Trust Center

Enterprise trust, security & responsible AI at OMS Organization.

This page is maintained by MD Mahadi Hasan and the OMS Organization team as a transparent view of how our platform, AI systems, and operations are designed, governed, and continuously improved.

Not an audit or certification. The statements below describe design principles and current engineering practice inside the OMS Organization ecosystem. They are not independent audit findings. Formal certifications, compliance attestations, and third-party security audits are pursued progressively and will be published here only after they are officially completed.

Core principles

Five commitments that shape every OMS system.

Shared responsibility: OMS Organization owns platform and product controls, while customers and operators remain responsible for the data they submit, the users they invite, and the workflows they configure.

Security-First AI Development

OMS follows security-first AI development practices — security requirements are defined before the first line of code, not retrofitted after launch.

Threat modelling reviewed for every new AI capability and integration.
Secure-by-default configurations across all OMS surfaces.
Continuous dependency, secret, and configuration scanning during development.
Least-privilege access for staff, agents, and third-party integrations.

Responsible AI Principles

Responsible AI principles guide all AI systems inside the OMS ecosystem — from Mother AI orchestration to specialised agents.

AI systems are designed to augment humans, not replace human judgement.
Grounded responses limited to knowledge the system has explicitly been given.
No autonomous financial, legal, or medical advice.
Guardrails against prompt injection, data exfiltration, and unsafe tool use.

Data Privacy & Access Control

Data privacy and access control are treated as core design requirements, not optional add-ons.

Purpose-limited data collection tied to explicit product functionality.
Encryption in transit (TLS) for every request to OMS surfaces.
Encryption at rest for managed databases and object storage.
Row-level security and role-based access controls on multi-tenant data.

Governance, Auditability & Human Oversight

All AI workflows are designed with governance, auditability, and human oversight built into the pipeline.

Every AI agent operates under a documented policy and capability boundary.
High-impact or irreversible actions require human-in-the-loop review.
Sensitive actions produce an append-only audit trail (who did what, when).
Model, prompt, and tool changes are tracked with version history.

Enterprise Security Architecture

OMS enterprise security architecture is continuously improved — hardened, reviewed, and iterated as the platform matures.

Managed cloud infrastructure with patched, hardened baselines.
Secrets held in a managed secret store — never committed to source control.
Segregated environments for development, staging, and production.
Incident response coordinated by the OMS founder and engineering team.

Transparency register

Certifications, compliance, audits & subprocessors.

These sections are maintained as an editable register by the OMS Organization team. Content is added here only after items are officially verified, contracted, or completed — never speculated.

In progress

Certifications

Formal third-party certifications are pursued progressively as the platform matures. Earned certifications will be listed here with issuing body, scope, and validity dates. No certification is claimed until officially awarded.