Purpose - Built for Regulated Industries.

In-Q Center is an AI-powered regulatory intelligence platform designed to help teams quickly and confidently access, interpret, and work with U.S. regulatory requirements and global standards in a structured, auditable way. The tool is designed to provide action-oriented recommendations for cross-functional teams, helping ensure regulatory and compliance standards are consistently and accurately applied across your supply chain and operations.

n-Q Center is built for FDA- and USDA-regulated industries, including food and beverage, ingredients, flavors and fragrances, dietary supplements, packaging, pet food, and other regulated manufacturing sectors.

Yes. In-Q Center provides citation-backed answers linked to the original regulatory sources and standards to support traceability, verification, and audit readiness.

Yes. Enterprise configurations can include your internal standards, SOPs, policies, customer requirements, approved workflows, and other organization-specific content.

Yes. While the platform’s validated foundation is centered on U.S. regulatory requirements, In-Q Center also provides access to global standards and international regulatory references. The platform allows easy comparisons between regional and country regulations, as well as your internal standards.

In-Q Center reduces manual searching, document creation, review, comparison, and repetitive regulatory interpretation tasks, helping teams respond faster, improve consistency, and make more informed compliance decisions across operations.

No. Customer data is never used to train our AI models. In-Q Center is designed with enterprise security, controlled access, and data privacy in mind.

Yes. Regulatory, Quality, Food Safety, R&D, Procurement, Manufacturing, and other cross-functional teams can all leverage the platform based on their workflows and access permissions.

Innova-Q’s AI model uses clients’ databases that are connected to its system and offers insights, it doesn’t store or modify the data. We follow ISO/IEC 42001 standard that provides an international framework for managing AI-related risks and opportunities through an Artificial Intelligence Management System (AIMS).

1) AI outputs are validated against the real-world code giving a basic level of protection.
2) We have strict guardrails that prevent operations outside of the scope of the application and use case following AIMS. This prevents any illegal actions.
3) We do not authorize our models to make any lasting change in data, without human approval.

1) Internally validated by experts
2) Periodic sampling of customer outputs
3) Customer Feedback

1) Innova-Q System is agnostic of LLM models working underneath them
2) We only work with model providers that offer guarantees around model deprecation and change management
3) This allows for proper time for validation

Every question, model outputs, tool calls and executions are meticulously logged. Performance is monitored continuously through a mix of automations and periodic human reviews.

1) All users can escalate mistakes made by AI.
2) AI provides confidence scores on its answer that makes user aware of their reliability of the answer, the confidence score is calculated based on automation and analysis of the AI call and outputs, the confidence score on outputs is another way to look out potential hallucinations.

Every question, model outputs, tool calls and executions are meticulously logged. Performance is monitored continuously through a mix of automations and periodic human reviews.

1) for internal development, Technical teams must test and validate the new models before launch.
2) For all of our clients, the UI always guides the user to human approval whenever a lasting change is going to be made.

1) AI is pretrained in industry data, and strict code of around its values, answerable and unanswerable questions.
2) Strict guardrails against explicit contents.
3) AI is purely restricted to scope of the application, preventing it from answering generic questions.
4) Strict security and access to data is restricted by the user roles and privileges, preventing any leakage of data.