Ocrolus raises $24 million to scan financial documents with computer vision - VentureBeat

Ocrolus raises $24 million to scan financial documents with computer vision - VentureBeat

Ocrolus raises $24 million to scan financial documents with computer vision - VentureBeat

Posted: 25 Jun 2019 06:30 AM PDT

Ocrolus, a New York startup that taps AI and machine learning to parse financial documents, today announced it has raised $24 million in a series B round led by venture growth equity firm Oak HC/FT. Ocrolus cofounder and CEO Sam Bobley said the fresh capital, which follows a $4 million series A in April 2018 and brings the company's total raised to about $30 million, will fuel expansion into verticals like consumer and auto lending and advance development of the company's underwriting solutions for banks.

"Sometimes humans are better than robots," said Bobley, who added that Ocrolus has quintupled in size since April 2018 and now counts hundreds of financial services companies among its customer base. "We combine machine processes with live human intelligence to provide customers with a complete solution. The capital will be used to develop workflows for new document types and sharpen our fraud detection and analytical capabilities."

Ocrolus' optical character recognition (OCR) technology — which it claims can analyze files with 99% accuracy — supports documents of almost any type and quality. Customers upload files or scans through Ocrolus' bespoke web portal, after which the company's backend algorithms extract key information before sending on anonymized snippets to a human team for validation. Finally, the results are delivered to customers' back-office system.

Ocrolus

Above: The Ocrolus platform.

Image Credit: Ocrolus

In that respect, Ocrolus' offering is a lot like Amazon Web Services' (AWS) Textract, which uses machine learning to parse data tables, forms, and whole pages for text and data. London-based Flux offers a comparable file-parsing service targeted at retailers, and Upflow's tech leverages OCR to autonomously detect and extract customer names, amounts, due dates, and more from invoices.

But as chief operating officer Vik Dua explains, Ocrolus' focus is narrower in scope, which enables it to address domain-specific problems that commonly throw other platforms for a loop. "Our infrastructure is highly scalable and continually teaches itself to become smarter," he added. "We're excited to accelerate our product roadmap and alleviate additional pain points for our customers. Ocrolus is poised to improve the quality of work in use cases across financial services and beyond."

Ocrolus offers a turnkey solution hosted on AWS. The platform reviews bank e-statements, scans, and cell phone pictures of printed statements and generates custom-tailored analytics, ultimately geared toward tracking account balances, detecting money movement, and identifying missing or fraudulent information. Its API plugs into Salesforce and other customer relationship management platforms, and it guarantees a baseline level of security with 256-bit AES encryption, SSL authentication, and multifactor authentication.

"Ocrolus is a unique company providing a rare combination of smart automation, analytics, and accuracy in its solution," said Oak HC/FT venture partner Dan Petrozzo. "By combining its tremendous technology with an added human touch where required, the platform delivers amazing results for its customers."

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Designing Social Robots for Older Adults - The Good Men Project

Posted: 20 Jun 2019 07:30 AM PDT

The limitations of current solutions to assisting older adults, the increased social and emotional toll on caregivers, and the inability of institutions to create structural solutions in a timely manner calls for a paradigm shift in the way we approach aging.

by Leave a Comment

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Most countries are projected to see the number of people ages 65 and older surpass the population under the age of 15 by 2050. The limitations of current solutions to assisting older adults, the increased social and emotional toll on caregivers, and the inability of institutions to create structural solutions in a timely manner calls for a paradigm shift in the way we approach aging.

As these new meanings of age, aged, and aging are re-negotiated at a personal and collective level, the main goal of this research initiative is to study aging adults' daily living assistance, social and emotional needs, and intergenerational connection while exploring the optimized modalities for embodied agents to successfully deliver these interactions. We see embodied agents as a method to enable older adults to age-in-place, supporting them in ways such as promoting social connectedness, tracking vitals, coaching in emotional wellness, and assisting with medical adherence.

Our work is rooted in partnering with the community through co-design and participatory design methods to inform robot design by empowering older adults to engage in our research. We prioritize developing robot interactions that can be tested long-term in older adults' homes to better inform how social robots can shape aging-in-place.

Currently, we are running a long-term codesign study with older adults. Over the course of the year, older adults will engage in interviews, interactive artwork, living with a robot, prototyping on a robot, and design guideline generation.

If you are 70 years of age or older and interested in participating in future study opportunities, please contact Anastasia Ostrowski ([email protected]).

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This post was previously published on www.media.mit.edu and is republished here under a Creative Commons license CC BY-ND 4.0.
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