Deployment control
Run locally, in a private cloud or in an air-gapped environment according to the customer’s architecture.
CONTROL BEFORE SENSITIVE CONTENT TRAVELS
Reduce sensitive-data exposure before unstructured content leaves the approved workflow.
Keep processing inside the enterprise environment, apply explicit policy and retain evidence of what was detected, reviewed and removed.
SENSITIVE SOURCE
↓ POLICY
CONTROLLED OUTPUT
For Security & Privacy
Move from a promising demo to a measurable workflow.
The model is only one component. Reliable enterprise outcomes require representative inputs, explicit expected behavior and evidence when something changes.
Reviewable policy
Define enabled entities, confidence thresholds, exclusions and manual review before final output.
Audit evidence
Record actors, timestamps, detected regions and input/output hashes for the transformation workflow.
Questions your data should answer
Make success observable before production.
- 01Where does processing happen?
- 02Who approved the output?
- 03What was removed and why?
- 04Can the result be verified independently?
Product fit
A clean division of work.
Use real examples only when they are necessary. Use synthetic scenarios to scale coverage and repeatability.
01GritRedactCONTROLLED REAL DATA
Enforce and evidence the approved transformation policy.
Detect, review, remove and verify sensitive information according to a defined downstream purpose.
- Policy-driven
- On-premise
- Auditable
02GritRenderSYNTHETIC EVALUATION
Reduce the need to distribute real identities into test environments.
Generate realistic documents, images and audio with labels, expected results and controllable variation.
- Known ground truth
- Edge-case coverage
- Repeatable runs
Start with the blocked workflow
Make sensitive content usable—on terms your enterprise can defend.
Show us the source content, workflow and downstream users. We’ll identify where redaction, synthetic data or a different control is actually appropriate.
Request a working session ↗