Artificial intelligence has shifted from hype to mandate.
In 2023, enterprises were experimenting with pilots. By 2024, AI spending had surged sixfold to $13.8 billion. In 2025, AI is no longer optional—it’s a board-level directive. Yet despite the urgency, 74% of companies still struggle to achieve and scale value from AI. Most face the same blockers: fragmented data across legacy and cloud systems, stale insights arriving hours too late, and a lack of governed, trusted data streams that AI can safely use in real time.
This is where Striim comes in.
Striim powers real-time intelligence for enterprise AI, providing the intelligent data infrastructure and event-driven streaming needed to operationalize AI at scale. Unlike batch ETL tools, open-source DIY stacks, or ingestion-only SaaS vendors, Striim delivers sub-second, governed data streams that are AI-ready from day one.
And crucially: Striim’s process is not just part of the AI journey—it is the AI journey. We meet enterprises where they are, guiding them through the four stages to operationalize AI:
Let’s walk through each stage and see how industry leaders are already using Striim to move from AI ambition to execution.
Stage 1: Cloud Migration & Adoption
For agentic AI to deliver to its full potential, it needs to live where innovation happens: the cloud. But moving massive volumes of critical data from legacy, on-premise systems is a high-stakes operation where downtime isn’t an option and data integrity is crucial.
The Challenges of Moving to the Cloud
Data Downtime: Enterprises cannot risk downtime, where even minutes of missing data could break AI responses and lead to poor outcomes for customers, partners, and the bottom line.
Data Inconsistency: Nor can enterprises afford data inconsistency during cutovers. Data cleaning or reformatting on arrival can be costly, inefficient and disruptive to AI systems.
Complex Integrations: Stitching together legacy systems, cloud platforms, and modern AI applications often requires brittle, custom-built pipelines that can’t support AI at scale.
How Striim Delivers Best-In-Class Cloud Migration:
With industry-leading change data capture (CDC), in-stream transformations, and sub-second latency, Striim is best-in-class when it comes to getting enterprise data from legacy systems into AI-ready cloud environments.
Striim’s fast, low-risk cloud migration lets enterprises focus on what they do best: innovating for their customers and delivering value.
Migrating to the Cloud with Striim Gives You:
- Lower migration and modernization risk through resilience and governance.
- Faster innovation and AI adoption with real-time, cloud-ready data.
- New revenue streams via AI-driven products.
- Strengthened compliance with governed data.
- Enhanced competitive edge with faster AI deployment cycles.
| Curious to see a real-world example of cloud migration with Striim? | Read Kramp’s story |
Stage 2: Data & Platform Modernization
With data now in the cloud, the next critical step is modernizing the underlying platform to make that data useful for AI. The goal is to create a unified architecture, like a data lakehouse, that acts as a single source of truth.
The Challenges of Fragmented, Legacy Systems
Data Silos: For enterprises, data is scattered across disconnected systems and siloed teams. This holds companies back from getting the unified view required for advanced analytics and AI.
Data Fragmentation: Even when accessible, data is often fragmented across different formats and structures.
Legacy Systems: Rigid legacy systems can’t support the low-latency, high-volume data streams essential for real-time AI and analytics, creating a bottleneck for innovation.
How Striim Delivers a Modern, AI-Ready Data Foundation
With continuous ingestion from every source, automated schema handling, and in-stream transformations, Striim ensures data is always AI-ready. The platform’s elastic scaling and interoperability with open data formats provide a truly future-proof data foundation.
With Striim, enterprises can stop wrestling with fragmented data and start building next-generation AI applications.
Modernizing with Striim Brings:
- Improved accuracy and effectiveness of AI models.
- Unlocked value from fragmented and legacy data.
- A solid foundation for new AI-driven initiatives.
- Reduced compliance and operational risk with governed streams.
- Lowered operational cost by consolidating platforms and silos.
| Want to learn more about a real modernization success with Striim? | Read Morrison’s story |
Stage 3: Upstream Analytics
AI and agentic systems need fresh, real-time data. By the time information arrives in hourly or daily batches, it’s already stale, and the window of opportunity for your AI to act has closed.
