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This Government Contract opportunity from The Judicial Branch was posted on May 4, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

AI-Assisted Transcription Drafting (Internal LLM Operations)

Closed
Federal

Contract Overview

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The contract involves the development and operation of an internal large language model (LLM) system designed to generate initial transcription drafts while maintaining stringent data security protocols. This system ensures that sensitive audio data is never exposed to external AI platforms, effectively protecting confidential information throughout the transcription process. The initiative aligns with the need for secure and efficient transcription services within the judicial sector. Issued by the Judicial Branch's Procurement Management Division, this subcontract opportunity, classified under NAICS code 541512, focuses on IT services related to custom computer programming. The work is to be performed in Washington, DC, with proposals due by May 18, 2026. The contract emphasizes the importance of internal processing capabilities to balance technological innovation with the protection of sensitive judicial audio data.

General Info

Development and operation of a secure internal LLM for confidential judicial transcription services.

Agency

The Judicial Branch → Aousc-procurement Management Division

NAICS

541512 - Computer Systems Design Services View NAICS

Place of Performance

Washington, DC, 20544, USA

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyThe Judicial Branch → Aousc-procurement Management Division
ContactsNo contacts available
OfficeN/A
Organization / Agency
The Judicial Branch → Aousc-procurement Management Division
Office AddressN/A
ContactsNo contact information available

Full Description

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Develop and operate an internal LLM system to generate initial transcription drafts without exposing sensitive audio to external AI platforms, ensuring full data security.