A governed approach to ingestion, modeling, quality, cataloging, lineage, and vectorization—so AI, analytics, and automation run on trusted data.
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Legacy-to-Agentic Transformation builds the foundation for AI. We standardize ingestion, cleaning, and modeling; enforce data contracts; and maintain a live catalog with lineage. Pipelines produce trusted tables and vector indexes so RAG, analytics, and workflows run on accurate, current, and governed data.
We profile sources, map schemas, and define contracts/SLOs for freshness and quality. ELT/CDC moves data into your lake/warehouse; dbt-style transforms apply rules and PII handling. Metadata, lineage, and tests run continuously. Vectorization adds embeddings and filters for governed retrieval.
A production thin slice: domain data products, curated marts, and vector stores; a searchable catalog with owners; quality and cost dashboards; and runbooks. Adapters connect apps, files, and APIs; SDKs expose data to products, analytics, and agentic platforms with clear SLAs.
Privacy-by-design with RBAC/ABAC, encryption, masking/tokenization, retention rules, and audit logs. Policies are codified and tested. We align to enterprise frameworks (SOC 2/ISO 27001, GDPR/CPRA, and HIPAA where applicable) without claiming certification on your behalf.
A governed approach to ingestion, modeling, quality, cataloging, lineage, and vectorization—so AI, analytics, and automation run on trusted data.
Not to start. We work with your stack (cloud DBs, lakes, warehouses) and add adapters; no rewrite required.
Detection, masking/tokenization, consent tracking, least-privilege access, and audit logs—validated by policy-as-code tests.
Yes—vector pipelines and governed content improve accuracy, traceability, and freshness for retrieval-augmented generation and agent tools.
Two weeks for an assessment and data contract plan; 8–12 weeks for a production thin slice with catalog, tests, and dashboards.
Snowflake/BigQuery/Databricks, dbt, Airflow/Dagster, Kafka, Lakehouse tables (Delta/Iceberg/Hudi), Postgres, OpenSearch, and vector DBs (pgvector, Pinecone, Weaviate) — plus DataHub/Amundsen for cataloging.
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