Knowledgator

Knowledgator is an open-source AI tool that provides information extraction capabilities. It offers task-specific encoder models for named entity recognition, relation extraction, and text classification, optimized for fast, on-premise deployment.

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At a glance

Pricing

Freemium · Enterprise · Custom

Free tier

Yes

API

Yes

Skill level

Technical

About

What is Knowledgator?

Knowledgator is a leading research organization focused on developing and maintaining open-source, task-specific encoder models for information extraction. The platform provides secure, affordable, and open-source AI document extraction solutions for R&D, finance, and healthcare teams. Key capabilities include GLiNER for named entity recognition, Extract-It for relation extraction, GliClass for text classification, and Text2Json for converting free-text into structured JSON. Knowledgator's models are designed for efficiency, interpretability, and accuracy, even in zero-shot settings, and can be fine-tuned with minimal data. They are optimized for local deployment on various infrastructures, including on-premise, private cloud, and edge environments, ensuring data sovereignty and fast inference speeds.

Best used for

Ideal for developers and data scientists who need to automate information extraction from various documents, structure unstructured text into JSON, and deploy AI models on-premise. Especially valuable for industries like life sciences, finance, and data protection requiring secure and efficient data processing.

Common actions

extract information

classify text

structure data

deploy AI models

fine-tune models

Capabilities

Key features

Named entity recognition
Relation extraction
Text classification
Text-to-JSON conversion
CPU-native inference
Few-shot learning
Open-source models

Target Audience

developer

Integrations

Not yet documented

Pricing & Plans

Freemium · Enterprise · Custom

Not publicly disclosed. Check knowledgator.com for current pricing.

FAQs

Can Knowledgator models be deployed on my own infrastructure?

Absolutely. Local deployment is a core feature. All models are open-source and optimized for on-premise, private cloud, and edge environments. You can fine-tune them via the platform or open-source frameworks, then export and run them anywhere, ensuring your data remains within your infrastructure.

What types of information extraction tasks do Knowledgator models support?

Our models cover a wide range of tasks, including named entity recognition, text classification, and structuring data into formats like JSON. They are designed to be efficient, interpretable, and accurate, even in zero-shot settings, and can be fine-tuned for specific domains.

How does Knowledgator compare to LLMs in terms of inference speed?

Knowledgator's non-generative approach delivers answers in milliseconds, significantly faster than LLMs which can take seconds to begin streaming a response. Our models are on average 20 times faster, completing full inference before LLMs finish their first token generation pass.

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