Draft is built with both lawyers and non-lawyers in mind. Depending on the complexity of your contract templates, you may wish to grant access to legal and commercial teams.
You can either move the contract into Review or download the contract as a pdf or docx file.
Review allows you to edit and negotiate your contracts more effectively, replacing the part of your workflow that would otherwise be done manually in Microsoft Word.
Review compares the contract to the preferred positions you set out, which we call a playbook. It then suggests edits to bring the contract in line with positions acceptable to you.
Our team of legal experts build the Playbooks for you to ensure they are configured correctly and in a way that our AI can understand.
Eventually, you will be able to view, edit and create your own Playbooks if you wish. For now, your playbooks will be created during onboarding and can be adjusted whenever you like - just talk to your Robin AI lawyer or customer success manager.
Review is built to handle not only documents you create - but contracts sent to you by other parties as well. Contracts include, but are not limited to:
We use a series of proprietary Machine Learning models to read a contract when it is added to the platform, in order to label each clause in a document. These labels are linked to the Playbook being used to edit the document, and tells the user which part of the document each entry in the Playbook refers to, whether it needs to be edited, and if so, to suggest an edit.
Machine Learning (ML) is the name for AI techniques that use big datasets to train an algorithm to perform a task. Instead of having a software engineer program a computer to go through all the steps required to perform a task successfully, ML uses data like a collection of labelled examples. Then a process of trial and error (called training), in which mistakes are used to adjust the program (called a model), is used to create a program that can perform the task successfully.
NLP stands for Natural Language Processing. That term covers a family of language processing algorithms, many of which we use at Robin. In particular, we use NLP methods to identify the key values in contract clauses so that we can assess whether that clause adheres to your Playbook, or whether it needs to be changed.
All of our customers to date have agreed to let us train our clause-labelling models using the contracts we process for them. This ensures that we can continue to improve our software and work on a growing list of contract types.
No, your data is only used to train the models that label the type of clause in a contract. The language and other data in your contract is only ever seen by you. The only impact your data has is that any mistakes our AI models make on your contracts are then corrected so that the model can learn to avoid these mistakes in the future.
No - As part of our complimentary ‘white glove’ onboarding service, our team of London-based legal professionals will set up all of your historic contracts to your specification, with the support of our proprietary machine learning technology.
No, we do the initial setup and then use AI to read your contracts and structure the data for you, so we don’t charge anything extra for onboarding.
Your contracts contain important deadlines and obligations that you need to keep track of, like expiration dates or reporting deadlines. With the reminders feature, create email reminders for those terms so you never get caught out.
You can use the Groups feature to manage which of your team members have access to certain contracts stored within Query - so everything stays private.
You can download a spreadsheet of your labelled contract data at any time as well as a copy of the original, and share it with anyone you like.
Once you’ve uploaded a document to Query, our ML will read your document and identify each clause based on thousands of examples it has seen before.What is Machine Learning?
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