The foundation every AI data project needs
AI initiatives fail without trusted, compliant, well-governed data. Many organizations lack the frameworks and controls to make their data AI-ready, leading to wasted investment, compliance risk, and stalled adoption. We establish governance frameworks, quality controls, and lineage tracking so your AI and analytics run on accurate, compliant, and secure data. Our experts cut preparation time by 80%, turning AI readiness into measurable business value.
Compliance you can trust
You need governance that satisfies strict regulations without slowing down innovation. Our certified Snowflake experts deliver frameworks aligned with GDPR, SOC2, and HIPAA to protect your organization while driving AI-ready growth and trusted decision making.
Reliable data, every time
Your teams should not waste time questioning datasets or second-guessing reports. With continuous monitoring, lineage tracking, and metadata management, you always know where your data comes from and how reliable it is.
AI that’s ready to deliver
Move beyond pilots and proofs of concept. Our experts run readiness audits and build ML-ready pipelines with governance, quality controls, and compliance frameworks built in. This gives your AI initiatives the foundation to succeed at enterprise scale.
Why leaders choose our data solutions
Trusted AI outcomes
Run every AI initiative and machine learning project on trusted data foundations.
Compliance risk protection
Reduce regulatory violations, compliance risks, and reputational damage across all data operations.
Enterprise-wide adoption
Increase executive confidence and drive faster enterprise-wide adoption of AI and analytics initiatives.
Competitive AI advantage
Deliver enterprise AI solutions faster and gain an edge over competitors facing governance challenges.
The expert-led delivery framework
No big bang, no black boxes
You never wait months with nothing to show. Instead of one risky launch work is delivered in steady steps you can test and trust.
Progress you can follow
You don’t get vague updates or empty promises. Regular checkpoints, demos, and updates keep you in the loop.
Flexibility when priorities change
Your priorities can change. Our approach adapts without slowing down so new requirements or scope changes never stop delivery.
Commitment you can rely on
You gain a partner, not just a vendor. With solid planning and experienced teams, we keep projects aligned and accountable.
Speed with quality built in
You reach production with no shortcut. We deliver your solution to production quickly with quality and security built in.
Value that drives your business forward
Every step delivers measurable impact. We focus on what reduces cost, speeds up insight, and drives real business growth.
How we transform data operations
How a top global logistics leader boosted BI performance by 65% with Snowflake
One wrong move during their Snowflake migration could have brought down hundreds of BI applications and reports. With legacy systems built over 15 years and rising maintenance costs putting operations at risk, this top-5 global logistics company faced its most critical data challenge yet.
One wrong move during their Snowflake migration could have brought down hundreds of BI applications and reports. With legacy systems built over 15 years and rising maintenance costs putting operations at risk, this top-5 global logistics company faced its most critical data challenge yet.
Our experts at Snowstack stepped in to navigate this complex transformation. The outcome? A smooth migration that turned the company’s greatest risk into a long-term competitive advantage.
Key outcomes:
- Report performance improved by 65%, with dashboards running in minutes instead of hours.
- Infrastructure costs fell by 40% while system performance increased.
- The migration achieved zero disruption, maintaining 100% uptime.
- Over 65% of legacy SQL was converted automatically, saving months of effort.
- More than 40 developers were trained and upskilled on Snowflake.
Over the years, our BI teams developed an effective approach to data modeling, which had long been a strength. However, with the ongoing migration of the central data warehouse to Snowflake, we knew that adopting new tools could take months, if not years. We urgently needed support from Snowflake professionals to guide the adoption process and help our BI teams incorporate the new technology into their workflows. - Lead Data Architect
Client overview
The client operates as one of the top 5 key players in the industry, managing supply chains that span multiple continents and serve millions of customers worldwide. Their data ecosystem had evolved organically, supporting hundreds of BI applications that power everything from real-time shipment tracking to route optimization algorithms.
The client’s BI reports weren't just internal dashboard. They powered customer-facing systems that enterprise clients used to track shipments worth millions of dollars. Any disruption to these systems could trigger contract penalties and damage relationships with major accounts.
