An Iron Man suit for contracts

A typical “contract analysis engine” should have two things:

1. A taxonomy. The vendor’s idea of how to classify the various components and data points in a contract. Commencement Date, Counterparties, Liability clauses, etc. If it’s a top 5% vendor, there may be some idea of how different components relate to each other (e.g. Expiry Date = Commencement Date + Term).
2. An analysis process. In goes your contract, out comes results. This involves reading the contract (either with computers or people) and identifying parts that correspond with the taxonomy.

These taxonomies are fixed. They paint a rigid picture of the contracting world and your contract must fit into that picture. They have to be rigid because the AI that looks at your contracts needs to have been trained on lots of representative data. They can work well for simple contracts. We even use them for simpler contracts (though ours is in a league of its own).

So, why does this suck for complex contracts?

Complex contracts are often completely unique. There is no training data for them. They don’t at all fit into the pre-defined taxonomy. These contracts have their own, one-of-a kind taxonomy. Since AI doesn’t work on them, you need a person to do the work. But offshored workers punching data into spreadsheets don’t have the tools or training. And law firms have no clue how to build contract databases, even if they do know how to send expensive bills.

We built Nomio to handle contracts of any complexity. Where AI falls over, we can supplement with our unbelievably adaptable team of Document Programmers. Our data architecture and tools mean that we can build new, bespoke taxonomies on the fly with a few clicks. It's like forging an Iron Man suit for your contracts.

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