Enterprise Security For Governed AI Operations

Security Overview

ThinkNEO is designed to help enterprises govern AI usage without unnecessary data exposure. Our security posture includes tenant-aware isolation, role-based access controls, immutable auditability, configurable governance metadata retention, and security documentation available upon request. ThinkNEO does not train models on customer usage. Our platform is built to support enterprise governance, operational accountability, and reviewable security controls across AI workflows.

Security Architecture

ThinkNEO's architecture is designed around tenant-aware boundaries, governed runtime execution, and observable control paths. The platform applies layered controls across workspace isolation, governed provider routing, policy enforcement, and reviewable event records. We follow a defense-in-depth approach intended to reduce unnecessary exposure, strengthen operational traceability, and support enterprise deployment requirements across sensitive AI workflows.

Encryption & Key Management

ThinkNEO uses encryption to protect data in transit and at rest. Sensitive credentials and provider API keys are handled through controlled storage and access protections designed to reduce operational risk. Our security program includes ongoing review of data flows, storage boundaries, and credential-handling practices to ensure that protection mechanisms remain appropriate to the sensitivity and use of the data involved.

Access Control

Access to systems and administrative functions is limited based on business need and role-based responsibilities. ThinkNEO supports role-based access control at the role and workspace level, with architecture prepared for enterprise identity and access integrations. We are formalizing access governance procedures to support least-privilege access, credential hygiene, privileged access review, and stronger onboarding and offboarding controls as the program matures.

Runtime Security

ThinkNEO is built for live AI execution environments, where security controls must operate during prompts, retrieval, model output, tool use, and downstream actions. Runtime guardrails are designed to reduce unsafe behavior before it reaches models, tools, or operational systems. Current runtime security capabilities include:

• Prompt injection defense with context integrity checks
• Jailbreak defense with risk-aware control paths
• Secret leakage prevention for credentials, tokens, keys, and sensitive identifiers
• Exfiltration prevention for outbound tool actions and response payloads
• Per-request and per-session risk scoring to support escalation and incident handling

Data Handling, Retention & Boundaries

ThinkNEO applies policy-aware controls to sensitive business context across prompts, retrieval context, generated outputs, and governed actions. Our program is designed to reduce oversharing risk, improve data visibility, and support operationally enforceable controls for sensitive AI use cases. Retention of governance metadata is configurable per tenant. Policy design also supports boundary-aware routing, destination-aware controls, and residency-sensitive governance requirements. Current platform capabilities include:

• Context-aware classification for sensitive business data
• Masking, tokenization, and redaction controls
• AI-specific DLP policies across prompts, retrieval chunks, outputs, and action payloads
• Data residency and boundary policy support by tenant, workspace, model path, and operational region
• Data lineage visibility from source context through prompt, output, and governed action

Logging, Auditability & Monitoring

ThinkNEO is designed to provide security and compliance teams with reviewable records and operational evidence across AI activity. We maintain immutable per-request event history to support audits and investigations, structured governance records for compliance workflows, and SIEM-ready export pathways for enterprise monitoring and incident response. This evidence-oriented design helps support policy review, anomaly investigation, risk escalation, and security operations across governed AI environments.

• Immutable per-request event history
• Exportable audit reports and evidence trails
• SIEM-ready monitoring and incident response exports
• Lineage visibility for governed AI actions

Subprocessors

ThinkNEO works with a limited set of infrastructure and service providers required to operate the platform. These providers are reviewed based on operational necessity, security considerations, and service reliability.

• Subprocessor details are available upon request through customer documentation.
• We publish and refine subprocessor disclosure as the trust program evolves.

Audit & Compliance Status

ThinkNEO is actively maturing its security and compliance program through control formalization, governance documentation, and readiness work aligned with recognized frameworks. Current status:

• Security program: In progress
• ISO/IEC 27001 controls: Alignment underway
• SOC 2 readiness: Underway
• Security documentation: Available upon request
• We do not claim completed certifications or attestations before they are formally achieved.

Security Contact

For security questions, customer due diligence requests, or responsible disclosure inquiries, contact:

security@thinkneo.ai

Request Security Review

Run a security and trust review with ThinkNEO to align architecture, controls, and enterprise due diligence requirements.