Enterprise Knowledge Search
MNP needed a better way to support client-facing generative AI advisory and contextual financial analysis because traditional analytics platforms could not support the LLM-powered services and data preparation needed for faster client advisory deployments.
Reported impact
MNP improved client-facing generative AI advisory and contextual financial analysis with measurable results including <6 weeks, while giving teams a faster path from governed data to production decisions.
MNP uses Databricks Data + AI Platform to support client-facing generative AI advisory and contextual financial analysis. The implementation replaced a legacy state where traditional analytics platforms could not support the LLM-powered services and data preparation needed for faster client advisory deployments. Client data and financial services knowledge move through production data pipelines and land in shared lakehouse datasets, giving teams one trusted data foundation. Unity Catalog governs access, lineage, and compliance across sensitive datasets. Model Serving, Agent Bricks, and AI Search operationalize models, agents, and analytics that deliver GenAI advisory insights and client decision support. MNP improved client-facing generative AI advisory and contextual financial analysis with measurable results including <6 weeks, while giving teams a faster path from governed data to production decisions.
Client data and financial services knowledge land on a shared platform, pipeline services clean and standardize them, governance controls enforce trusted access, and AI, model-serving, and analytics services deliver GenAI advisory insights and client decision support.
The GenAI Advisory Program has been invaluable to our early successes with Databricks,
The impact of Databricks technology enabled us to deliver enhanced services to our clients, demonstrating the powerful relationship between advanced AI and effective data management.
The support we’ve received has vastly accelerated our path to deployment and adoption.
To strengthen their market leadership in professional services, MNP chose to adopt a lakehouse architecture that could support the integration of large language models (LLMs) and provide contextualized insights to their
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