Natural Language Processing

Leveraging human-machine synergy

Natural Language Processing: A game-changer in human-machine dialogue

By enabling machines to read, understand, and interpret our language, Natural Language Processing (NLP) is bridging the divide between humans and technology. As a branch of Artificial Intelligence, it introduced us to a new era of human-machine interaction, making our interactions with machines more seamless and intuitive than ever before.

Seamless Language Processing

Facilitate human-machine conversations

Natural language understanding and generation

Document reading and processing

Grammatical error corrections

Driving efficiency and value-creation with NLP

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Increases employee productivity

Supports decision-making

Improves customer service and experience

Download our e-Book on ‘The Scope of Intelligent Automation in Insurance Industry for more insights.

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Simplifai’s Solutions: Driven by the power of NLP

AI technologies such as NLP and Intelligent Process Automation make up the core of Simplifai’s state of the art AI solutions.

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Created to empower employees through saving valuable time and resources, our solutions are equipped to understand customers and fulfill their needs akin to humans, but with greater efficiency and speed.

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With NLP techniques, our AI solutions can accurately comprehend, analyze, and respond to various human languages. They extract relevant entities and intents from free text, performing a variety of tasks accurately and efficiently. Our solutions automate tasks such as correspondence, document archiving, system updates, and replies, leading to swift outcomes within minutes or even seconds.

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Customer Service

Claims Handling

Debt Collection

Simplifai Archiver

Document Handling

NLP: A trending topic

Our commitment to exploring new advancements is integral to our mission of delivering exceptional AI solutions. As Generative AI gains increasing prominence, it propels NLP to the forefront of AI-related discussions. At Simplifai, we stay up to date with the latest developments to ensure that we continue to provide innovative and effective AI solutions for our clients’ specific needs.

Transformer-based models:

These models have shown impressive results in various NLP tasks, including language understanding, question-answering, and text generation.

Pre-trained language models:

Trained on large amounts of text data and then fine-tuned for specific NLP tasks, this approach has shown remarkable results in reducing the amount of labeled data needed to achieve an outstanding performance.

Multilingual NLP:

As more companies are expanding their operations globally, multilingual models are gaining popularity by being able to perform tasks such as language identification and machine translation in multiple languages.

Zero-shot learning:

A technique that allows models to perform tasks for which they were not explicitly trained. This approach can be useful in scenarios where training data is limited or unavailable.

Explainable NLP:

A growing field that aims to make NLP models more transparent and interpretable. This is important for building trust in AI and for addressing ethical concerns around the use of AI in decision-making.

Gartner Report: 61% of High Tech Leaders consider NLP and Natural Language Understanding (NLU) as their organization’s primary investment when it comes to emerging innovative technology.[1]