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Trellis

Trellis is an AI-powered ETL platform designed to transform unstructured data such as phone calls, PDFs, and chats into structured SQL-compliant data based on user-defined schemas in natural language. It addresses complex data extraction challenges in industries like financial services, customer support, and operations by automating manual data entry and enabling SQL queries on messy or legacy data sources. Leveraging a combination of fine-tuned LLMs, vision models, and validation systems, Trellis offers high accuracy (95%+ out of the box, up to 99%+ with fine-tuning and human-in-the-loop) and supports end-to-end workflows including data integration, transformation, monitoring, and custom validation rules. It is well suited for enterprises requiring reliable processing of complex documents, compliance workflows, and RAG data ingestion pipelines.

platform:web pricing:subscription pricing:custom form:web-app form:saas feature:ai-powered feature:workflow-automation feature:data-validation feature:human-in-the-loop feature:document-processing feature:table-extraction feature:model-routing integration:api target:enterprises target:teams use-case:data-preprocessing use-case:etl use-case:automation use-case:compliance

About Trellis

Trellis is an AI-powered ETL platform designed to transform unstructured data such as phone calls, PDFs, and chats into structured SQL-compliant data based on user-defined schemas in natural language. It addresses complex data extraction challenges in industries like financial services, customer support, and operations by automating manual data entry and enabling SQL queries on messy or legacy data sources. Leveraging a combination of fine-tuned LLMs, vision models, and validation systems, Trellis offers high accuracy (95%+ out of the box, up to 99%+ with fine-tuning and human-in-the-loop) and supports end-to-end workflows including data integration, transformation, monitoring, and custom validation rules. It is well suited for enterprises requiring reliable processing of complex documents, compliance workflows, and RAG data ingestion pipelines.

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