Likelihood to Recommend Specifically, it starts processing millions of documents in minutes by leveraging the power of machine learning without having trained models from scratch. If any of the content contains personally identifiable information not only can Amazon Comprehend locate it but it will also redact or mask it. Using NLP techniques Amazon Comprehend goes well beyond keyword search or rules-based tagging to accurately classify documents. For my task or development, I cannot find any difficulties with Amazon Comprehend.
Read full review Kira is a great due diligence tool and can be well utilised on both large and small transactions. It also has good application if you are looking to compare multiple documents against a model form document or market standard templates. Kira is less useful if you are looking to review emails (e.g. as part of a disclosure exercise); or if your review involves non-Latin based script languages.
Read full review Pros Amazon Comprehend identifies the language of the text and extracts Key-phrases, places, people, brands or events. It can build a custom set of entities or text classification models that are tailored uniquely to the organisation's need Amazon Comprehend's medical can be used to identify medical conditions, medications, dosages, strength and frequencies from sources like doctor's notes, clinical trial reports and patient health records. This service is very good and with well an accuracy or confidence score. Read full review UI/UX - tagging and naming feels much easier than you'd expect machine learning to feel Accuracy - Kira's built-in models perform well out of the box Assistance - Kira's support team gets back to me same day if I have a question Read full review Cons It will be great if Amazon Comprehend provide support specifically for litigation or related text documents to extract insights from it. For REST API support using JAVA SDK, it will be great for developers if they provide support for testing without any credentials or account details. Setting up for REST API integration can be as simple as possible. Read full review Inability to relabel smart fields to suit the review process means it is hard to align it to particular projects (e.g. it would be useful to relabel the "Assignment" smart field as "Is the contract assignable?") Not enough non-English smart fields. Needs the ability to resell user-trained smart fields in a marketplace. Output is not customizable enough. Built-in analysis tools are useful but a little basic. Read full review Usability If our firm had more contracts in English, the usability of Kira would be rated higher. However, since we have to train clauses in Portuguese in order to use Kira, it makes its usability lower. We still are not able to fully use Kira for reading contracts in Portuguese. It takes a long time and many associate hours to make Kira usable in other languages.
Read full review Support Rating Customer Support is excellent. The online help portal is probably the best I have ever seen. Great videos with content easily found. The HelpLine is staffed by knowledgeable people. The videos have saved us providing a lot of in-house training, which we would struggle to resource. The account managers really know the product and their law firm clients and share best practices and trends.
Read full review Alternatives Considered For natural language processing tasks or techniques, there are many service providers out there in the market such as Azure Cloud Services, IBM Watson and Google Cloud Platform (GCP), but compared with them, Amazon Comprehend is the best service provider in contents of accuracy, speed of processing multilingual text, supporting SDK for most of the languages and well documented.
Read full review Kira offers a lot more out of the box than other providers and is also more flexible around integrations. This, plus the clear pricing structure, is why we went for it instead of (or as well as) others. Diligen, RAVN, Leverton, Della, Seal not in list.
Read full review Return on Investment It supports better and accurately as compared with our existing or old implementations. So, we fulfil our needs as per clients' requirements and it will help to grow or improve client satisfaction. For these specific requirements, we do not require any machine learning engineers or related professionals to hire in our organisation. None of any negative sides can be affected our business or distract existing clients. Read full review Positive ROI: Increased comfort level of attorneys and use of tech Neutral ROI: It has not significantly change how we handle projects, since there still is a need for manual review Negative ROI: It has been cost prohibitive to scale it Read full review ScreenShots