Service Details
AI Model Finetuning & Performance Optimizations
Finetuning large language, speech recognition, and text-to-speech models for domain-specific and multilingual production use cases. This includes adaptation to new languages, dialects, and accents, with a strong focus on improving accuracy, robustness, and inference efficiency under real-world constraints.
What You Get
Domain & Language-Specific Model Adaptation
Finetuning LLM, ASR, and TTS models for specialized domains, as well as new languages, regional dialects, and accent variations to improve linguistic coverage and real-world usability.
Inference & Latency Optimization
Task- and language-aware evaluation using appropriate metrics to validate accuracy gains across domains, languages, and acoustic conditions.
Production-Ready Model Artifacts
Clean, documented model checkpoints and configurations, ready for integration into downstream systems and applications.
Development Workflow
Use-Case, Language & Constraints Analysis
Defining domain goals, target languages or accents, and system constraints that guide finetuning and optimization strategies.
1 weekFinetuning Strategy & Training
Selecting suitable base models and applying finetuning techniques for domain, language, dialect, or accent adaptation.
1-2 weeksEvaluation & Performance Optimization
Benchmarking performance across languages and speech conditions, followed by optimization for accuracy, latency, and resource efficiency.
2-3 weeksModel Handoff & Validation
Delivering optimized models with validation results and clear usage guidelines for multilingual and speech-aware integration.
1 week