Data your AI agents and board can actually trust
Accuracy and governance, not just access control
RBAC controls who can query a table; it says nothing about whether that table is right. Most "AI-ready" problems are really data-quality problems: stale feeds, conflicting definitions, numbers that do not reconcile. We fix the data underneath: reconcile source-to-report, add freshness and quality checks, trace lineage end to end, and encode business definitions once in a governed semantic layer your agents and BI both read.
Data quality you can prove
We reconcile source-to-report, add freshness and completeness checks, and catch the broken or partial feeds that quietly poison a metric, so a number is right before anyone, or any agent, trusts it.
One set of trusted definitions
Net revenue, active customer, fiscal year, defined once in a governed semantic layer, under RBAC, where Cortex Analyst and your dashboards read the same logic. No more five versions of the truth.
Governed and safe to ship
Lineage, access controls, masking, and audit trails aligned to SOC 2, HIPAA, and GDPR, so agents run on data that is not just accessible, but accurate, compliant, and current.
Why data leaders work with us
Trusted AI outcomes
Run every AI initiative and agent on data foundations you can trust.
Compliance under control
Privacy, legal, and security see exactly what is happening with the data, making approvals and audits straightforward.
One governed source of truth
One set of definitions instead of five conflicting versions, consistent across analytics and AI.
Ship agents that are right
Deliver new AI use cases faster than competitors still fighting data-quality and governance gaps.
Our signature Snowflake consulting methodology
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 our Snowflake consulting transforms data operations
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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.
How a $45B FMCG leader regained control of their Snowflake platform with Snowstack
Companies that fail to master their data platforms in 2025 will not just fall behind. They will become irrelevant as AI-native competitors rewrite the rules of the market.
Companies that fail to master their data platforms in 2025 will not just fall behind. They will become irrelevant as AI-native competitors rewrite the rules of the market. One global FMCG manufacturer recognized this early on. By partnering with us, they turned their underperforming Snowflake environment into an innovation engine.
Key outcomes:
- 30% reduction in Snowflake costs through intelligent optimization
- 60% faster incident resolution with 24/7 monitoring
- 5+ new AI/BI use cases unlocked from reliable, curated datasets
- 100% audit readiness for SOC 2 and GDPR frameworks
Having a dedicated Snowflake team that truly understands our platform made all the difference. We no longer chase incidents or firefight pipeline issues - we’re focused on enabling the business. Their ownership, responsiveness, and expertise elevated our data platform from a bottleneck to a strategic asset. - Senior Director, Data Platforms
Client overview
The client is a multinational Fast-Moving Consumer Goods (FMCG) manufacturer operating in over 180 countries through both corporate offices and an extensive franchise network. With global revenues exceeding $45 billion and more than 6,300 employees worldwide, they manage a diverse product portfolio distributed through complex regional supply chains.
The challenge
Despite investing in modern cloud infrastructure, the client was stuck. Their internal teams lacked the specialized expertise needed to run the platform. When key engineers left, so did the expertise. This resulted in growing technical debt. Critical pipelines regularly failed or ran late. Compliance and audit demands became difficult to satisfy due to inconsistent governance. Without proper optimization, Snowflake costs increased. As a result, the platform’s reputation fell from being seen as an innovation enabler to becoming a business blocker.
What made things even harder was the seasonal nature of FMCG operations. Demand for data engineering resources fluctuated throughout the year. Resource needs spiked during busy times and dropped during slow periods. This led to ongoing hiring and retention challenges. Meanwhile, competitors kept moving forward with steady expertise and data strategies.
Our solution
The client wanted a better way to manage their data and prepare for future growth. They asked us to provide a full Snowflake delivery team that could handle the project from start to finish. Instead of hiring separate contractors, they gained a team of Snowflake-certified experts who worked together to deliver the solution quickly.
Our execution
With our support, the client regained platform stability, resolved recurring system issues, and accelerated the delivery of new data solutions. The Snowflake environment became easier to manage, more predictable, and better aligned with business priorities.
