Sold by: Crayon
Co-innovated with the AWS Generative AI Innovation Center (GenAIIC) Partner Agent Factory (PAF), Crayon refiNER is a multilingual, agentic entity recognition framework that enhances existing NER systems with large language models and adaptive refinement. It acts as an intelligent reflection layer that automatically identifies, validates, and improves entity extraction across different domains and languages. Using contextual reasoning and web-based validation, Crayon refiNER delivers accurate, explainable, and scalable results. Designed for enterprise NLP workflows, it improves precision, reduces manual effort, and continuously adapts to new data and domains without the need for retraining.
Overview
Crayon refiNER is a cutting-edge, multilingual, agentic entity recognition framework built on large language models (LLMs). It automatically detects, validates, and refines entities across languages, domains, and content types. Using an intelligent, tool-driven workflow, it combines contextual reasoning, dynamic validation, and adaptive refinement to deliver accurate, explainable, and scalable entity extraction.
Powered by AWS Generative AI Innovation Center (GenAIIC) Partner Agent Factory, Crayon RefiNER continuously monitors extraction outputs and applies closed-loop feedback to refine model behavior. By leveraging contextual understanding, tool-assisted validation, and LLM-as-judge evaluations, RefiNER achieves progressive accuracy improvement without manual intervention.
Built using AWS Strands SDK and Amazon Bedrock, RefiNER is engineered for enterprise-grade reliability and scalability. It incorporates GenAIIC’s Intelligent Document Processing (IDP) reusable asset and has been successfully deployed on AgentCore, leveraging the platform’s Runtime, Memory, Identity, Gateway, and Observability primitives for efficient, monitored, and explainable operations.
Benefits:
- Adaptive Learning: Continuously adapts to new data, languages, and domains without retraining, ensuring sustained performance and relevance as business contexts evolve.
- Transparent & Auditable: Provides clear, explainable extraction results supported by detailed validation logs and reasoning chains enabling compliance, auditability, and trust in automation.
- End-to-End Traceability & Observability: Built on Amazon CloudWatch, AWS X-Ray, Amazon Bedrock, and AgentCore Observability, delivering full visibility across model inferences, tool invocations, agent workflows, and runtime dependencies. Enables service maps, correlated traces, and audit-ready insights for monitoring and debugging.
- Secure, Identity-Aware Access: Implements hardened authentication and authorization through Amazon Cognito and AgentCore Identity & Gateway primitives. Enforces scoped tokens, granular role-based controls, and comprehensive audit trails to ensure that all users and internal components operate within defined trust boundaries.
- Controlled External API & Tool Access: Facilitates secure integration with external GenAI and web-connected tools such as Tavily, retrieval APIs, or third-party knowledge services via AgentCore Gateway and Identity layers. These layers handle token exchange, policy enforcement, and signed request routing, ensuring that all external calls comply with enterprise security, observability, and governance standards.
- Reduced Manual Effort: Eliminates time-consuming manual tagging and rule-based updates, thanks to integrated quality evaluation and self-refining feedback loops.
- High Precision and Recall: Combines contextual reasoning, dynamic validation, and adaptive refinement to enhance accuracy across complex, multilingual, and unstructured text sources.
- Seamless Enterprise Integration: Easily integrates with existing NLP pipelines, analytics platforms, and enterprise workflows, supporting scalable and practical deployment.
Highlights
- Multilingual Intelligence: Delivers accurate, context-aware entity extraction across multiple Singaporean and global languages using advanced large language models (LLMs) trained for multilingual understanding and domain adaptation. - Self-Optimizing Accuracy: Continuously improves precision and recall through adaptive feedback loops, contextual reasoning, and automated refinement eliminating the need for manual tagging or model retraining.
- Real-Time Validation: Enhances reliability by validating uncertain entities through live web and knowledge sources, combining LLM reasoning with tool-driven verification for trustworthy extraction. - Comprehensive Evaluation: Integrates objective performance metrics with LLM-as-judge scoring to provide transparent, explainable, and continuously improving quality assessments. - Flexible & Extensible Design: Built on a modular architecture that supports domain-specific customization.
- End-to-End Observability & Security: Provides full operational traceability through CloudWatch, Bedrock, and AgentCore Observability, with secured access managed via Cognito, Identity, and Gateway primitives for auditable, compliant operations. - Controlled External API Access: Enables safe, policy-enforced connectivity to external tools and web-based APIs (e.g., Tavily) through AgentCore Gateway, ensuring all requests are authenticated, monitored & aligned with enterprise security governance.
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Crayon customers please reach out to your Crayon representative via phone or email. Non-Crayon customers may contact aws.alliance@crayon.com for more information.