Part Two (read Part 1 here)
Incorporating AI is Strategic
Including AI in your product is an important strategic move. And building your own AI system is something many organizations consider: however, it is rarely a viable choice. The challenges are quite a few (see the Part One of our article), yet being able to assess how to incorporate AI into your solution or organization and the best way to achieve that is critical.
To Build or to partner, this is the question
As it often happens, given the increasing demand for RPA and automated processing capabilities, businesses are facing themselves with the classic strategic dilemma in AI: Build or Partner.
The decision rests largely on your use case and urgency to fill the gap. Not necessarily on owning the IP – as many would think.
While it’s true that developing AI in-house allows you to have full control on the IP- yet, it ignores all the sunk costs related to the initial stages of development and deployment.
We heard the buzz: democratization of AI is here, ready for us to grasp. This is based on
- A. Proliferation of AI engines by big-tech (Google, Amazon, Microsoft…)
- B. Continuous promotion of new features for said engines
Organizations are increasingly becoming convinced that they can develop their own AI (and perhaps do it quickly). However, these engines are merely AI infrastructure: much like WordPress, Drupal are for building web applications.
Yes, it’s true, developing ML models has become relatively easy – something a motivated techie can teach themselves online. Which means more and more enterprises are able to use machine learning to automate, predict, plan, and personalize their products and services.
But does it mean you should build your own ML technology?
While actually building models has gotten easier, translating them from science projects into reliable, scalable software that brings businesses value is still hard.
What organizations really are missing is that these tools are generic. Developing and advancing them to meet niche industry or scenario needs, requires maturity, domain expertise and repeatability.
General AI means that the models provided are not optimized for specific needs – be it legal or financial. This in turn means that these models need to be trained to understand domain specific content. As we saw before, this is the hard part: a time consuming process that starts from data collection and processing and proceeds to model training, testing and validating. Sure AutoML is great and easy to tackle, but let’s face the truth: building fully functional models takes months.
Contact us to know more about the Cognitiv+ API
At Cognitiv+ we are fully aware of the pain points of building your own AI application.
We know it because we have been developing AI technology for legal document review since 2015, not only constantly refining and enhancing its capabilities but also making sure that a solid MLOps structure was in place to allow smoothless scalability.
Our AI document review technology is one of the most advanced on the market and features:
- A proprietary machine learning model recognising over 10,000 clause types clustered into 256 clause families
- 9 pre-built turnkey templates including credit agreements, service agreements, lease agreements and regulations
- Distinct ability to understand and extract Obligations and allow users to rank them on the basis of their severity, for deeper risk analysis
- The first of its kind no-code AutoML interface for professionals to build custom models for their own documents and use in their projects.
While we offer these features on a SaaS platform, we realized how pivotal it would be for partner applications to be able to leverage our capabilities through an API. And that’s what we have worked on in the past few months.
Turn on your AI, with Cognitiv+ API: endless data extraction power at scale.
If you have built a product for legal use and wish to leverage the cutting edge capabilities of our AI document review technology, you can integrate through our API to extend the potential of your platform, fully tapping into the power of legal AI.
The Cognitiv+ API allows you to build on the back of a solid infrastructure, delivering new value to your clients and ultimately capturing new revenue streams.
Here are some examples of what you can achieve through Cognitiv+ API
Enhance the granularity and quality of your database
Cognitiv+ technology has been developed to extract data from legal documents with an extremely high accuracy and granularity. Our Vision AI technology can process scanned and handwritten documents and automatically extract data points. By integrating your DMS with Cognitiv+ technology, you can improve the quality, quantity and granularity of your data.
Boost contract comparison
Redlining and blacklining is essential to contract drafting and contract review.
Leveraging state-of-the-art machine learning technology, partners can AI-power their contract comparison system. Our technology can automatically highlight differences between contracts, pinpointing any changes and anomalies and summarize them in a redlined document – boosting the capabilities of your software.
Automate contract classification
Clustering your contracts into a taxonomy is key for proper management of your library of contracts – but also for internal business processes like contract triaging and contract queueing. Classification can be automated through our AI technology that can recognise and cluster clauses, clause families and documents with no risk to jeopardize accuracy.
Cognitiv+ API Features
The Cognitiv+ API is publicly available and accessible, ready for integration by commercial and non commercial providers in the legal, insurance, finance, property industry and beyond.
API documentation is one of the keys to integration success. We strived to make our documentation as accessible and clear as possible so that’s easy for your dev team to implement it.
We designed our API from the outset to be extensible; this means that everyone can build on top of it – so that its components and capabilities can become building blocks of new processes and value chains.
Dedicated roadmap and team
When leveraging our API, you can rest assured you can tap into our team of developers and data scientists to assist you at every step of the way, giving you a clear roadmap of what you can achieve and deliver.