Migration that runs where your data lives
An AI-native migration system for regulated enterprises, deployed air-gapped in your own estate. Legacy books moved in weeks, not months.
- Ingest
- Filter
- Transform
- Reconcile
- Load
- 8 weeks
- Typical migration timeframe on the ZILO™ Migrate platform, against a nine-month programme run the traditional way.
- 100,000s
- Of data points the agent harness has been optimised across, covering large books and complex migration scenarios.
- End to end
- Ingestion to load in one closed loop, so there is no artefact for your team to execute and no separate ETL track beside it.
- Local model
- A small, fine-tuned migration model with the power of the frontier, running on-prem inside an air-gapped deployment. Nothing leaves your estate.
What sets ZILO™ Migrate apart
Built the way regulated firms actually run migrations
Most tools stop at generating a mapping and hand the trials, the reconciliation and the risk back to you. ZILO™ Migrate runs the whole loop, inside your perimeter, with your people in control.
Built for regulated enterprises
Migration data is the most sensitive copy of your book that will ever exist. The platform and its model deploy air-gapped inside your estate, and nothing leaves.
- Air-gapped deployment, always
- The model runs on-prem, not in the cloud
- Details on the Security page
One closed loop, end to end
Ingestion, filtering, transformation, reconciliation and load run as one governed process. No hand-off to a separate ETL team, no shadow SQL track beside it.
- Ingest to load in one platform
- Trials and reconciliation on every change
- Lineage and a written reason on every mapping
Autonomous, never unattended
The agent tests its own work and brings your people the evidence. Named owners verify and sign off at every gate, and nothing loads without them.
- Human sign-off at every gate
- Full audit trail and version history
- Rollback at every layer
Source and target agnostic
Trained on the patterns of migration work, not on your data. It carries no assumptions about the source system, the target system or the domain.
- Any source, any target, any schema
- Proprietary and industry-standard formats
- Reinforcement-learned on migration tasks
How it works
One closed loop, from connection to load
Six stages run in order on the harness, and every record that moves writes to the lineage ledger. The results of each run feed the next, so the loop tightens until the book is ready to go live.
Autonomy
Most tools stop at generation
AI that cannot verify its own outputs has its capability capped. ZILO™ Migrate's air-gapped solution gives the specialised agent harness a secure environment to trial its work, reconcile against its objectives, and achieve complex, long-horizon data migration goals.
Autonomous is not unattended. Named people verify the evidence and sign off at every gate, and nothing loads without them.
Where generation tools leave the run to you, the harness does the work and brings you the evidence.
Platform
Built for large books and complex scenarios
Enterprise controls are not an add-on. Governance, lineage, tenancy and access control are how the platform works, on a small book and on a full-scale migration alike.
Source and target agnostic
The mapping model carries no assumptions about the source system, the target system or the domain. Trained on patterns, not data.
Controls and sign-off
Define natural language rules and controls, and let the agent decide how to verify them.
Lineage, audit and rollback
Full audit trails and version history, with clean data lineage from source through transformation to target. Information is never lost, and every layer supports rollback.
A lifecycle, not one event
Migrations run as a sequence: phased data offloads, dress rehearsals, then a clean live migration, all against the same project and the same rules.
Multi-tenant by design
Run migrations for every client on one deployment, with clean data segregation between tenants and per-client management and control.
RBAC down to the agents
Role-based access control applies to people and to agents alike. An agent holds a role and permissions the same way a person does, so you set what it can touch.