Helps customers implement a production-ready "intelligent retrieval and discovery" agent across knowledge assets that helps teams find relevant content, case studies, or answers faster through AI-powered search.

• Example Outcomes
• Extract value from your unstructured data by allowing rapid search, retrieval, and summarization across your documentation.
• Democratize access to data by allowing non-technical users to focus on their data insights.
• Develop best practices on data ingestion for Search, tuning, and evaluation. All while enabling your resources.

Helps customers implement a production-ready "talk to your data" agent for structured data, to drive adoption of AI-assisted analysis.

• Example Outcomes
• Driving operational efficiencies and reducing the number of ad hoc data and dashboard/reporting requests, freeing up capacity for higher value add activities.
• Accelerates adoption of GenAI with best practices and guidance on latest product capabilities.
• Democratize access to data by allowing non-technical users to focus on their data insights.

A ready-to-run conversational AI application that guides users to relevant knowledge, surfaces insights from multiple content sources, and applies business context and reasoning to deliver clear, actionable answers across structured and unstructured data.

• Example Outcomes
• Faster access to answers by unifying search, retrieval, and reasoning across all knowledge sources
• Improved decision-making through AI-generated insights enriched with business context and data
• Greater knowledge reuse and consistency across teams by centralizing how information is discovered
• Higher productivity as both technical and non-technical users get immediate, accurate responses

A team of experienced migration experts to help guide and enable customer teams during the initial weeks of a DIY migration to Snowflake through key support activities.

• Example Outcomes
• Accelerate migration by enabling internal team with Snowflake experts and accelerators
• Enable and teach customer teams on migration process and accelerators
• Identify potential risks early in the project
• Review the migration plan for potential issues and recommend approach
• Identify efficiencies that could be leveraged or modernization benefits not being realized

Production Pilot for a set of business users or other consumption methods to move live reporting from the legacy system to Snowflake.

• Example Outcomes
• Potential to address other current issues such as data security / privacy early in the migration
• Identify potential data differences due to data types, rounding, space issues, etc.
• Implement necessary change management early based upon validation results

Series of workshops designed to provide an estimate of effort, high-level timeline, and set of recommendations for migrating a single data warehouse platform entirely, or targeted data workloads to Snowflake; with a review of opportunities to leverage automation for database code conversion, data migration, and data validation.

• Example Outcomes
• Clarify scope and alignment across stakeholders
• Reduce architectural ambiguity
• Understand effort and resource requirements
• Minimize migration risks and unknowns
• Identify migration accelerator opportunities

Framework that simplifies AI Data Cloud transformations across organizations, processes, and platforms. Powered by proven toolkits, accelerators, and governance models, it enables customers to design and execute with speed, confidence, and measurable impact.

• Example Outcomes
• A standardized, repeatable approach for delivering AI Data Cloud transformations across teams and platforms
• Faster execution through proven toolkits, accelerators, and governance models
• Greater cross-functional alignment around processes, roles, and transformation objectives
• Clear measurement frameworks that demonstrate impact, value realization, and progress over time

Series of interactive workshops with Snowflake business, industry, technical experts to provide your team direction, recommendations and a plan of action to map out the “HOW”, tie use cases to go-lives and have a plan for healthy adoption.

• Example Outcomes
• Clear alignment on target business outcomes, value propositions, and strategic AI/ML priorities
• A well-defined and shared understanding of the current state and desired future state
• A comprehensive plan detailing stakeholder roles, prioritized use cases, roadmap themes, and quick wins to jump-start execution

Strategic engagement to design and implement a FinOps framework for the Snowflake AI Data Cloud. This service establishes the cultural practices and technical solutions required for continuous cost governance, optimization, and financial accountability across an organization.

• Example Outcomes
• Accelerate FinOps maturity by shifting to a proactive, sustainable, and collaborative practices that deliver faster value
• Gain stronger financial control with predictable cloud spending, clearer visibility, and accurate forecasting
• Unlock efficiency at scale by applying repeatable governance and optimization that reduces waste and frees resources for innovation

A focused two-week engagement that kickstarts your first use case on Snowflake. By combining hands-on implementation with expert guidance, it accelerates adoption, builds confidence across your teams, and delivers a clear roadmap to expand into future use cases with speed and certainty.

• Example Outcomes
• A fully functioning initial use case deployed on Snowflake
• Accelerated team readiness through hands-on learning and expert coaching
• A clear, actionable roadmap to expand into additional high-value use cases

Holistic engagement helping customers identify and address security gaps against a Snowflake-aligned baseline. Through interviews, environment reviews, and collaborative sessions, we deliver detailed findings and actionable recommendations to strengthen security and reduce risk. As part of the engagement, customers also participate in experiential learning sessions where we jointly action 1–2 key recommendations—ensuring both immediate impact and practical enablement for the future.

• Example Outcomes
• Establish baseline security awareness to accelerate adoption of improved practices
• Accelerates integration of platform controls with enterprise governance and compliance frameworks
• Implements and enforces security best practices to reduce risk across the environment
• Security guidance into day-to-day operations, reducing exposure and risk

Provides guidance for the core Snowflake platform and specialized services, helping customers assess their current maturity, pinpoint efficiencies, and maximize business value.

• Example Outcomes
• A clear understanding of current Snowflake maturity across core platform and specialized services
• Identified efficiency opportunities that reduce cost, effort, and operational friction
• A prioritized plan to maximize business value from Snowflake investments
• Improved alignment between technical capabilities and strategic business goals

Embedded Snowflake expert to support customers on their Snowflake AI Data Cloud journey.

• Example Outcomes
• Enablement of customer teams in snowflake capabilities, functionality and best practices
• Upskilling of customer on features of cloud & security considerations therein