FERZ, Inc. supports the GSA's effort to establish a baseline for safeguarding Government Data in LLM systems and offers thirteen targeted recommendations to improve the draft clause. The company argues that the clause should better distinguish between evidence of process (like monitoring and traceability) and evidence of pre-execution authorization for "consequential actions."

The Cyber Strategy Institute, a small business specializing in AI governance, supports the proposed GSAR clause 552.239-7001 but provides detailed technical recommendations to improve its implementation. They argue for role-scoped flowdowns, autonomy-based proportionality, and clearer measurement standards for unbiased AI principles.

Distributed Solutions, Inc. (DSI) supports the GSA's objective of protecting Government Data within LLM systems but argues for specific clarifications to the proposed GSAR clause. They advocate for distinguishing between improvements to acquisition applications (like workflow automation and RPA) and improvements to the underlying LLM to avoid unnecessary compliance burdens on non-AI-centric systems.

DAY1044 Solutions, a small business cybersecurity and AI consulting firm, supports the proposed GSAR clause regarding data safeguarding in LLMs. They recommend specific revisions to ensure that compliance obligations are realistically achievable for small businesses, specifically by aligning requirements with the roles of system integrators and commercial market standards.

Trilogy Innovations, Inc., an SBA 8(a)-certified federal IT small business, supports the core objectives of the proposed GSAR clause regarding the safeguarding of data within LLM systems. However, they argue for specific revisions to address technical infeasibilities (such as data deletion from fine-tuned models), clarify incident notification timelines for supply chains, and reduce the administrative burden on small businesses through consolidated compliance paths.

Krishna Chaitanya Balusu, an individual contributor to OpenTelemetry and an IEEE Senior Member, supports the core objectives of the proposed GSAR clause 552.239-7001. He argues that the clause should be strengthened by requiring structured, machine-readable telemetry (specifically referencing OpenTelemetry GenAI semantic conventions) to ensure audit trails are verifiable, portable, and consistent across the AI supply chain.