VINOD VALLOPPILLIL: Hi, everybody.
I'm Vinod Valloppillil with Google Cloud,
and we're here to talk about Google Cloud and Ironclad's
latest announcement for revolutionizing document
workflows involving contracts.
So today's talk, we're going to cover a couple of quick topics.
First, why document workflows, and why
is Google putting such an outsized investment
in this area?
Our big technology investment in this space
is something we call Document AI,
and we're especially pleased to announce Contract Document
AI in today's session.
We're also doing a lot of work with Ironclad,
and so we'll be introducing my colleagues from Ironclad
to talk about digital contract management,
and how they are revolutionizing the space.
And in particular, using Contract Doc AI to do it.
So with no further ado, let's dive in.
So once again, my name is Vinod Valloppillil,
and I lead the product management
team for Google Cloud's language and vision products.
And so this spans everything from natural language
processing to vision processing, and as I
mentioned before, a particular emphasis on document processing
and Document AI.
I'm joined by my colleague Cai, who comes from Ironclad
and is a CTO and co-founder of the firm.
So why document workflows?
Why is Google putting such a big emphasis on this in this space?
Well, nearly every business process
begins, ends, or includes the processing of a document,
ranging from things like invoices and receipts
to tax forms to business documents
to contracts, income tax documents, and so on.
For Google, there's quite a bit of parallel
between all the work that goes on inside of an enterprise
to understand all this important, unstructured content
that's packaged in the form of a document,
and everything we do on a daily basis
to understand the world's largest
repository of unstructured documents, the World Wide Web.
And so we're able to quickly map that technology that we spent
decades refining on the Web and bring it over
to these enterprise workflows.
So our package or our product, or our effort
to package all that stuff into an enterprise form,
is something that we call Document AI.
And put simply, Document AI is a set
of technologies that takes unstructured content,
for example, an image of somebody's driver's license,
and turns it into structured data that can be automated
and interpreted by machines.
It sounds really simple, but it's anything but.
At the beginnings of Document AI, the lowest level of the AI,
of course, is natural language processing.
Even at this first building block,
natural language processing is actually
a very difficult problem for computers.
Why?
Because text is ambiguous.
A phrase like "the British left waffles on Falkland Islands"
can be interpreted many different ways, some of which
are humorous and some of which are intentionally not.
And so the context of words like "waffles"
has a lot of impact on the meaning of the entire sentence.
In order to solve this problem, of course,
we're investing significantly in artificial intelligence
technology.
Documents take the natural language
and artificial intelligence problem to the next level.
They're a very special piece of text, or a very special piece
of content, layered with multiple levels of meaning.
It's one thing for example to tell you
that this document had the words "Jane Doe" and "Ohio" in it.
It's a very different thing to tell you that this is actually
Jane Doe's Ohio driver's license, issued
on this date and expiring on this other date.
That latter assertion is much more valuable
in a business setting, and is the big trick, or the big goal,
by applying tons of artificial intelligence into the problem.
So what takes documents to the next level?
Well, unfortunately, contracts are probably, bit for bit,
one of the most valuable document types in industry.
Contracts govern every single dollar that
flows in and out of a business.
Contracts govern the entire business itself,
the incorporation of the business,
as well as critical business transactions,
like acquiring entire businesses.
And as a result, every single word, every single element
of a contract, is potentially something
that's valuable to the business and must be understood
by the artificial intelligence.
And so in order to address the world's contracts
and the world's documents, we're very
pleased to announce a new type of Document AI
that we call Contract Document AI.
Contract Document AI, of course, is a specialized set
of AI models for understanding the world of contracts.
This is a very large, very deep technology.
And so we currently have this in preview,
and we are focused on an initial set of contracts
and an initial set of elements that we pull out
of the contract.
Contract Doc AI takes our existing technology.
And so for example, in this situation is very simple case.
I've got a contract where the expiry date of the contract
is written in natural language text.
We apply natural language, today's techniques,
and can identify the expiry date on this particular contract
is January 1st.
Document AI brings in visual-spatial information.
And so in this situation, the expiry date
was encoded inside of a table.
And so we use a different set of techniques
to recognize this new expiry date.
