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Request a demo →

Your
proprietary AI

Develop bespoke AI for your organization with
domain specificity that only hybrid intelligence
can deliver at unparalleled speed.

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Automation has stagnated at
many financial institutions

One reason is because tools and methods that work for simple documents like drivers licenses do not work for more complex documents like earnings reports where the data is structured in infinite formats.

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The only method for automating such highly unstructured documents is deep learning, which requires a vast amount of training data. Generating enough high-quality training data is often a roadblock because it is costly.

Cognaize eliminates this roadblock ensuring that whole new categories of documents can be automated. Our best-in-class AI and novel methodology provide your firm with a proprietary AI capability to push automation beyond current limitations. We help improve your firm’s operational efficiency and deliver a sustainable competitive advantage.

Let's talk →
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Establish your team
as a strategic asset

Your data science team has much to offer through innovation and automation. Cognaize leverages hybrid intelligence to provide new avenues for their valuable contributions.

We pave the way forward by deploying our AI platform in your environment with models pre-trained on financial documents and help you establish proprietary AI models mapped to your data dictionary and trained on your data.

  • We deploy in your private cloud, hybrid, or on-premise environment
  • Standard APIs enable easy integration with your tech stack
  • All models developed by your team are your firm’s IP and strategic asset

3+ million

Complex financial documents processed to date

50,000+

Complex documents processed every month

Unlike other providers that train their models using client data, with Cognaize, your work builds your IP so that it works only for you - not your competitors.

Let's talk →
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Unleash your team’s creativity

With Cognaize, data science teams receive an unlimited stream of high-quality domain-specific training data to develop new automation models for any number of use cases

Choose deep learning for unstructured data

Deep learning is the most effective technology for processing unstructured documents, but it requires a large amount of training data — especially when those documents are complex. This presents a paradox — as the amount of training data increases, the benefits of additional data decrease while the cost of obtaining and processing it remains constant. As a result, the process becomes uneconomical long before automation begins to add exponential value.

With Cognaize, training data is generated constantly as a byproduct of data validation performed by subject matter experts in your business units. This continuous flow of high-quality, domain-specific training data is fed to the data science team so your models never stop improving until they reach or exceed expert accuracy levels.

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Ever-better automation
with hybrid intelligence

One of the most common impediments to building automation solutions is a breakdown in communication between the business and technical teams leading to misalignment. Often this can be due to new types of documents or documents types changing without the tech team’s knowledge.

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Cognaize offers a new way of working with an integrative experience for both teams. With subject matter experts now generating training data as a byproduct of routine data validation, any new document types or changes are immediately flagged to the data science team. Data science teams can structure more precise data validation by putting at the center the expert who validates data at various stages, for each type of model.

For example, if we consider a document with numerous tables, a first validation step can be added to make sure tables are detected properly. Then a subsequent validation step can check the extracted values per table. This helps catch model discrepancies before they snowball into larger issues for data science teams to identify and resolve.

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hybrid intelligence, and document automation.

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