Services
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Knowledge & Training Data Synthesis
Synthesis of high-quality training datasets - including synthetic data - when real data is limited, sensitive, or imbalanced.
Knowledge & Training Data Synthesis
In many specialized domains, general-purpose LLMs are not enough: they miss nuances, misinterpret terminology, and struggle with edge cases. If you need to train an LLM for a specific task, we help you design the dataset, collect and label examples, clean and normalize sources, and build training pipelines that deliver stable, reproducible performance. When real data is limited, sensitive, or costly to obtain, we apply reinforcement learning–based techniques to synthesize high‑quality training data, simulate rare scenarios, and iteratively improve data distributions. This allows your model to learn robust behaviors even in data‑scarce settings while preserving privacy and compliance.
Workflow
why we?
Domain-Accurate Datasets for Specialized Tasks
Domain-Accurate Datasets for Specialized Tasks
We capture your terminology, nuances, and edge cases general-purpose LLMs typically miss.
End-to-End Dataset Engineering
End-to-End Dataset Engineering
From data design to collection, labeling, cleaning, normalization, and quality assurance—one accountable workflow.
Synthetic Data for Rare and High-Risk Scenarios
Synthetic Data for Rare and High-Risk Scenarios
RL-based synthesis simulates rare cases, balances distributions, and improves robustness in data-scarce settings.
Privacy- and Compliance-First Approach
Privacy- and Compliance-First Approach
We reduce reliance on sensitive data and implement controls to meet internal governance and regulatory requirements.
Faster Time-to-Model with Lower Cost
Faster Time-to-Model with Lower Cost
Efficient data workflows and targeted synthesis shorten iteration cycles and cut data acquisition overhead.
Reproducible Training Pipelines
Reproducible Training Pipelines
Versioned data and pipelines deliver stable, repeatable results across runs, teams, and environments.