And then finally, Contract Doc AI
introduces a third set of techniques,
something we call decision tree learning,
that interprets the full body of the contract.
And so in this situation, the top of the contract
said that this agreement began on April 7, 2017,
but a secondary section or a latter section in the contract
says that the term of the agreement is one year.
Decision tree learning takes both bits of information,
the start date as well as the expire as well as
the term of the contract, in order
to compute an expiry date.
And so this type of analysis, or this type
of whole document understanding for contracts,
is a pretty new piece of technology.
And it's something that we're quite excited to introduce.
We're currently applying this, inside of Document AI,
we're currently launching this with something like 8 to 10
different contract modules.
And so we're creating a body of semantic lenses,
or a body of these decision tree modules,
that understand different elements
that are common across all different types of contracts.
And so, for example, at a document level,
most contracts have a name.
They usually have a reference number
that was created by a lifecycle management tool.
Different term and termination elements, dispute resolution
covenants, and so on.
Each of these tools or each of these modules
is something that we have specialized logic
or specialized AI around, and you'll
expect to see these modules grow over time as we
tackle different specialized types of contracts.
And one example of what's going on,
so this is our module for parties
or understanding the elements, the players
inside of a contract.
As you can see inside of this contract body,
we have two different parties, CMC ICOS Biologics,
and a company called Agenus.
And Google Contract Doc AI is able to recognize
different references, the different definition
for these parties, and provide enriched data that
identifies who exactly these parties are
for subsequent processing.
So it's not just returning the data
that it found in the contract and using
the body of the contract, it's actually returning more data
than might have been physically resident inside
of the contract.
A big part of a big problem in contract management, of course,
is classification or recognition of different types
of contracts.
A big feature that we're also announcing in this conference
is pre-built recognizers to recognize
six of the most common types of contracts: the supply chain
contract, real estate contracts, corporate finance and more.
Once again, over time, the set of contracts
will grow, as well as the set of modules
that we use to identify and process
the entire body of the contract.
We're also very excited to announce a relationship
with our partners Ironclad, who will
be kind of our launch customer for contract Document AI.
With that, I'm going to hand it over
to my colleague Cai, who'll will talk about Ironclad.
CAI GOGWILT: Thanks, Vinod.
And thanks for sharing why it's so important
that Google Cloud AI is taking on the challenging
domain of contracts.
My name is Cai GoGwilt, and I am the CTO and co-founder
of Ironclad, a digital contracting platform that
brings archaic business contracting processes
into the modern digital era.
We're a leading contracting solution,
according to analysts like Forrester and Gartner,
and we're trusted by over 700 customers, including
Mastercard, Staples, and Peloton.
More contracts flow through our platform
than any other contracting solution on the market,
and we're also the only solution that
can handle every type of contract,
from heavily negotiated sales contracts to consumer click
wrap agreements.
So on the next slide, I'll tell you how it works.
We start by digitizing the contract.
This means we take static contracts-- think
paper documents or PDFs.
We turn them into dynamic processes.
We transform them from static legalese
to conditional logic that can, for example, bring
the relevant approver in at the right time.
With the document and processes digitized,
all parties to that document, whether they're
internal collaborators or counterparties outside
of the company, are brought together
to get the contract done.
They can collaborate in a shared online editor,
so deals can be done faster and more
collaboratively, with fewer meetings and crossed wires.
Finally, and this is where Google Cloud AI comes in,
we unlock contracts data and pipe previously inaccessible
data within contracts to other parts
of the business to enable better, faster decision-making.
And unlocking contracts data is why
I'm so excited to talk to you today about Ironclad
and Contract Doc AI.
Together with Google, we are turning contracts
into operational data pipelines that serve the entire business.
We're doing this by providing access
to the data that is locked inside of the contracts.
In a pre-Contract Doc AI world, gaining access
to the critical information locked inside of contracts
is really hard to do.
It requires a Herculean and expensive effort,
involving teams of people manually tagging documents.
And once the documents are tagged,
they're not auto-updating, so you can never
be sure if the data collected is the most
up-to-date and accurate.
