Most organizations are not blocked by models or algorithms. They are blocked by data. Fragmented systems, strict regulatory boundaries, and costly data movement make it difficult to operationalize analytics or machine learning at scale. As a result, many projects never progress beyond prototypes because the underlying architecture cannot support secure, distributed execution.
Scalytics Federated addresses this structural limitation. Built by the original creators of Apache Wayang, the platform enables computation to run directly on distributed data sources. No centralization. No replication. No new silos. For ISVs and MSPs, this creates a repeatable and compliant path to deliver real AI and analytics capabilities without forcing clients into disruptive data migrations or expensive infrastructure redesigns.
The Challenge: Why Many AI Projects Never Move Beyond Pilots
IBM’s analysis shows that about 40 percent of AI initiatives remain in pilot stages. Data complexity, legal constraints, and compliance requirements are the main reasons. Centralizing sensitive data increases risk and slows down deployment. It also inflates cloud and storage costs.
For ISVs and MSPs, these issues compound. Clients want AI capabilities, but they require strict security, predictable costs, and solutions that operate within regional or industry specific regulations. Traditional architectures do not solve these constraints.
The Scalytics Approach: Federated Execution Without Data Movement
Scalytics Federated removes the dependency on centralized data systems. Its federated learning and federated data processing model executes computations where data already resides. Sensitive information stays within its original boundaries while operators, models, and workflows are pushed into the local environment for execution.
This approach provides several advantages:
Simplified Compliance
Data locality ensures alignment with GDPR, HIPAA, and sector specific regulations. Auditability and control are preserved without duplicating data.
Cost Efficiency
Eliminating large scale ETL pipelines and cloud data replication reduces operational overhead and infrastructure spend.
Scalable AI Enablement
Predictive analytics, real time decision pipelines, and retrieval augmented generation models can operate across distributed sources without a central warehouse or lake.
Why Join the Scalytics Partner Program
Partners gain a platform that enables AI at scale without forcing clients into disruptive migrations or risky data consolidation. This creates clear differentiation in a crowded market where most vendors still rely on centralized architectures.
Scalytics partners benefit from:
A competitive advantage
Deliver decentralized, secure, and scalable AI solutions that match current enterprise requirements.
New revenue opportunities
Offer AI enablement services built around federated processing, real time analytics, and privacy preserving model execution.
Technical depth and support
Access expertise from the team behind Apache Wayang, including architectural guidance and solution design.
Faster time to market
Integrate with existing client systems without long migration phases or heavy replatforming.
The Early Mover Advantage
AI adoption is accelerating, yet the window for clear differentiation is narrowing. IBM notes that early adopters already outperform competitors in ROI, efficiency, and decision making. Scalytics Federated positions ISVs and MSPs to lead this shift with solutions designed for modern, regulated, and distributed data environments.
Help your clients unlock AI without expensive data movement or compliance risks. Build a sustainable AI service portfolio that scales.
Become an AI enabler. Join the Scalytics Partner Program today.
About Scalytics
Scalytics Federated provides federated data processing across Spark, Flink, PostgreSQL, and cloud-native engines through a single abstraction layer. Our cost-based optimizer selects the right engine for each operation, reducing processing time while eliminating vendor lock-in.
Scalytics Copilot extends this foundation with private AI deployment: running LLMs, RAG pipelines, and ML workloads entirely within your security perimeter. Data stays where it lives. Models train where data resides. No extraction, no exposure, no third-party API dependencies.
For organizations in healthcare, finance, and government, this architecture isn't optional, it's how you deploy AI while remaining compliant with HIPAA, GDPR, and DORA.Explore our open-source foundation: Scalytics Community Edition
Questions? Reach us on Slack or schedule a conversation.
