Smarter Data Curation & Knowledge Encoding with Loktak
Break Data Labeling Bottlenecks & Enhance Model Accuracy
Break Data Labeling Bottlenecks & Enhance Model Accuracy
- AI-Powered Data Labeling: Automate the creation of high-quality training datasets with minimal manual effort.
- Seamless SME Collaboration: Leverage an intuitive platform for domain experts and data scientists to refine model accuracy.
- Loktak’s Proprietary Data Generation: Utilize programmatic data generation, synthetic augmentation, and aut
- AI-Powered Data Labeling: Automate the creation of high-quality training datasets with minimal manual effort.
- Seamless SME Collaboration: Leverage an intuitive platform for domain experts and data scientists to refine model accuracy.
- Loktak’s Proprietary Data Generation: Utilize programmatic data generation, synthetic augmentation, and automated labeling to accelerate LLM fine-tuning with minimal human effort.
Break Data Labeling Bottlenecks & Enhance Model Accuracy
Break Data Labeling Bottlenecks & Enhance Model Accuracy
Break Data Labeling Bottlenecks & Enhance Model Accuracy
- Programmatic Labeling at Scale: Instantly generate thousands of prompt-response pairs with encoded SME acceptance criteria.
- Automated Error Analysis via Loktak: Identify and correct training data issues with built-in AI-driven analytics.
- Reinforcement Learning from Human Feedback (RLHF) Integration: Improve model decision-making through iterative feedback loops.
Deploy Optimized LLMs at Scale
Break Data Labeling Bottlenecks & Enhance Model Accuracy
Deploy Optimized LLMs at Scale
- Adaptive Model Fine-Tuning: Optimize model weights with advanced techniques like LoRA (Low-Rank Adaptation), distillation, and parameter-efficient fine-tuning (PEFT).
- Seamless Integration with Major AI Frameworks: Compatible with AWS SageMaker, Google Vertex AI, Azure ML, Databricks (Mosaic AI), OpenAI, Cohere, and Meta.
- Hybrid & On-Prem D
- Adaptive Model Fine-Tuning: Optimize model weights with advanced techniques like LoRA (Low-Rank Adaptation), distillation, and parameter-efficient fine-tuning (PEFT).
- Seamless Integration with Major AI Frameworks: Compatible with AWS SageMaker, Google Vertex AI, Azure ML, Databricks (Mosaic AI), OpenAI, Cohere, and Meta.
- Hybrid & On-Prem Deployment with Loktak: Ensure maximum data security and compliance by fine-tuning models within your own infrastructure.
Higher Model Accuracy with Domain-Specific Intelligence
Fine-tuning foundational LLMs with specialized enterprise data produces models that outperform generic solutions in accuracy and efficiency.
Enhanced by Loktak’s RAG Optimization
Loktak uniquely enhances retrieval-augmented generation (RAG) by curating high-quality, domain-specific knowledge bases to ensure highly accurate, context-aware responses.
Lower Costs & Faster Inference
By distilling and fine-tuning smaller, task-specific models, enterprises reduce inference costs and latency while maintaining high performance.
Enterprise-Grade Security & Compliance
PhrasIQ provides the highest security in the industry, ensuring data privacy, regulatory compliance, and AI governance through robust encryption, audit trails, and access controls.
