Success Story

BBG: $100K Projected Savings, AI Readiness at Enterprise Scale

BBG partnered with Adastra and AWS to migrate critical workloads to AWS, govern data on Snowflake, and pilot AI for sales and legal to move faster and cut manual work.

20+

AI/GenAI use cases

$100K

projected annual savings from the AI Sales Coach

80%

reduction in manual contract replication with the Legal AI Assistant

About the Client

Breakthru Beverage Group (BBG) is a family‑owned, $10B North American beverage distributor in 16 highly regulated U.S. and Canadian markets.

Solution

BBG, with Adastra and AWS, exited legacy data centers to AWS, set Snowflake data governance, and under clear guardrails launched an AI CoE plus pilots for Breakthru GPT, Sales Coach, Legal Assistant, and a supplier portal.

Success Story

Industry:

Expertise:

AI | AWS

Date:

April 21, 2026

Adastra invested early by co-creating our AI leadership summit and building our first Sales Coach Agent on AWS. That partnership helped us move quickly from ideas to real, measurable value.

Glenn Remoreras
EVP, Chief Information Officer, Breakthru Beverage Group

Challenge

Growth Exposes Legacy Limits: Moving to a Cloud-First, AI-Ready Foundation

Breakthru Beverage Group (BBG) is a family-owned leader in North American beverage distribution with roughly 10,000 employees across 16 markets.

Rapid growth, expanding digital operations, and shifting market dynamics, including changing consumer preferences and rising B2B expectations, exposed the limits of two legacy VMware-based data centers. Scalability constraints, rising costs, and operational complexity made it harder to meet evolving disaster recovery, security, and compliance requirements in a highly regulated industry.

BBG set out to modernize its technology foundation, enable a cloud-first, AI-ready enterprise, and deliver new capabilities across supply chain, sales and marketing, and e-commerce. As a high volume, low margin distributor in a tightly regulated three tier system, BBG needed to drive efficiency and reduce manual work, not just add more tools.

Solution

From Data Centers to AI‑Ready: Cloud Migration, Snowflake Governance, and Early Use Cases

BBG partnered with Adastra and AWS to execute a phased migration and modernization of its on-premises environment, exiting legacy data centers and moving mission-critical workloads, including its e-commerce platform, into a secure, scalable AWS environment ahead of schedule. The program aligned technology execution with business priorities through up-front assessment and governance, rather than one-off projects. In parallel, Adastra helped establish a Snowflake-based data governance foundation to improve data quality, visibility, and AI readiness. 

BBG anchored its approach in a simple AI flywheel, described as a three‑layer cake: the platform layer, the data layer, and the AI layer. The platform layer provides a stable cloud foundation for BBG's core business systems. The data layer brings information together from across the company and makes it reliable and reusable. The AI layer sits on top of this trusted data and powers practical solutions such as assistants, copilots, and analytics inside everyday tools. To scale this approach, BBG is formalizing a Cloud Innovation and AI Center of Excellence, led by its VP of Data and AI in partnership with Adastra and AWS. 

Executive alignment and adoption were built through an AI leadership summit with about 35 senior leaders, including the CEO, shifting focus from pre-baked solutions to the art of the possible and the constraints that matter. BBG educated leaders, co-created pilots with teams, and then began to scale literacy and usage across the company via learning and development initiatives, including a planned AI masterclass. Legal and HR co-developed transparent guardrails and acceptable-use policies to balance speed with security and compliance. 

With foundations in place, BBG moved to tangible initiatives. An internal Breakthru GPT uses internal policies, playbooks, and FAQs so employees can quickly answer "how do we…" questions without escalating to HR, Legal, or IT. An AI Sales Coach, developed with Adastra and AWS, uses existing sell sheets, product information, and sales tactics to give day-to-day coaching on preparation, assortment, and upsell opportunities before customer visits, with adoption driven by manager engagement and coaching rituals. A Legal AI Assistant helps legal and commercial teams replicate and review contracts across markets, states, and even counties, taking account of local regulatory differences and reducing manual copy and paste work. A modernized supplier portal with embedded analytics, stronger data governance, and role-based access improves supplier onboarding, self-service reporting, visibility into performance, and collaboration. 

Impact

Results to Date: Faster Delivery, Stronger Security, 20+ AI Use Cases in Flight

"Our migration to the cloud marks a pivotal milestone in BBG's broader digital transformation strategy. Partnering with Adastra and AWS has given us the confidence and expertise needed to modernize our IT environment while maintaining business continuity."

– James Harrington, VP of Corporate Platforms

Even as migration and modernization continue, BBG reports greater agility in deploying new services, a strengthened security posture via centralized, proactive controls, and improved scalability and resilience to support growth and continuity. The cloud-first shift is freeing IT teams to focus less on maintenance and more on innovation, and BBG has assessed and sequenced more than 20 AI and generative AI use cases using the same value and viability framework introduced at the AI leadership summit, so delivery remains focused on real business constraints and outcomes. 

  • ~$100K projected annual savings from the AI Sales Coach (reduced onboarding and turnover costs), with additional upside expected from faster ramp-up and improved cross-sell and upsell conversions. 
  • Legal AI Assistant: ~80% projected reduction in manual contract replication, ~$56,280 projected annual savings, and ~190 hours per year saved through faster, standardized turnaround. 
  • 20+ AI and GenAI use cases assessed and sequenced for delivery based on feasibility, impact, and data readiness. 

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