CLIP : Text Analytics

Clip is a state of the art text analytics product suite that offers the most accurate, fast, and scalable text analytics algorithms that were built with careful consideration of the complexity of arabic language. Clip is powered by the latest advances in Natural Language Processing (NLP) offering NLP solutions that are specifically tested and optimized for the Arabic language. Clip uses phonetics similarity, powered by complex deep learning methodologies, to detect the different transliterations of Arabic words. It can also recognize misspellings, misplaced info, missing details, nicknames, initials, and other errors. Our platform offers flexible fuzzy matching search, semantic matching and entity extraction capabilities that align with your business requirements. Clip can be customized to a wide variety of use cases. An example of which is entity matching as entities can be matched regardless of entry language, spelling mistakes, or partial entry.

Arabic first


Arabic-specific support: NLP algorithms that are specifically tested and optimized for Arabic over the years.


Automated transliteration: removes intermediary and costly human transliteration.


Phonetics recognition: accounts for the multiple variation of english names when transliterated from Arabic.

Value Proposition


Accurate: Achieves high accuracy.


Customizable: Customizes according to the business needs.


Easy integration: Integrates with various application and services.

Mozn case study


An entity was required to reclassify more than 500,000 businesses using only their names. Conducting such a task manually would have required months of rigorous work.


Using the semantic relation algorithms of Clip, the process was automated while maintaining a high level of accuracy.


Through Clip the entity accomplished the reclassification of all businesses in their database accurately while minimizing the consumption of time and money.