Data-flow map
Sources, processing steps, model endpoints, storage locations, exports, and reviewer touchpoints for the selected workflow.
Security & Governance
Security is the architecture, not a feature.
We design AI systems for sensitive environments around an explicit customer-approved boundary: on-premise, customer cloud, tenant-isolated managed service, regional deployment, or a documented combination with approved external model services.
01
Private Deployment
We scope the application, storage, retrieval, and model-service boundary for your VPC, on-premise hardware, or dedicated single-tenant environment where appropriate. An on-premise application can still use an approved external model service; that path is documented before sensitive material is connected.
02
Strict Access Controls (RBAC)
AI should only see what the user is authorized to see. Workflows are designed around row-level security, role-based access, least privilege, and reviewer permissions before answering sensitive queries.
03
Audit Trails
Data extraction, natural-language queries, reviewer edits, and approvals can be logged so compliance teams can inspect how important outputs were produced.
04
Data Discovery & Masking
We implement readiness workflows to discover, classify, and mask sensitive data before approved material reaches an AI model for processing.
Security review pack
Give InfoSec the artifacts they need before sensitive data moves.
A workflow pilot should be reviewable before it is connected to confidential files. We prepare the operating and security details around the specific workflow being tested.
Access model
Named user groups, roles, least-privilege rules, source permissions, reviewer permissions, and audit responsibilities.
Model and provider boundary
Approved model endpoints, data-sharing assumptions, retention settings, logging scope, and client-owned infrastructure options.
Pilot control checklist
NDA/DPA path, sample-data approach, deletion rules, approval checkpoints, incident contacts, and rollout decision criteria.
Procurement Readiness
Questions your InfoSec team will ask before a pilot.
Your team should not have to guess how an AI workflow touches confidential data. We clarify the deployment boundary, data flow, access model, retention, and reviewer controls before engineering work begins.
Where does client data run?
Deployment is scoped around the client's security boundary: client VPC, on-premise, or dedicated single-tenant cloud where appropriate. The final model, storage, and integration path is agreed before sensitive material is shared.
Do client files train public models?
We use only customer-approved model endpoints and provider configurations. Training, retention, residency, and logging terms are verified for the selected provider and recorded in the engagement's data-flow and security design before confidential material is connected.
What can we review before a pilot?
We can provide the proposed data-flow map, model/provider list, access-control design, logging and retention approach, deployment responsibility matrix, and review checkpoints for the selected workflow.
How do you handle retention and logging?
Retention, export, audit logging, and deletion are defined per engagement. For sensitive workflows, we prefer client-owned storage, minimal retained payloads, and logs that preserve traceability without exposing more content than necessary.
Can this use our identity and access controls?
Where the environment allows it, workflows are designed around client IdP, role-based access, least privilege, and audit trails so users only see the sources and outputs they are authorized to review.
What happens before legal and InfoSec approval?
We can work from sanitized examples during discovery, execute an NDA before sensitive review, and support DPA or security addendum discussions as part of contracting.
Does Dotnitron hold SOC 2 or ISO certification?
Not currently. Dotnitron does not claim SOC 2, ISO 27001, or ISO 42001 certification. We apply project-level security and responsible-AI controls, document the customer-approved architecture, and provide evidence for the customer's own review; these practices are not an independent organization-wide certification.
Technology partnership
Build with an OpenAI Select Partner.
Recognized by OpenAI for helping organizations build, deploy, and scale AI solutions.Have something in mind?