Because the data is locked away, most companies
have no visibility into their contracts.
They're flying blind.
As a result, they can't produce the insights
needed to confidently inform business decisions.
Ironclad and Google enable companies to fly with control,
by first solving the problem of access.
Contract Doc AI enables companies
to harvest data from contracts, while Ironclad
takes that data and pipes it into parts of the business that
need it, providing visibility to a chief sales officer who lives
in Salesforce, or a business intelligence professional who
needs it in Data Studio.
This enables the business to uncover previously
hidden new insights.
Our own chief sales officer at Ironclad, for example,
uses data on in-flight contracts to forecast which deals
are going to close and when.
This vision to democratize access to contracts data
has been important to us from the beginning.
And the promise of AI in the contracting space
has been exciting to us from the beginning as well.
In fact, we, Ironclad, started working on AI in-house
five years ago, and even brought a few features
into early alpha.
But the technology and techniques before 2019
couldn't achieve the accuracies we needed,
and we were unwilling to bring the resulting
features to market.
And then in 2019, there was an inflection point
for natural language.
We started looking at Google's language products,
and realized that they'd just made AI commercially
viable for contracts.
Almost overnight, experiments that had taken us weeks
were taking just hours, and document parsing pipelines
that took minutes to run were replaced by hosted models that
took seconds.
Our precision and recall numbers were head and shoulders
above the models we'd spent two years developing and training.
With the great underlying technology of Contract Doc AI,
we've been able to focus on delivering value
to our customers.
Ironclad Smart Import lets companies take import contracts
from anywhere and automatically ingests, classifies,
and extracts all the key pieces of data from a contract.
And because contracting is a domain with a low tolerance
for errors, Smart Import enables customers to quickly verify
extracted contracts data.
This makes it possible for companies
to fly with full visibility of not just
key terms on their own paper, but also the key terms on paper
that originated outside of the organization
with third parties.
Since its launch, Smart Import has
driven some transformational results across our customers.
To give you a look into some early results,
customers have been able to upload and tag contracts
75% faster than they could before,
and they're seeing a 40% cost savings
compared to having external contractors do it for them.
With all of these great results we've seen so far,
we're expecting to process around 50 million contracts
over the next few years.
But what excites us the most is how Smart Import
is bringing a step change improvement
to our customers, customers who before Smart Import
had resigned themselves to flying blind
when it came to contracts data.
Civica Rx is one of these customers.
Civica is an incredible non-profit pharmaceutical
company whose mission is to make quality generic medicines
accessible and affordable to everyone.
Before using Smart Import, Civica would only ever
upload contracts on an as-needed basis,
and they didn't even think about data extraction.
It wasn't that they didn't need the data,
they simply could not afford the time and the money.
With Smart Import, their legal and finance teams
can track contract expiration dates and renewal dates,
so they can proactively avoid racking up automatic renewal
fees.
Their legal team no longer has to manually search
for legacy contracts that live outside of Ironclad.
This doesn't just save them time, money,
and a whole lot of doubt, it opens up
a whole world of possibilities that they previously
lacked access to.
As their AGC Sarah says, "this has been a game changer for us.
For the first time, we have visibility
across all our contracts, past and present,
and are getting that insight with minimal investment."
We're honored to be part of Civica's journey,
and excited about the possibilities
our partnership with Google brings
to create this same kind of step change transformation
for every company that works with contracts.
Back to you, Vinod.
VINOD VALLOPPILLIL: Thank you, Cai.
So as you can see, we are very excited about Contract Doc AI.
We think there's a lot of transformative opportunities
that this will enable, both directly
as well as in conjunction with our partners at Ironclad.
We also hope you're inspired by it, too.
It takes some of the most cutting
edge and broadest artificial intelligence techniques
that Google has developed, and bring them up to another level
by making them vertically specific
and starting to understand the nuances of some
of the key elements or key aspects associated
with processing contracts.
To learn more about all this, be sure to visit cloud.google.com.
And on cloud.google.com, you can find
pages that get into more details about Contract Doc AI.
In the meantime, we hope you're enjoying the conference,
and looking forward to working with all of you
to help transform your contracting experience.
Thank you.