Turn SaaS Data Into an AI-Ready Database
Use SPIRITT to lift data out of cloud apps, preserve its context, and keep a governed database ready for analytics, automation, and AI.
What you can do
Move the operational data trapped inside SaaS products into a database your organization controls, without reducing it to a pile of CSV files.
SPIRITT can own the full Data Lift:
- connect to business apps, APIs, files, and internal systems
- discover the live schemas instead of relying on a stale field list
- preserve record relationships, property history, archive state, and source context
- normalize the parts people query while retaining raw source payloads for fidelity
- classify every source surface as complete, unavailable, or needing attention
- deliver a one-time migration or a recurring, hands-off refresh
- add a secure viewer, backups, search, analytics, and downstream AI workflows
Why this is more than an export
A normal export captures whatever fits in a flat file at one moment. It commonly loses associations, custom objects, value history, lifecycle state, and data that lives behind separate product APIs.
A Data Lift treats the source as a connected system. SPIRITT inspects how records relate, follows pagination to its real terminal state, reconciles later scans, and records explicit coverage evidence. The destination becomes a trustworthy operational data layer rather than another copy nobody knows how to validate.
Proof: from a cloud app to a governed data vault
Inside SPIRITT, we applied this pattern to our own customer platform and built an independent, organization-internal PostgreSQL mirror. Our agent moved millions of records, relationship edges, history entries, and supporting resources while discovering the evolving object graph, preserving mutable history, reconstructing directional associations, and adding a read-only data browser.
It also implemented organization-based authentication, persistent storage, recurring refreshes, lifecycle reconciliation, and verified backups. The final isolated reconciliation accounted for 100% of the source surfaces the platform makes enumerable. Features unavailable to that account were recorded as explicit exclusions instead of being hidden as apparent success.
What becomes possible next
Once the data lives in a governed database, every follow-on project starts further ahead.
SPIRITT can build cross-system dashboards, semantic search, retrieval for agents, anomaly monitors, revenue models, customer timelines, scheduled reports, or controlled reverse syncs. New AI products query the data layer directly instead of rebuilding source integrations every time.
The database becomes durable organizational infrastructure. The agent keeps the connections, schema handling, coverage checks, and refresh jobs working as the source systems change.