The challenge
15 years of business growth had created a BI environment that was difficult to manage. Hundreds of reports were built independently by different teams with varying skill levels. Although they all drew from the same data warehouse, each team applied its own transformation logic within separate BI systems. What began as team-specific solutions had grown into a web of technical debt that no one fully understood.
Our solution
Recognizing the critical need for modernization, the client made the strategic decision to unify their data model and move it to Snowflake alongside their ongoing data warehouse migration. We guided the client through five steps.
Step 1: identifying the foundation
Together with the client, we analysed their extensive BI landscape to identify the datasets most frequently used across reports. This joint assessment defined a minimum viable product (MVP) scope that would deliver immediate value and build momentum for the broader transformation.
Step 2: building the Snowflake environment
We worked with the client to establish a dedicated Snowflake environment designed specifically for BI collaboration. Together, we implemented:
- Standardized schemas and roles to ensure consistent data access patterns across teams
- Compute scaling strategies optimized for BI workloads
- Role-based access control (RBAC) to strengthen governance
- BI-specific access patterns tailored to Snowflake datasets
Step 3: automating the migration process
To accelerate the transition and protect prior investments, we partnered with the client to implement automated migration scripts that converted legacy SQL into Snowflake SQL. This achieved a 65% automatic refactor success rate, dramatically reducing manual work while preserving business logic.
Step 4: orchestrating seamless integration
In close collaboration, we designed and deployed new orchestration pipelines that synchronized Snowflake model builds with BI report refreshes. These pipelines were integrated with the client’s existing technology stack, including:
- Airflow Snowflake Operator for workflow management
- AWS SNS for notifications
- AWS S3 for data staging
- Git for version control
Step 5: investing in the team
Recognizing that technology transformation must go hand-in-hand with people transformation, we partnered with the client to deliver training for more than 40 BI developers. This knowledge transfer ensured teams could confidently work with Snowflake as their new backend, embedding long-term value into the organization.
Foundation for Future Innovation
Still running hundreds of disconnected BI reports with inconsistent data models?
Upgrading your BI architecture is no longer a matter of if. The real question is how quickly you can create a one source of truth before competitors pull so far ahead you can’t catch up. The companies winning today are those replacing broken reporting with accurate, unified data that every team can trust. Each month you delay, they improve decision accuracy and grow their market share.
We help you close that gap fast. Our Snowflake-certified experts bring years of experience and a proven approach to modern BI transformation. We can take years of messy, disconnected systems and turn them into a single, reliable analytics platform in months. With one source of truth in place, your teams spend less time fixing reports, more time acting on accurate information, and deliver faster business decisions.
Ready to unify your BI architecture on Snowflake?
Project details:
- Industry: Global Logistics & Supply Chain
- Duration: 3 months implementation
- Engagement Model: Migration service with comprehensive training & support
- Team Composition: Lead Architect, Data Engineers, Migration Specialists, BI Developers
- Frequently Used Snowflake Components: Warehouses, RBAC, Snowpipe, Tasks & Streams, Secure Data Sharing, Materialized Views, Time Travel, Stored Procedures
- Other Tools Integrated: Airflow Snowflake Operator, AWS SNS, AWS S3, dbt, Fivetran, Power BI, Azure AD
How a global finance leader achieved AI readiness in 90 days with Snowstack
Monthly spend had passed $800K with no clear breakdown of where the money was going. By partnering with us, they gained full visibility and, within 90 days, turned uncontrolled costs into a governed, AI-ready platform built for scale.
$800K in cloud costs every month, and no explanation. For a leading financial services firm, cloud was critical to scaling the business, yet it had become one of the fastest-growing expenses. Monthly spend had passed $800K with no clear breakdown of where the money was going. By partnering with us, they gained full visibility and, within 90 days, turned uncontrolled costs into a governed, AI-ready platform built for scale.
