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The Problem

Developing against real data is hard. The common approaches all have significant drawbacks:
  • Seed data — Stale, incomplete, doesn’t reflect production edge cases. Maintaining seeds is a constant tax.
  • Staging databases — Expensive, drift from production, shared across the team (your changes break someone else’s test).
  • Database snapshots — Large, slow to restore, consume storage. Not practical for quick iteration.
  • Mocking — Doesn’t catch real query bugs, schema mismatches, or performance issues.
For AI agents, the problem is worse. Agents need to explore database schemas, run diagnostic queries, and test mutations — all against real data. Giving an agent write access to production is dangerous. Giving it a stale seed database produces poor results. More importantly, the pace of development post AI is accelerating rapidly. We used to modify core tables maybe once a month after three levels of review. Now we’re modifying them multiple times a day. We urgently need better environments for testing.

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The Solution

Mori gives every developer and AI agent a virtual copy of the production database. Reads return real production data. Writes are captured locally. Reset is instant. No data copying. No snapshot management. No staging infrastructure. Just swap a connection string.