Solutions
Data control & residency
Verify where data goes before it goes there.
Vendor training policies are a runtime condition, not a contract you can file. Defaults change, retention obligations arrive by court order, and de-identification is not anonymization. Orcher checks the destination's posture on every call, before the payload leaves.
The problem
- A single vendor default change swept roughly 300,000 organizations into training by default.
- Sensitive data now makes up a third of enterprise AI traffic.
- Residency commitments are asserted at the contract layer and unverified at runtime.
The Orcher approach
- Classify the payload, verify the destination, then route — in that order, every time.
- Block or re-route automatically when a provider's posture stops satisfying policy.
- Record the data-control verdict beside the action it governed.
Vendor posture is a runtime condition, not a contract
Most data-protection programmes treat provider terms as a procurement artifact: reviewed at onboarding, filed, and revisited annually. Agentic execution breaks that assumption. A default training setting, retention window, or processing region can change between one call and the next, and a single such change in August 2026 affected roughly 300,000 organizations at once.
If your control is a signed contract, you learn about the change from the press. If your control runs at call time, the routing decision simply changes and the verdict is recorded.
Classification, destination, verdict
The Data Control Gateway classifies every outbound payload — regulated personal data, protected health information, privileged material, trade secrets, unrestricted — and evaluates the candidate destination's live posture: training exclusion, retention, processing region, sub-processor chain.
It then permits, re-routes, or blocks. When posture cannot be verified, it fails closed. The verdict is attached to the execution record, so the question of where a specific payload went, under which policy, is answerable per call rather than per quarter.
De-identification is not a control
Treating de-identified data as anonymous is the most common way sensitive material ends up in a training corpus. Re-identification risk does not disappear because a name was stripped, and the obligations attaching to the underlying population do not lapse.
Orcher's position is that classification plus destination control is the control. De-identification is a useful additional measure and a poor substitute for one.
Rollout
How a deployment actually starts
One workflow, proven end to end, before anything scales.
01
Classify the estate
Map the payload classes your agentic work touches and the obligations attached to each.
02
Declare permitted destinations
For each class, define acceptable providers, regions, training postures, and retention windows.
03
Turn on fail-closed routing
Route through the gateway with block-on-unverified semantics, and confirm re-routing behaves as intended.
04
Rehearse the enquiry
Answer a mock data-protection enquiry from the ledger to confirm per-call verdicts are complete before scaling.
What you get
Per-call residency proof
Every call carries a recorded verdict naming the destination, region, and policy in force at the time.
Policy changes absorbed
A provider changing its defaults changes a routing decision, not your compliance posture.
Fail-closed by default
Unverifiable posture blocks or re-routes rather than proceeding on assumption.
Questions
What enterprises ask first
- Does this stop us using frontier models?
- Only for payloads whose classification forbids that destination. Unrestricted work continues to route wherever cost governance prefers.
- How do you know a provider's current posture?
- Posture is treated as a runtime input that is refreshed and re-checked, never cached as trusted. Where it cannot be verified, the gateway blocks.
- Is this a replacement for DLP?
- No. DLP inspects content leaving the network. The gateway governs which model, operated by whom, in which jurisdiction, under which training policy, may see that content at all.
Most often bought for
Industries running this, and the components behind it
Derived from the Orcher components this solution engages.
Use case
Manufacturing
Physical consequence closes the loop on digital authority.
Use case
Telecommunications
Network authority at carrier scale.
Use case
Energy & Utilities
Reliability standards do not recognize autonomous intent.
Use case
Healthcare
Named directives and liability boundaries for this industry.
Use case
Government & Public Sector
Named directives and liability boundaries for this industry.
Use case
Life Sciences & Pharma
Named directives and liability boundaries for this industry.
Proof
Measured, sourced, and cited
10.7% → 34.8%
growth in the sensitive share of enterprise AI traffic
Vol. I, p.24
410M
DLP violations across enterprise AI channels
Vol. I, p.24
93%
of surveyed programs could not verify training exclusion at runtime
Vol. I, p.24
Components engaged
How Orcher delivers it
Bring a directive. We will show you the cycle.
Briefings walk one of your real workflows through the seven components end to end.