Assisting and replacing the human workforce in text-based work Learn more
Delivering better-than-human performance in text-based work

Applica significantly reduces the human effort necessary for scrutiny and comprehension of unstructured text. Our technology eliminates up to ninety percent of human error and reduces document turnover rates to as little as under one second.

Human workforce effort
reduced by up to 75 percent
Document turnover time
reduced to less than one second
Human error reduced
by as much as 90 percent
Automating complex text-based business processes

Companies get inundated by enormous volumes of unstructured text. Thanks to the latest research in deep neural networks, our technology can prevent this from happening while providing results equal to or better than human ones.

The Applica AI-based solution helps reduce the human workforce effort, shorten document turnover, and cut down on human error.
More effectiveness. Less risk. Added flexibility.

Credit verification
The credit check process typically requires tedious corroboration
of loan or mortgage agreements against property deeds. Applica automatically extracts relevant information from official documents and performs thorough content comparisons in a way that emulates attentive and competent human scrutiny. Our technology doesn’t get tired, bored, or distracted.
Customer care
In most industries, customer service representatives are so busy dealing with repetitive issues that outlier cases often get mishandled. Thanks to Applica, standard claims can be managed in an automated or semi-automated workflow, freeing employees to concentrate on the more complex, and often most important, non-standard complaints and inquiries.
Debt recovery
The legal paperwork involved in debt collection can consist of over a dozen court files, even in a single case. For a large collection agency, the annual count is in the millions. Most of the work involved is slow, repetitive, and boring: case identification, document classification, extraction of information from text, predictable decision making. The Applica AI solution assists or substitutes humans in all of these steps.
Applying neural
language modeling
to real business problems

Most AI requires supervised machine learning using large volumes of annotated documents. Thanks to our progressive neural language modeling techniques, Applica reduces supervised learning to a minimum.

Human-level precision
Applica delivers precision equal to or better than that of humans in tasks such as document classification and extraction of information from unstructured text.
Thanks to neural language modeling, non-experts can train the Applica AI solution using as little as ten percent
of examples required by other AI systems.
Applica learns from interactions with regular users. This advanced feature enables consistent and precise document classification and extraction of information over time.

Unlike a human workforce, Applica is fully scalable, facilitating equally scalable business processes to promote accelerated business growth and increased ROI.
About us
Deploying progressive AI to bring down complex business challenges

The Applica R&D team comprises more than fifty experts, including deep learning experts, data scientists, mathematicians, and computer linguists. Over half hold a PhD.

We foster employee growth and career development in many ways, including through maintaining partnerships with prestigious institutions worldwide. Many of our team members participate in research internships at leading AI centers.

Thanks to our all-star R&D team, the Applica solution has been optimized, road-tested, and made available for commercial use to process more than 200,000 documents and 2,000,000 internet posts and user comments every month. is a proud Techstars portfolio company.

> 30 top experts
dynamic team of AI experts, mathematicians, computer linguists, and software engineers
> 30 top
> 50% PHDS
more than half of our
R&D team hold a PhD
> 50%
next-level capabilities
200,000 documents and 2,000,000 internet posts processed per month
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