Key outcomes:
- Data ingestion latency reduced by 80%
- AI-readiness achieved in 90 days
- Real-time cost monitoring and automated optimization
- Modern data platform for analytics, ML, and AI use cases
Client overview
Our client is a financial services company generating $500M in annual revenue with a team of 2,500 employees across North America and Europe. In the midst of rapid growth, they were transitioning from legacy systems to a modern cloud data platform built on Snowflake. But they faced rising cloud costs and a fragmented data landscape.
The challenge
Our client had ambitious AI and GenAI goals, but lacked the foundational architecture to support them cost-effectively.
The client knew what Snowflake could deliver but needed the right partner to design, implement, and operationalize a solution that would translate that capability into measurable business value.
Our solution
The client set out to gain full visibility, governance, and scalability in their cloud environment. By partnering with us, they implemented a modern, AI-ready data platform built on Snowflake to address the challenges limiting performance.
Unified data Ingestion with OpenFlow
They consolidated structured and unstructured data from SharePoint, Salesforce, and custom systems into a single ingestion framework, eliminating fragmented pipelines and enabling real-time analytics.
Centralized Metadata and governance with Horizon Catalog
They integrated metadata from BI tools, dbt models, and Iceberg tables into one governed repository, achieving full lineage visibility, consistent KPIs, and stronger compliance controls.
Consistent logic with semantic views
Business rules were embedded directly into the data layer. This made sure that every team worked from the same definitions for analytics and AI training.
Self-service analytics with Cortex AI SQL
Business users can now query governed datasets in natural language, reducing reliance on engineering and accelerating decision-making.
FinOps cost governance
Daily cost visibility, clear ownership tracking, and accurate forecasting were integrated into operations, turning cost control into a proactive practice.
Why it mattered
If you can’t see your cloud costs, you’re losing money. In many enterprises, unused services, duplicate workloads, and unclear cost ownership quietly drain millions each year. Without visibility and governance, budgets overspend, AI projects stall, and growth slows.
Our team provides the insight and control to stop waste, making every cloud dollar accountable and directly tied to business results. So start controlling your cloud spend today.
Book a Snowflake consultation.
Project details:
- Industry: Financial Services
- Duration: 90 days (initial build) + ongoing support
- Engagement Model: FinOps & AI readiness program
- Team Composition: Snowflake Solution Architect, Data Engineers, BI Specialist, Data Governance Lead
- Frequently Used Snowflake Components: OpenFlow, Horizon Catalog, Cortex AI SQL, Semantic Views
- Other Tools Integrated: SharePoint, Salesforce, dbt, Fivetran, Power BI
Enterprise-grade security
Enterprise security controls and governance frameworks built into every Snowflake implementation. Role-based access, data encryption, and audit trails configured from day one.
SOC 2
Compliance
What our clients say
An AI-ready data foundation means your data is properly structured, governed, and high quality so AI and ML models can use it without manual prep or fragmented sources. In Snowflake this process is faster and more efficient, with built-in capabilities to share data securely across teams and, with Cortex, make AI integration even simpler.
Excellent. Snowflake provides built-in ML capabilities, integrates with Python/R, and supports popular ML frameworks. We structure your data and implement governance to support both current analytics and future AI initiatives.
Snowflake is easier to use and has better built-in governance features. Databricks is good enough for custom machine learning projects, but Snowflake handles most business AI needs with less complexity and better data control.
We implement data quality controls, create curated datasets, establish data lineage, and configure APIs that ML teams can use reliably. Your data scientists get clean, documented datasets ready for model development.
Most companies who work with us see improvements in data quality and governance within the first 30 days. Using our Sled Framework, a full AI ready foundation with governance and secure data sharing is typically in place within 90 days.
No. Client data stays in your environment under your full control. Snowstack designs governed architectures where data is only used for the agreed business use cases. In pharma and finance projects, we implemented controls to prevent non-auditable access and ensure data was never exposed outside the client’s Snowflake and cloud setup .
Our clients see results within 2–3 months. In one FMCG engagement dashboards loaded 10x faster and time-to-insight improved by 80%. In finance and pharma projects, clients gained full lineage control, reduced reporting times by 80%, and achieved compliance-ready environments in under 90 days.