When a hyperscaler is training the next model behind a search experience, the ground-truth data has to land fast, and it has to land right.

Overview

A Global Hyperscaler needed prompt-and-response content across five categories ” audio, multimodal, instruction, reasoning, and coding, generated, evaluated, and ranked at production volume on a three-week clock.

Firstsource delivered 20,000+ prompts and responses run by 100+ subject-matter experts across the US and India.

This was Intelligence That Operates: SFT/CoT training data and human preference signals delivered on a release cadence, not a research cadence.

Challenges

• A three-week window for 20,000+ prompts collapses if the SMEs aren't ready. Coding, ideal-response prompts, and multimodal generation each need credentialed authors. A pool that's not pre-vetted can't move on a hyperscaler's timeline.
• Five content categories share no single workflow. Audio speech transcription, code generation, response ranking, and prompt-response writing each need different rubrics, validation logic, and review paths.
• A 0% error tolerance leaves no room for downstream cleanup. Production-grade ground-truth data going into a foundation model can't be patched after delivery ” accuracy and quality discipline have to hold at the point of authoring.

How We Made It Happen

We deployed credentialed SMEs and one quality discipline across all five categories on a single operating cadence.

• 100+ SMEs vetted across all five categories. Authors and reviewers credentialed for audio, multimodal, instruction, reasoning, and coding work ” were deployed in parallel.
• SFT/CoT Demonstration Data plus Expert Preference (RLHF) in one program. Prompt-response generation, response ranking, and model-output evaluation ran together rather than as sequential vendor handoffs.
• One quality bar, US + India delivery. Authoring and review carried a single quality discipline across both regions, with continuous oversight rather than batch QC at the end.

Conclusion

Hyperscalers don't slow their model releases for data programs that can't keep up. Firstsource delivered training data, evaluation signals, and zero-error quality on a release cadence, turning prompt engineering into Intelligence That Operates.