Multi-source ingest & enrichment pipeline
Excel, calendar, mail, and public-fact merge consolidating into a clean relational store with enrichment and CRM-ready seed tables — the playbook applied to your own legacy data.
SVC // 05
Database Conversion & AI-Native Management
We modernize legacy databases into AI-friendly stores — enriched metadata, embedding-aware schemas, semantic indexes, and the boring-but-essential migration discipline that makes the cutover safe. Plus straightforward database management and cross-engine transfers when that's what's actually needed.
▌▌▌ WHAT WE DELIVER ▐▐▐
DELIVERABLES
Data your models can actually use.
- // SCHEMA AUDIT Inventory, profile, and document what you actually have today — types, cardinality, gaps, and the undocumented constraints holding the system together.
- // AI-NATIVE CONVERSION Re-shape into AI-friendly storage — vector columns, embedding pipelines, semantic indexes, and metadata layers tuned to retrieval and reasoning workloads.
- // METADATA ENRICHMENT Generated descriptors, provenance, lineage, quality flags, and entity links so both models and humans can reason confidently over the data.
- // MIGRATION RUNBOOK Dual-write, shadow-read, cutover plan, and rollback story — with property-based tests that prove zero data loss before anyone flips the switch.
- // ETL & CROSS-ENGINE TRANSFER Postgres, MySQL, MS SQL, Oracle, SQLite, DuckDB, object storage — moved cleanly, with CDC and ongoing sync where it's required.
- // ONGOING MANAGEMENT Backups, restore drills, observability, query-plan hygiene, and a maintenance posture your team can actually keep up with.
▌▌▌ REPRESENTATIVE ENGAGEMENTS ▐▐▐
DOSSIER
Selected work — redacted.
Geospatial relational data plane
Postgres + PostGIS data plane built for national-market ingestion, search, and partner integrations — schemas engineered for the queries the product actually runs.
▌▌▌ HOW WE WORK ▐▐▐
PROCESS
Audit. Convert. Operate.
- // 01 AUDIT Profile the current store, document the contract you didn't know you were keeping, and pick the target shape against the workloads that actually matter.
- // 02 CONVERT Build the new schema, the enrichment pipeline, and the migration plumbing. Shadow-run against production before you cut over.
- // 03 OPERATE Execute the cutover, observe, and stand up backup, restore drills, and a maintenance routine your team owns.