If your data infrastructure isn’t ready for AI, neither is your organization.
In fact, a recent report outlined that 95% of enterprise AI pilot projects are failing to deliver meaningful results. The issue is not the AI models. It comes down to “flawed enterprise integration”, in other words: the inability for enterprises to connect AI systems with the data they need to perform.
And not just any data. For enterprises to break into the elusive 5% of organizations succeeding with AI, they need unified, trusted data from all their critical sources. Data that’s transformed, enriched and delivered in real time.
Fractured systems: The Challenges Behind Data & Platform Modernization
Enterprise data is everywhere. It’s often scattered, siloed, and stuck in legacy systems. That’s why upgrading infrastructure towards a unified dataset is essential for enterprises that aspire to operationalize AI.
Data Silos: Siloed data isn’t just inefficient, it increases risk while eroding trust. In an enterprise environment, the stakes are too high to feed siloed, disconnected data to AI. To succeed, agentic systems need unified, well-governed data that the organization can rely on.
Data Fragmentation: Even when accessible, data is often fragmented across different formats and structures. If it’s not cohesive, consistent, and easily available, enterprise data will fail to provide meaningful context for agentic systems.
Legacy Systems: Rigid legacy systems can’t support the low-latency, high-volume data streams essential for real-time AI. Without fresh, real-time data, agentic AI risks missing new opportunities or worse: acting on false information with disastrous results.
How Striim Modernizes Data Platforms with Trusted, Real-Time Data
Striim’s platform lets enterprises transform disparate, disconnected environments into an integrated, low-latency architecture. With low-latency, schema-aware pipelines sending data from every critical source, AI can train, fine-tune, and reason over a consistent, governed dataset.
Armed with modern data platforms with Striim, enterprises get:
- A single, consistent, governed dataset for AI training
- Full interoperability across open data formats and diverse platforms
- Real-time availability for AI and analytics
- A scalable, future-proof data foundation, ready for AI
Benefit From a Modern, AI-Ready Data Foundation
Enterprise teams shouldn’t waste time fixing broken systems and wrestling with disparate data sets. With Striim, they can get rich, real-time data where it needs to be, and build a future-proof data foundation that’s always AI-ready.
Improved accuracy and effectiveness of AI models
By feeding AI systems with real-time, governed, and context-rich data, Striim ensures that models are always working with the freshest and most reliable inputs. This reduces data drift, improves prediction accuracy, and enables AI to deliver consistent, trustworthy outcomes across critical business scenarios.
Striim unifies siloed, outdated, and disparate systems into a single, AI-ready stream of governed data. This transformation allows enterprises to finally tap into valuable insights hidden in legacy platforms, enabling new analytics, automation, and AI-driven use cases that were previously out of reach.
What this means for you: Feed AI systems with a complete, unified data platform without leaving valuable data behind.
With Striim’s intelligent streaming platform, organizations gain a future-proof data foundation that supports rapid experimentation and deployment of AI. By embedding governance and enrichment in motion, Striim equips teams to confidently build next-generation applications, from predictive analytics to agentic AI systems.
What this means for you: Gain confidence in a clean, consistent, AI-ready dataset.
Data governance is embedded directly into the stream, ensuring sensitive fields are masked, validated, and compliant before they ever reach AI workloads. This lowers audit scope, reduces regulatory risk, and gives enterprises peace of mind that AI decisions are both safe and accountable.
By replacing fragmented pipelines and multiple point tools with a single, enterprise-grade platform, Striim helps organizations cut complexity and reduce total cost of ownership. Teams spend less time maintaining brittle integrations and more time driving strategic AI initiatives, all while consolidating spend across systems and vendors.
Data Modernization in Action: How Sky personalized the customer experience at scale with a unified, compliant dataset
Sky, one of Europe’s leading media and entertainment companies, needed to modernize their infrastructure to enhance the customer experience. They sought to streamline the onboarding process, optimize pricing, and tailor ad experiences for over 17 million customers.
The Striim Solution
With Striim, Sky can deliver real-time, well-governed pipelines into Kafka and unlock analytics in all their downstream systems.
- Real-time personalization enabling tailored ads, dynamic pricing, and customer-specific offers
- Accelerated onboarding made possible by rich customer profiles and history
- Enforced opt-in/opt-out preferences across all systems for audit-ready compliance
- Real-time pipelines sent to Kafka with analytics in BigQuery, Looker, and Tableau
The Results
- Increased engagement with sub-second personalization
- Higher customer lifetime value (CLV) through optimized pricing
- Reduced time-to-value for new users
- Improved customer loyalty with context-aware experiences
- Lower risk of fines under GDPR, CCPA, HIPAA, and AI governance acts
Ready to take the next step, and explore data modernization with Striim? Try Striim for Free, or Request a Demo to learn more.