The Challenges of Stale Data
Delayed Insights: Traditional analytics rely on batch processing, meaning insights are generated from data that is hours, or even days, old. This prevents AI models from acting on what is happening in the business right now.
Missed Opportunities: The lag between when an event occurs and when it is analyzed results in missed opportunities. Businesses cannot instantly respond to changes in customer behavior, market shifts, or operational issues, limiting their agility.
Reactive Decision-Making: Batch analytics forces organizations into a reactive posture, where they can only look back at what has already occurred. This limits the ability of AI to be truly predictive and respond to live events as they unfold.
How Striim Delivers Real-Time, Upstream Analytics
With ultra-low latency in-stream processing, advanced streaming analytics, and built-in anomaly detection, Striim delivers sub-second insights directly from the data stream. The platform provides full pipeline observability and feeds context-rich, governed streams into AI systems for instant action.
With Striim, enterprises can stop making decisions based on stale data and start acting on live intelligence.
Upstream Analytics with Striim Delivers:
- Improved operational efficiency through faster actions.
- Competitive advantage via instant responses to market and customer shifts.
- Reduced risk with real-time anomaly detection and intervention.
- Enhanced customer experiences with adaptive, AI-driven services.
- Continuous innovation through live insights.
| Curious to learn what Upstream Analytics with Striim looks like in action? | Read Clover’s story |
Stage 4: Agentic AI
AI and agentic systems have the potential to transform virtually every industry. But to be in a position to benefit from AI, enterprises need a governed, trusted, real-time data foundation, as well as the means to make this data available to agents in a safe, non-disruptive environment.
The Challenges of Running AI on a Shaky Data Foundation
Production Data Risk: Granting AI agents direct access to live production databases and systems creates significant security and operational risks.
Lack of Trust & Verifiability: Without a governed, verifiable, and continuously validated data source, enterprises cannot trust AI agents to make autonomous decisions.
Data Governance & Compliance: Deploying autonomous agents that interact with sensitive enterprise data creates major governance and compliance hurdles. It becomes incredibly complex to ensure adherence to regulations like GDPR, HIPAA, and the EU AI Act when agents have direct access to production data.
How Striim Enables Safe, Scalable, Intelligent AI
Striim’s platform was built to solve the core challenge of trust and safety in agentic AI.
Striim embeds a suite of AI agents directly into the data stream to make data safe, intelligent, and AI-ready. Governance agents like Sherlock AI & Sentinel AI automatically discover and mask sensitive data, Euclid prepares data for RAG architectures by transforming it into vector embeddings, and Foreseer detects and predicts anomalies directly in the data stream.
With MCP AgentLink, continuous, real-time, cleansed, and protected data replicas give agents access to fresh, accurate data without exposing production systems. This means enterprises can leverage MCP-ready, event-driven architectures and take full advantage of autonomous, agentic systems.
With Striim, enterprises can move from AI ambition to execution, deploying agents with confidence. They have the power to scale intelligent operations safely, knowing that their data is governed, their production systems are protected, and their AI-driven outcomes are built on a foundation of trust.
Agentic AI with Striim Delivers:
- Faster AI operationalization with trusted, compliant pipelines.
- Strengthened compliance with GDPR, HIPAA, and the EU AI Act.
- Enterprise-wide trust in AI-driven outcomes.
- Reduced compliance costs by automating data governance.
- Accelerated ROI with production-grade, scalable AI deployments.
| Curious to see real-time AI in action? | Read UPS’ story |
Take the next step towards AI readiness, with Striim
The four stages—Cloud Migration, Data Modernization, Upstream Analytics, and Agentic AI—represent critical steps on this path. Striim provides the unified platform to navigate each stage, transforming fragmented, risky data operations into a secure, real-time engine for innovation.
The age of AI is not just coming; it’s already here. With the right data infrastructure, your enterprise won’t just be ready for it—you’ll be leading the charge.
Ready to take the next step? Try Striim for free or book a demo to see how you can activate your data for AI.
