We’re proud to announce that PYGIO is a launch partner for Snowflake Intelligence, a major step forward for enterprise AI in Africa. In this article, we will highlight production use cases of how we have implemented Snowflake Intelligence for our clients.

How PYGIO uses Snowflake Intelligence

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We integrate Snowflake Intelligence directly into client environments through Pygio Assembly, our AI Acceleration Framework. Assembly helps teams utilise raw, unstructured, semi-structured and structured data sources to build real enterprise intelligence with:

• Structured, governed data
• Tools for processing unstructured content
• Industry-specific business-ready semantic layer
• OOTB industry ontologies for BFSI, Telco, Retail, and Industrial Tech

With these foundations in place, clients can activate AI agents and analytics quickly, safely, and at scale. Here's how we're using Snowflake Intelligence:‍

Case #1: Transactional Monitoring for Financial Services

‍Problem: South African banks face rising AML pressure, with alert volumes exploding and over 90% false positives overwhelming compliance teams. Traditional rules-based systems miss complex laundering patterns and can’t keep up with the scale of modern transactions.

PYGIO Solution: Using Snowflake Intelligence, all transactional and customer data is unified into a governed graph model of the bank. This exposes relationships, money flows, and hidden networks that rules-based systems fail to detect.

A hybrid detection engine then applies:

• Graph-based anomaly detection
• Self-supervised learning that understands transaction behaviour
• Real-time scoring and automated reporting

Impact: 

• 20–50% fewer false alerts
• Faster investigations (30–50% less handling time)
• Clearer detection of mule networks, structuring, and layering - understanding known money laundering patterns
• Stronger compliance and reduced regulatory risk

This delivers a modern, AI-driven approach to AML that actually keeps up with how criminals move money today.

Case #2:  Wealth Advisor Agents

Problem: Wealth and asset-management teams struggle with fragmented customer data and slow access to portfolio insights, which leads to missed opportunities, inconsistent advice, and higher churn risk. Advisors often operate across many isolated systems and cannot easily access a single, up-to-date client picture, limiting their ability to provide timely recommendations

PYGIO Solution:

Using Snowflake Intelligence, client, portfolio, transactional, and product data is unified into a single advisor-ready view. This enables AI agents to surface insights instantly, such as cross-sell opportunities, churn risk factors, unusual withdrawals, and investment recommendations. Advisors no longer need to switch between systems; insights are delivered conversationally through an advisor co-pilot interface. 

What the AI Agent delivers:

• Instant 360° client and portfolio visibility
• Real-time portfolio, risk, and behaviour insights
• Natural-language answers to advisor questions (“What changed in this client’s portfolio this week?”, “Show churn risks.”)
• Personalised recommendations using bank-specific data models
• Signals for wallet-share leakage and early churn indicators

Impact: 

• Wealth Advisor Agent can lead to 23% higher customer LTV (lifetime value)
• Stronger client engagement and personalised advice
• More revenue opportunities through next-best-action insights
• Faster prep for meetings and client conversations
• Reduced churn by identifying risk signals early
• Elimination of internal service-desk dependency for basic queries

Case #3:  Dark NOC Revenue Assurance for Telco

‍Problem: Large telcos run millions of daily network and billing events across prepaid, postpaid, roaming, wallet, and partner systems. According to internal material, these environments are often fragmented, generating blind spots that lead to revenue leakage, undetected anomalies, and delayed root-cause investigations. Traditional assurance systems struggle to combine subscriber, network, and transaction data fast enough for real-time detection.

PYGIO Solution: Using Pygio Assembly and Snowflake Intelligence, all network, billing, usage, partner, and financial data is unified into a governed model of the telco environment. This enables an AI-driven Dark NOC, an autonomous layer that monitors and self-corrects for network operations, leakage, irregular patterns, and integrity failures across the entire revenue chain.

What the AI Agent delivers:

• Detect billing gaps, rating errors, and duplicate/failed charge events
• Identify unusual network behaviour linked to revenue loss
• Highlight partner-settlement issues, roaming discrepancies, or wallet anomalies
• Provide root-cause explanations in plain language
• Notify operations teams with recommended actions
• Continuously learn from historical events to improve accuracy
  

Impact:

• Enhances and builds autonomous network operations
• Significant reduction in revenue leakage
• Faster escalation and resolution of network or billing anomalies
• Lower operational cost through early detection
• Better partner-settlement accuracy
• More reliable customer billing and reduced disputes
  
  

This creates a proactive, AI-enabled revenue assurance function, shifting telcos from reactive investigations to continuous, automated monitoring across the entire network and billing ecosystem.

Driving the next phase of AI in South Africa

The PYGIO-Snowflake partnership combines:

• PYGIO’s hands-on AI and data engineering experience
• Snowflake’s secure, scalable AI Data Cloud
  
  

Together, we help clients turn data into intelligence that drives outcomes across compliance, customer engagement, risk management, and network operations.

As Dimitri Gonatas, CEO of PYGIO, said at SnowDay Johannesburg:

“This isn’t about experimenting with AI,  it’s about operationalising it. Together with Snowflake, we’re helping enterprises make intelligence real, measurable, and secure.”