Direct answer

What are the main delivery risks when undertaking LLM fine-tuning projects in India?

The main delivery risks include extended delays during data preparation and annotation (which can take 3-4x longer than expected), production deployment challenges where models fail basic sanity checks in staging, and handover complications where the partner's environment is incompatible with your production DevOps and security setup. Additionally, there's the risk of prohibitive inference costs or latency being discovered too late in the process.

26 Feb 2026
ai_solutions

Short answer

The main delivery risks include extended delays during data preparation and annotation (which can take 3-4x longer than expected), production deployment challenges where models fail basic sanity checks in staging, and handover complications where the partner's environment is incompatible with your production DevOps and security setup. Additionally, there's the risk of prohibitive inference costs or latency being discovered too late in the process.

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What are the main delivery risks when undertaking LLM fine-tuning projects in India?

The main delivery risks include extended delays during data preparation and annotation (which can take 3-4x longer than expected), production deployment challenges where models fail basic sanity checks in staging, and handover complications where the partner's environment is incompatible with your production DevOps and security setup. Additionally, there's the risk of prohibitive inference costs or latency being discovered too late in the process.

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