Kore SLM

Kore SLM (Small Language Model) provides a versatile suite of enterprise-grade services, including PII detection, tokenization, summarization, and classification capabilities, alongside a range of other powerful language model tasks, all within a secure, scalable cloud-native deployment.

Automated PII detection

Leverages advanced natural language processing models to identify and classify personally identifiable information (PII) such as names, addresses, social security numbers, and other sensitive data in unstructured text, with high accuracy and minimal false positives.

Secure, authenticated API

Provides robust API endpoints with multi-layer authentication and authorization mechanisms, ensuring that only verified applications and users can access the service. Built-in support for OAuth2 and API key management ensures enterprise-grade security.

NLP/tokenization

Utilizes optimized machine learning pipelines for tokenization, part-of-speech tagging, and named entity recognition. Designed to handle high-throughput workloads, enabling lightning-fast processing with low latency for both batch and streaming inputs.

Real-time processing

Supports real-time data ingestion and processing, making it ideal for applications requiring instant feedback and decision-making. Offers optional persistence of processed results in secure, encrypted storage for compliance auditing, traceability, or downstream analytics.

Classification and sentiment analysis capabilities

Includes built-in models for categorizing text into predefined or custom labels, as well as assessing the sentiment (positive, neutral, negative) of any given input. Ideal for content moderation, customer feedback analysis, and social media monitoring.