C-DOT
Deploying Multilingual Local Language LLMs at ScaleCentre for Development of Telematics (C-DOT) is an autonomous telecom R&D center. They partnered with Nife to deploy and scale large language models (LLMs) tuned for Indian local languages, deploying inference workloads securely on private and edge GPU infrastructure.
Challenges
Deploying and serving large language models for diverse Indic regional languages required low-latency GPU inference, strict data sovereignty, and high throughput across distributed networks.
High latency in localized language model inference degraded real-time user experiences.
Complex GPU orchestration for multi-model Indic LLMs required specialized infrastructure expertise.
Strict data privacy and sovereign compliance mandated hosting on local, secure infrastructure.
Solution
Nife provided automated GPU-accelerated LLM deployment for C-DOT, enabling seamless one-click hosting for Indic language models with dynamic scaling and sovereign edge routing.
Automated Indic LLM Hosting: Streamlined model packaging and inference serving for Indic language models.
GPU Orchestration & Scaling: Optimized resource utilization across NVIDIA GPU clusters for peak demand.
Sovereign Edge Infrastructure: Deployed LLM inference nodes on local private networks for strict data privacy.
Results
Sub-100ms
Local language LLM latency
Indic language AI model inference served instantly across regional networks.100%
Data sovereignty compliance
Hosted entirely within sovereign local cloud infrastructure per C-DOT policies.10x
Faster model checkpoint deploys
Reduced deployment time for new Indic language LLM model checkpoints.Deploy LLM models and AI workloads securely with Nife. 🚀
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