Sold by: Kriv AI
End-to-end data and AI pipeline engineering for organizations building modern data platforms on AWS. Kriv AI designs and implements data lakes, ETL/ELT pipelines, real-time streaming, and AI/ML data preparation using Amazon Redshift, Glue, SageMaker, Bedrock, Kinesis, and S3. Specialized in regulated industries with built-in data governance, lineage tracking, and compliance controls. 4-8 week fixed-scope engagement. Databricks Partner for hybrid lakehouse architectures. Includes architecture documentation, monitoring, and team training.
Overview
Every AI initiative depends on a solid data foundation. Yet most organizations struggle with fragmented data, inconsistent pipelines, poor data quality, and governance gaps that block AI adoption. The result: 73% of enterprise data goes unused, and AI projects fail because they cannot access clean, governed, production-ready data.
Kriv AI's Data and AI Pipeline Engineering service builds the data infrastructure your AI needs to succeed -- designed from the ground up for regulated industries where data governance is not optional.
WHAT WE BUILD:
Data Lake Architecture: Modern data lake on Amazon S3 with medallion architecture (Bronze/Silver/Gold layers). Raw data ingestion, cleansing, transformation, and curated datasets ready for analytics and AI/ML workloads.
ETL/ELT Pipelines: Automated data pipelines using AWS Glue, Step Functions, and Lambda. Support for batch processing, micro-batch, and real-time streaming via Amazon Kinesis. Error handling, retry logic, and monitoring built in.
AI/ML Data Preparation: Feature engineering, data labeling workflows, training/validation/test dataset management, and model input pipelines. Integrated with Amazon SageMaker and Bedrock for seamless AI development.
Data Governance Layer: Data lineage tracking, access controls, data quality monitoring, PII/PHI detection, and audit logging. Built for HIPAA, SOC 2, and regulatory compliance requirements.
Analytics and Reporting: Amazon Redshift or Databricks lakehouse for analytics workloads. Pre-built dashboards and self-service analytics capability for business users.
Real-Time Streaming: Event-driven architectures using Amazon Kinesis, MSK (Managed Kafka), and EventBridge for use cases requiring real-time data processing and AI inference.
ENGAGEMENT STRUCTURE:
Weeks 1-2: Discovery, current-state assessment, architecture design, and data source mapping. Weeks 3-6: Pipeline development, governance implementation, testing, and iterative deployment. Weeks 7-8: Production cutover, monitoring setup, documentation, and team training.
WHO THIS IS FOR:
CDOs, VP Data Engineering, CIOs, and data platform leaders at healthcare organizations, insurance companies, financial institutions, and other regulated industries running on AWS. Also ideal for organizations with existing Databricks investments seeking AWS-native integration.
ABOUT KRIV AI:
Kriv AI delivers data and AI solutions for regulated industries. AWS Partner. Databricks Partner. Specialized in healthcare, insurance, and financial services data platforms.
For detailed methodology: https://kriv.ai
Highlights
- End-to-end data platform: data lake, ETL/ELT pipelines, real-time streaming, and AI/ML data preparation on AWS
- Built-in data governance for regulated industries: lineage tracking, PII/PHI detection, audit logging, and compliance controls
- AWS Partner and Databricks Partner -- hybrid lakehouse architectures with medallion layer design
Details
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You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
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Support
Vendor support
PRE-PURCHASE SUPPORT:
Before purchasing, contact Kriv AI for:
- Architecture review and scope assessment
- Data source inventory discussion
- Custom pricing via private offer
- Databricks integration planning
Contact us:
- Email: info@kriv.ai
- Phone: +1-732-433-5564
- Website: https://kriv.ai/contact
Response time: All inquiries answered within 1 business day.
POST-PURCHASE SUPPORT:
After purchase, customers receive:
- Dedicated data engineering lead assigned within 24 hours
- Kickoff call within 3 business days
- Weekly status updates and architecture review sessions
- All source code, configurations, and documentation delivered
- Infrastructure-as-code templates (CloudFormation/Terraform) for reproducibility
- 30-day post-deployment support for pipeline issues and optimization
- Email and phone support (9 AM - 6 PM ET, Monday-Friday)
ONGOING SUPPORT OPTIONS: Managed data operations service available as a separate engagement for ongoing pipeline monitoring, optimization, and data quality management.
REFUND POLICY: Full refund before kickoff. After kickoff, partial refund based on work completed.
Software associated with this service
PointGuard AI's integration with AWS AI (Bedrock, SageMaker) significantly enhances the security and governance of AI applications built on AWS AI (Bedrock, SageMaker). PointGuard AI's solutions provide guardrails and policy enforcement across the entire AI lifecycle, from data ingestion to model deployment. By combining AWS AI's powerful data processing capabilities with PointGuard AI's robust security measures, organizations can accelerate their AI initiatives while maintaining a strong security posture, ensuring that sensitive data and AI models are protected from evolving threats.