Press Release
Automat-it, an AWS Premier Partner and Managed Services Provider focused exclusively on startups, today announced the launch of its new Data & Analytics practice. The new offering helps startups build the data foundations required to successfully deploy, scale, and optimize Generative AI (GenAI) and machine learning workloads on Amazon Web Services (AWS).
Data Complexity is Blocking AI ROI
While startups are racing to deploy GenAI applications, the biggest obstacle isn’t the model, it’s the data. Fragmented pipelines, poor data quality, and legacy infrastructure increase cloud spend, drain engineering resources, and often prevent AI projects from reaching production.
Automat-it Data & Analytics: An Enterprise-Grade Data Foundation
Automat-it’s new Data & Analytics practice solves these challenges by modernizing your data platform, automating data pipelines, and building scalable architectures that support AI and machine learning at scale using AWS-native services. By aligning with data mesh principles, domain ownership, and clear SLAs, Automat-it offers scalability, trust, and accelerated time-to-value for your startup.
“A robust data foundation is the difference between an AI experiment and a scalable, production-grade AI product,” said Yoav Zuri, CTO at Automat-it.
“Our new Data & Analytics practice streamlines data preparation and implements scalable lakehouse architectures to transform data from an operational bottleneck into fuel for advanced AI and ML models.”
The new practice expands Automat-it’s portfolio of AWS-focused services, which includes DevOps, FinOps, Cloud Security, and GenAI and agentic solutions, to help customers:
- Build production-ready data platforms: for AI and machine learning workloads.
- Deliver Data as a Product: Utilizing DataOps, automated data CI/CD, and data discovery/cataloging to build highly scalable, consumer-centric data platforms.
- Ensure Privacy & Compliance: By embedding automated PII redaction, data masking, and robust access controls into pipelines for secure, SOC2, HIPAA, and GDPR-compliant AI feeding.
- Power Real-Time Streaming: Transition from batch updates to event-driven architectures (via Amazon MSK and Kinesis) for up-to-the-millisecond AI applications and rapid decision-making.
- Drive Business Intelligence (BI): Bridge raw data and strategy with automated dashboards (e.g., Amazon Quick) to visually track KPIs, model ROI, and monitor product health.
- Create scalable architectures: For RAG, GenAI, and advanced analytics use cases
- Reduce infrastructure costs: Through optimized data architecture and resource utilization
The new Data & Analytics practice already includes:
- ETL Modernization using contemporary technologies: Standardized, automated pipelines that integrate seamlessly with existing AWS services.
- Unified Log Platform: an AWS-native centralized logging solution for predictable, infrastructure-based pricing, deployable in 5 business days.
- Pixel Data Platform: Automates scalable data pipelines without heavy warehouse costs to transform raw, fragmented data into production-grade intelligence, built specifically for RAG pipelines, model optimization, and GenAI workloads running on AWS.
- Modern Data Platform Accelerator: End-to-end ingestion, Medallion Lakehouse architecture, and automated data quality validation (via Deequ) for ultimate accuracy and reliability.
- Multimodal Data Lakes for GenAI Training: Specialized architectures with enterprise-grade security, comprehensive data versioning, and optimized access patterns for text, image, and audio data.
- Data Platform Proofs of Concept (POCs): Rapid evaluation of new architectures and tools to validate performance and reduce risk before full production adoption.
Proven Metrics & Business Impact
Automat-it has a track record of driving significant operational ROI for data-heavy startups. By leveraging Automat-it’s optimization strategies across data and ML architectures, customers have seen model training times reduced by up to 57%, infrastructure costs cut by 40%, and the timeline to deploy production-ready AI solutions shrink from months to a matter of weeks.
“We are committed to empowering the startup ecosystem to build, run, and scale securely on AWS,” said Ziv Kashtan, CEO at Automat-it.
“The launch of our D&A Practice means, as startups transition into an AI-first world, they have a trusted partner capable of optimizing their entire journey, from the deepest data pipelines to the highest-level GenAI applications.”
Start Modernizing Your Data Today
Learn more about Automat-it’s Data & Analytics practice and how to build a scalable data foundation for Generative AI.
Contact our team of data experts here.
