Analyze is LinkSquares cloud based repository.

This is where our customers can segment out and store all their executed agreements, and this is where our proprietary AI runs across the contracts for data extraction.

Our AI can extract around a hundred and fifteen different data points from their contracts, things like full clauses, key dates from the agreement, key numerics, and milestones. So customers can not only search and report on those contract obligations, but we actually use those data points we extract from your contracts to assist you with automating the organization of the contracts.

As you can see here in my repository, every contract has been re renamed automatically to a standard naming convention.

Users can customize their naming preference so that every agreement, both legacy, but also contract signed moving forward, are renamed automatically to that convention.

The type classification occurs as well by our AI. Our AI reviews the documents and determines what broad category of agreement they are. This allows for an automated data filter. If I come into the system, I want to see only my NDAs or certain type of agreement. I can refine down by type.

The right hand side is our tagging structure.

So this is how we categorize and organize the contracts on a more granular level within the system. We do have automated tags. You'll see here in green. The AI pulls out the parties in the contract and effective year. So that baseline customers have that organization set. If you wanted to come into the system and see all your contracts with this vendor or customer or counterparty, you can click that counterparty name, and it brings you to those contracts you have with them.

Now we can also add additional tags according to your preference. So this is a way to segment out contracts further by department it belongs to or by type of agreement it is or project or region. This would be fully customized depending on your organizational preference. We do have ways as well to input these tags during the presignature process. So if users are utilizing our finalized pre signature solution, we can apply tags there. And once the agreement is fully executed, those tags in that organization for that contract will flow in to the repository alongside with the agreement.

Now focusing on an individual document.

We can touch on the different processes that occur when we ingest the contracts into the repository.

The first process is to ensure that the contract is accurately digitized and searchable for our users.

So oftentimes, we have customers who have older documents that look like this or things that are wet signed or scan locked. And so we can ingest these types of agreements into the system. These would funnel through our OCR process.

So we do have an internal OCR process where we run the initial OCR to transcribe a document like this. However, that could pull some errors, especially with an older agreement like this. An m transcribes as two n's or the incorrect date here, January one, could pull as January l. Just causing a lot of errors and causing a lot of issues if you are trying to full text search across your agreements.

So we layer a proprietary script on top of the transcription that's gonna flag all those different error points. And we do have a human QA team based here that can go into those error points and fix them so that you do have an accurately searchable agreement for full text searching.

After that point, we layer on our AI.

Again, for agreements that are digitized, our AI will automatically run and pull out different data points. But if we do have that scanned agreement, we do need the digitized text to run the AI across.

Once the agreement is in the system, the process is on our team to not only have it digitized, but also have the AI run. So the left hand side is showing the output of the around a hundred and fifteen different data points that can be automatically surfaced from the contracts.

That includes things like full text clause extraction.

Our AI can extract key provisions from the contract so that you can search and report on those obligations.

Things like what are the assignment provisions in my contracts? What are the change of control clauses, limitation liability, indemnification language, the term clause?

We also have algorithms that are true false data points. This check box here. So this will flag if the agreement auto renews or if there's termination for convenience language, or if change of control consent is required.

In that way, you can pull those reports in aggregate. I can pull a report of my contracts that auto renew or quickly see if we have agreed to any contracts with termination for convenience language in our agreements. A big point for a lot of teams is tracking key dates.

That's something we automatically pull as well. We extract the effective date, the commencement date, the renewal date, the termination date. And even if a date is not explicitly stated in the contracts, we'd be able to do a calculation.

For example, not only pulling the renewal date itself, but actually taking into account the required opt out period. If you have to give notice sixty days before the renewal, we backtrack and calculate the automatic renewal opt out date. That way, prior to any renewals or prior to any decisions regarding next steps with that particular engagement, you'd be able to get adequate notice and have information as to whether or not you do want it to auto renew.

All these data points are out of the box, but customers can also customize data points. If there's something more bespoke you'd like to track, there are different ways to do that. One of those ways is what we call user generated data points.

So oftentimes, this encapsulates tracking things not within the four corners of the contract, like a point of contact, an agreement owner. You can see at the bottom here, I have a couple examples, these blue pencils. Users can create as many additional data points as they'd like to track. And again, you can search and report on these alongside the automated data extraction as well.

There's quite a few things we do with the data now that we extract. So we can showcase holistic reports.

