
Enterprise Data Foundation
Establish a robust data infrastructure designed to enable AI applications across your organization.

Enable Enterprise-Wide AI Integration
Convert your organization’s data and infrastructure into an AI-ready ecosystem. Get a robust technical foundation that enables seamless AI integration, real-time processing, and scalable operations.
Business Challenge
Data Silos
of time is spent on data discovery, preparation, and protection, and only 20% of time is spent on actual analytics
Efficiency Loss
of data users’ time is spent searching for data when there’s no clear inventory and governance
Service Overview
Establish a robust data infrastructure designed to enable AI applications across your
organization
- Cloud/on-premise architecture setup
- Storage solutions implementation
(data lake, warehouse) - Security controls and framework
- Monitoring and logging systems
- Backup and disaster recovery
- ETL/ELT pipeline development
- Real-time/batch processing systems
- Data quality management
- Source system connectivity
- Data catalog implementation
- Data standardization and enrichment
- Schema alignment and Master Data
Management (MDM) - Data governance framework
- Business rules implementation
- Quality validation framework
Measurable Business Outcomes
Data Silos Reduction
Modern data foundation eliminates fragmented data sources, enabling unified data access across departments.
Data Quality
Improved data accuracy and consistency through standardized validation and governance processes.
Rapid ROI Realization within
Organizations achieved a significant ROI through reduced infrastructure costs and improved operational efficiency.
Cost & Investment
Project Scope and Complexity
- Number and complexity of use cases
- Depth of customization required
- Integration requirements with existing systems
Team Composition
- Size of the development team
- Expertise level required
- Need for specialized roles
Training and Support
- Level of training required for client’s team
- Duration and extent of post-deployment support
How Enterprise Data Foundation Works
Our program establishes three critical layers for enterprise AI success and further AI agents and traditional ML systems deployment and scaling.
Phase I: Data Architecture
- Multi-tenant data architecture design
- Data quality management establishment
- Real-time or batch data processing
- Custom ETL/ELT pipeline setup
Phase II: Data Harmonization
- Multi-modal data vectorization
- Organization knowledge graph creation
- Semantic layer implementation
- Search and retrieval applications testing
Phase III: On-premise or Cloud Infrastructure
- Agent-ready cloud architecture development
- MLOps & LLMOps platforms rollout
- System monitoring dashboard integration
- Scalability & performance audit and optimization
Testimonials
Generative AI Success Story
Roman Jasins, Co-Founder of Peak Defence, shares the technical perspective on the successful implementation of their GenAI based cybersecurity platform in collaboration with Neurons Lab and AWS.
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