Secure ETL and ELT pipelines for AI readiness with encryption in transit and at rest, data lineage tracking, and audit compliance. Our data infrastructure enables production AI systems while maintaining regulatory compliance and complete data sovereignty for regulated industries.
AI-ready data infrastructure with enterprise-grade security and compliance controls.
Scalable data pipelines for AI workloads using Apache Airflow, dbt, and custom orchestration. Batch and streaming architectures. Incremental processing with change data capture. Error handling and retry logic with full observability.
Automated document processing and chunking strategies. Embedding generation with batching optimization. Vector database integration (Qdrant, Milvus, pgvectorscale). Incremental refresh with drift monitoring and alerting.
Schema validation and data contract enforcement. Anomaly detection with automated alerting. Data profiling and statistical quality checks. Lineage tracking for audit compliance and debugging.
Encryption in transit (TLS 1.3) and at rest (AES-256). PII detection, redaction, and tokenisation pipelines. Column-level masking and role-based data access. Secure API integrations with credential management.
Data lineage tracking with full provenance. Retention policies with automated secure deletion. GDPR compliance including right-to-erasure automation. Audit logging with tamper-evident storage.
Secure ETL and ELT pipelines that transform enterprise data into AI-ready systems with full compliance and observability.
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flowchart LR
subgraph Sources["Data Sources"]
A1[Enterprise Databases]
A2[APIs & Streams]
A3[Files & Documents]
end
subgraph Ingest["Secure Ingestion"]
B1[Encrypted Connectors]
B2[Data Validation]
B3[Change Detection]
end
subgraph Processing["ETL / ELT Processing"]
C1[Transform & Clean]
C2[Embeddings]
C3[Quality Checks]
end
subgraph Storage["AI-Ready Storage"]
D1[Data Warehouse]
D2[Vector Database]
D3[Secure Lake]
end
subgraph Apps["AI Applications"]
E1[Model Training]
E2[Real-time Inference]
E3[RAG Search]
end
A1 --> B1
A2 --> B1
A3 --> B1
B1 --> C1
B2 --> C1
B3 --> C1
C1 --> D1
C2 --> D2
C3 --> D1
D1 --> E1
D2 --> E3
D3 --> E1
D1 --> E2
Layout-aware extraction for contracts, policies, and regulatory filings. OCR integration for scanned documents. Metadata extraction and classification. Format conversion and normalisation.
Qdrant, Milvus, and pgvector deployment and optimization. Index configuration for latency and recall targets. Hybrid search with dense and sparse embeddings. Incremental updates with consistency guarantees.
Event-driven architectures with Kafka and cloud-native alternatives. Stream processing for real-time AI features. Change data capture for database synchronisation. Low-latency pipelines for inference workloads.
Column-level lineage, PII redaction at ingest, GDPR Article 28 processor posture, HSM-managed key material. Retention policies enforced as code, not policy alone.
Airflow, Dask and PostgreSQL with column-level encryption, tamper-evident audit logs, 7-year retention. Manual effort down 60%, 99.9% pipeline reliability, 100% audit coverage.
Read the case →30-minute call. Engineering discovery memo within five working days.