We pull all those dates we extract from your contracts, and we present them automatically into an events calendar. This showcases what's upcoming for termination, renewal, what's the auto renewal opt out date. So you can see this month, this quarter. We can also present this in a list view as well.

We can also present this in a list view as well. All of these dates as well, we can set up automated notifications to go out prior to these dates. These reminders can be customized in terms of who's receiving those reminders, if there's a certain team managing these dates and these milestones, If there's a certain team managing these dates and these milestones, you can set it up so they receive that reminder. You can also customize when they receive that reminder. Thirty, sixty, ninety days before, we can set that up so that those proactively go out to those individuals prior to these dates.

LinkSquares also has a dashboard. So within the repository, our dashboard is focused on analyzing your executed agreements. Now that everything is centralized and stored and organized in the system, you can really get this bird's eye view. I can see of the fourteen hundred agreements I have, what's a breakdown of contracts by type. I can see agreements renewing or terminating each quarter. You can click into these present spreadsheets of these data points, export anything to Excel, but it also provides for a deeper analysis into all the different data our AI surfaces.

A clause analysis allows me to view and compare certain clause provisions.

If I wanna see the change of control clauses, I can pull that report. If I'd like to see price increase language, I can zero in on that data point. Similarly, with those true false data points, you get holistic visibility into whether that language exists in your contracts. I can see ninety five contracts I have have termination for convenience language in them, and quickly access those agreements as well.

Now the dashboard is really focused on overarching reporting. We can also get really granular and specific with reporting back here on this main page.

There's many different ways to search and filter across your repository.

First and foremost, now that we have helped you organize the contracts, you can filter by name of the contract, by type of contract, or by organizational tag. But we also can advance filters and search within the contracts themselves.

There's many different searching options. I'll showcase a couple here today. We do have an agreement content search.

So this acts as a keyword search across your entire contract database.

I can type in a term. I can advance it to multiple terms with and or searching abilities. But, essentially, this runs off of fuzzy or inexact logic where it's pulling me not just to regulate in my contracts, it's pulling me to regulations, regulatory as you can see down here, and allows me to toggle within the contract to see where that was extracted from as well.

This gives you the broadest search possible, but you can also narrow this down to just an exact search to just pull the term regulate.

With our full text searching, again, this allows digitized, but even if you have older contracts that are, again, presented like this and are not currently searchable, those would have gone through our OCR process, are digitized, and are now full text searchable for you.

Text search, we do have proximity searching abilities. So you can even narrow down the scope of the full text search to look for language within a certain word count of a certain term. The word data, for example, is certain word count of a certain term. The word data, for example, within twenty words of the word delete deletion.

This allows me to go within a paragraph or a sentence in my contracts to do do that proximity hook.

In addition to the full text searching, we also have reporting based on our AI data points. So global term searching allows us to report on our AI data points, any custom terms we're tracking as well. And essentially, we can get really granular with our searching and reporting.

Specify the period, but, essentially, depending on the time frame you input, so here the next year, it'll refine me down to the forty two contracts I have renewing within that period.

This is where tags come to play as well because I can use tags, the organization, as additional hooks in reporting. Let's say I just wanna run this renewal date search for a certain department's contracts or my vendor customer contracts or contracts from a certain region. You can get really specific and narrow with just running reports on these subsets of contracts, and you'll see the repository will continue to refine down.

Not only can I see a list of these contracts, I can also export this or even customize the report with data from the contract? So we can treat this page a little bit like an Excel. I can build out this spreadsheet with any data I want to view and compare. So maybe the renewal date here, the notice clause, you'll see those will present on this page so I can compare that. We also can export. Export. So if we needed to send this to any stakeholders or anyone external, we can push this to Excel to access as well, as you can see here.

Finally, our system also allows customers to leverage a clause library. This is a great hook between the repository, the executed agreements, and the pre signature aspect.

So a lot of times our customers come across language they like in terms of language they've agreed to in the past. You can see here this assignment clause and this one contract, and they wanna use that in the future when drafting. You can simply highlight a clause from here and add it right to the library. You can name it, categorize it, have notes on when to use, and submit that as a clause version.

Within the system, you can track all those clauses and your library and playbook, so you can see different iterations of clauses, different fallbacks, and really have notes on when to use. And again, all these clauses can be pulled seamlessly into the presignature side. So when you're creating new agreements.