodities trading, including an AI model platform, feature store, and data architecture, with a focus on using best-of-breed tools.

Data Mesh Analytics Platform for Manufacturer

Deployed a mesh-type architecture integrating cloud and machine shop data, enabling seamless AI model deployment and cross-departmental data product utilization.

Data Fabric for Investment Management Company

Developed a unified data access layer using REST and event services, with a centralized GraphQL layer for orchestration and deployment on Azure native services.

Data Foundation for Entertainment Corporation

Implemented a mesh-type architecture for marketing, integrating various channels for a single customer view, enabling real-time access to virtual reality experiences.

Deep Learning for Music Information Retrieval

Developed advanced matching algorithms for music collaboration, including feature-to-taxonomy mapping and comprehensive data ingestion interfaces for enhanced music information retrieval.

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