Structured collaboration
The client led a phased rollout, supported by bi-weekly service reviews and backlog planning sessions. We worked directly within their workflows (Slack, Teams, Jira) and joined daily stand-ups and steering meetings. To help address long-standing challenges with knowledge retention, we introduced clear RACI ownership and thorough documentation practices.
SLA-Driven Support Model
The engagement featured a service model tailored to the client’s operational needs. Platform support was aligned to business hours, extended hours, or 24/7 coverage depending on requirements. SLAs were defined by incident severity, with guaranteed response and resolution times in place. To give the client real-time visibility and control, we implemented automated monitoring and alerting.
Platform optimisation and future-proofing
The client was committed to building a Snowflake environment that could scale with the business. With our support, they focused on optimising performance, controlling costs, and staying ahead of future demands.
Faster delivery, greater impact
We supported ongoing initiatives by onboarding new data sources, integrating BI tools and APIs, and maintaining platform standards across internal and third-party teams. Automation and reusable pipelines cut source-to-Snowflake integration time from weeks to days.
Continuous improvement and strategic reporting
Monthly platform reports provided clear visibility into KPIs, usage trends, incidents, and optimisation opportunities. This helped the client move from reactive support to a proactive and data-driven platform management.
Governance and security practices
To support regulatory and internal compliance requirements, we implemented platform-wide governance controls. These included RBAC, data masking policies, access audits, and full alignment with SOC 2 and GDPR frameworks.
The results
Strategic value
Owning a data platform is not the goal. Making it work for the business is.
This partnership showed how Team as a Service can turn a complex platform into a strategic asset. By working directly inside the client’s operations, our certified Snowflake experts turned a complex, high-maintenance platform into a scalable foundation for growth.
Now, they are ready to take on AI and advanced analytics, backed by an architecture built to grow with the business.
At Snowstack, we don’t just help companies manage Snowflake. Our model helps enterprises stay ahead in a data environment that keeps changing
Ready to turn your Snowflake platform into a competitive advantage?
Let’s talk about how our team can help you get there
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 TYPE II
Certified
HIPAA Certified
What our clients say
It means your data isn't just access-controlled, it's correct. AI-ready data governance covers the data quality and definitions underneath your platform: source-to-report reconciliation, freshness and completeness checks, end-to-end lineage, and one governed semantic layer where every metric is defined once. The result is data your dashboards and AI agents can both read and trust, accurate, governed, and safe to ship.
Usually it isn't the model, it's the data and the definitions. Agents answer from stale feeds, partial loads, or metrics defined three different ways across the business, so the same question returns three different numbers. We fix the data underneath: reconcile source-to-report, add freshness and quality checks, and encode each definition once in a governed semantic layer, so the agent and your dashboards read the same trusted logic.
RBAC controls who can query a table; it says nothing about whether that table is right. Most 'AI-ready' problems are really data-quality problems: stale data, conflicting definitions, numbers that don't reconcile. Access control is necessary, but accuracy and governance go further, with reconciliation, freshness, lineage, masking, audit trails, and consistent definitions, so the data an agent reaches is both permitted and correct.
We reconcile source-to-report so figures tie back to their origin, add freshness and completeness checks to catch broken or partial feeds, and trace lineage end to end. Business definitions live once in a governed semantic layer that Cortex Analyst and your dashboards both read. Where it matters, we measure agent accuracy against your own KPIs before anyone relies on it.
Governance is built in, not bolted on. Lineage, role-based access, masking, and audit trails are aligned to SOC 2, HIPAA, and GDPR, so privacy, legal, and security can see exactly how data is used and approvals and audits stay straightforward. Agents and analysts run on data that's not just accessible, but accurate, compliant, and current.
We start with a fixed-scope assessment that maps where your data breaks agents and dashboards today. Most clients see data-quality and governance wins within the first 30 days, with a governed, agent-ready foundation typically in place around 90. Pricing is transparent and outcome-aligned: a fixed-fee assessment first, then scoped sprints or a fractional platform team.
