Live in two weeks. Fully migrated in eight.
Three ways to move how you work.
Custom-built systems
Own360 coding agents ingest the codebase, extract workflows, dependencies, and operational behaviour, and re-implement the logic inside the matching OwnApp. The most efficient path when source access exists.
Existing SaaS platforms
Browser AI agents observe usage patterns, navigation flows, and process sequences through the UI itself — then the flow is rebuilt inside Own360. No backend access or vendor cooperation required.
Tribal & undocumented
When logic lives in operational practice rather than code, a structured discovery exercise with business, ops, and tech stakeholders maps the process into a migration blueprint.
Replicate, virtualise, or bridge — per system.
Replicate
Sync the dataset into OwnData — real-time or scheduled. Best for heavy AI and analytics workloads; keeps working through source-system outages.
Virtualise
No-copy abstraction layer exposes the source system in place. Built for sensitive datasets, residency constraints, and regulated sources that must not move.
Bridge
Existing REST APIs, middleware, and DB connectors plug into OwnFlow, which syncs data and triggers automations while the estate transitions at its own pace.
Four steps decide the whole path.
01
Map
Existing architecture and its accessibility — code, APIs, databases, people.
02
Choose
Data-movement strategy per system: replicate, virtualise, or bridge.
03
Identify
Integration paths and dependencies across the estate.
04
Sequence
Timeline, risk register, and the compliance plan for cutover.
The output is concrete: a structured migration assessment, target architecture, integration strategy, risk register, and an executable roadmap. Migration done this way preserves institutional intelligence — the workflows, rules, and habits your organisation actually runs on — and moves it onto an AI-native operating layer with full optionality preserved.