White Papers

Mosaic Data Science’s whitepapers are authored by our AI/ML experts, diving into groundbreaking research, meticulous analysis, and forward-thinking in AI and machine learning. Whether you’re seeking to comprehend the latest trends, demystify intricate technologies, or grasp the far-reaching implications of these innovations, our whitepapers are your gateway to informed decision-making.

Unlocking Smarter AI with GraphRAG: Better Answers with Knowledge Graph-Enhanced Retrieval

In an era where businesses need precise and actionable information, GraphRAG offers a significant leap forward in information retrieval. Unlike traditional retrieval-augmented generation (RAG), which can struggle to connect related but dispersed data, GraphRAG uses knowledge graphs to deliver more contextual, relevant, and actionable responses. This technology enables organizations to unlock deeper insights from their data, improving operational efficiency and decision-making without sacrificing precision.

By Melissa Rodriguez, ago
Top LLM Business Applications

Top LLM Applications for Modern Business

AI and LLMs are not just a technological leap; they’re a strategic imperative. By embracing this evolution, businesses gain a distinct advantage—staying ahead of the competition, enhancing stakeholder experiences, and optimizing both time and costs. In this white paper, we explore our top LLM business applications.

By Melissa Rodriguez, ago

Unlocking Business Opportunities with Generative AI

While Generative AI is still in its early stages, its potential is immense. Businesses that can harness this technology effectively will be well-positioned for success in the years to come. Discover how your firm can tap into this transformative force and achieve its business goals by leveraging Generative AI for cost savings, revenue generation, competitive differentiation, employee empowerment, and enhanced customer engagement.

By Melissa Rodriguez, ago

Building a Neural Search Engine with Mosaic

Mosaic dives into our latest solution framework, The Neural Search Engine. Our tool can be tuned to ingest any set of documents and return relevant information in seconds. We leverage the retriever/reader architecture where for a given question, related context is obtained from the enterprise-specific knowledge base and fed to deep learning models.

By Sel Gerosa, ago
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