Data engineering and analytics for enterprise systems

DNA Solutions builds data platforms that consolidate existing sources for reporting and analysis. Work can include migration, data pipelines, validation and dashboards. We start with the systems already in place and the questions your teams need to answer, then select the architecture and tools around those requirements.

We define the comparisons with your team, check source and target outputs and investigate discrepancies. Validation can cover records, transformations and business totals. These checks inform corrections and the decision to switch over. We also agree how the team will monitor data quality after the migration.

We implement vector databases for semantic search and retrieval over enterprise documents and operational data, often alongside our AI/ML engagements. This lets your teams query unstructured content by meaning rather than exact keywords, and it provides the retrieval layer that AI assistants need to answer from your own governed data instead of generic sources. We embed your documents and records, store the vectors next to the structured data already in the platform, and wire the retrieval into the applications that consume it. Because the vector layer sits inside the same governed environment, access control and lineage apply to it the same way they apply to the rest of your data. In practice this is what lets an internal assistant cite a real contract, ticket or report rather than a plausible guess.

We clarify access requirements, data ownership and the controls needed for your reporting environment. Documentation explains the sources, transformations and operating procedures. We review these with your engineers so they can maintain the platform and assess the impact of later changes.