Engineering trustworthy AI: Grounding generative models in enterprise truth

A technical guide for leaders: Partner with Slalom and Google Cloud to build precise, verifiable, and contextually relevant GenAI applications.

GenAI holds great potential, but technical teams often face hurdles like model errors, knowledge gaps, and ensuring outputs are aligned with proprietary enterprise data. True enterprise AI requires reliable, verifiable answers.

Slalom and Google Cloud grasp the technical challenges of deploying trustworthy GenAI. This eBook, “Grounding generative AI in enterprise truth,” provides the technical acumen needed to turn potential into effective and accurate business solutions.

This guide outlines strategies to build AI that utilizes your organization’s data for unmatched reliability.

What you’ll learn:

• RAG vs. CAG vs. agentic approaches: Discover how RAG enhances foundation models by integrating external, dynamic data before generation, reducing inaccuracies without retraining.
• Data integration & vector search: Learn about vector embeddings and how to incorporate your enterprise data, including databases like Bigtable and BigQuery, for highly relevant contextual results.
• Overcoming model limitations: Technical strategies to tackle challenges like errors, knowledge gaps, and the demand for domain-specific precision.
• Building explainable & compliant AI: Understand how grounded models naturally support traceability with source citations, vital for trust and compliance.

Slalom partners with your tech teams to anchor foundation models, ensuring better accuracy, context, and relevance for superior outcomes. As a leading global consulting firm and trusted Google Cloud partner, we enable your technical teams to harness Google Cloud’s advanced capabilities, ensuring your GenAI yields truthful insights.