One of the most common questions we hear from our customers and prospects is whether products like ours can be built in-house or whether they need to be bought from a vendor like Ivo. And it’s a very good question. Many companies, particularly large technology companies, are used to building their own tools, which makes a lot of sense. These are companies with huge amounts of resources, the most talented engineers, and the technical know-how to build successful products. 

One thing we often hear from customers is that they have to go through a robust cost-benefit analysis when considering whether or not to buy these tools. Buying a legal AI solution is not easy right now. There are so many different vendors saying so many different things, and it’s important for legal professionals to make the right decision on which tools will solve the challenges they face. And, in order to select the right tool, contracting teams have to filter through the noise of the myriad of different solutions in the market.

There are three important considerations to think about when calculating whether the right approach is to build a legal tool in-house vs. buying from a vendor. They are:

  1. The cost-effectiveness of building vs buying
  2. The trustworthiness of an in-house tool vs one purchased from a vendor
  3. The technical maintenance of software in your company 

Figuring out the ways your organization would answer all of those questions will make the answer of whether to build or buy an AI legal solution more clear. 

Is it more cost effective to build or buy? 

Companies usually undergo a very robust cost-benefit analysis of whether to buy a software tool, and many, many organizations believe that they can build a tool with the right functionality for their contracting teams more efficiently and effectively than buying from a vendor. There are many factors that go into this economic decision. The choice to purchase software creates costs in the ongoing subscription fees, possible professional services, and additional licensing fees, whereas building in-house requires an upfront investment in development resources as well as the hidden opportunity cost. Will the business decide that it makes sense to divert engineering talent to creating a tool for contracting teams? How will those resources be prioritized? And what happens to the project if something else takes priority? Ultimately this decision rests on whether a tool can be procured at a lesser cost than the time and resources to build it in-house. 

Can you trust a legal AI tool built by a vendor? 

One of our customers told us, “It’s been a while since we’ve had to deal with something that is so new and so powerful and yet could be such a big mistake if not implemented properly.” Legal and contracting professionals need to be able to trust their AI tools; it is a professional necessity. A small mistake could present unacceptable risk. Sometimes companies have the perception that a tool built in-house is created with more sophisticated technology than tools built by external vendors, and will therefore be more accurate and more trustworthy. 

One of the things that we’re particularly proud of at Ivo is that our product is purpose-built for lawyers because lawyers are part of the custom implementation for every customer. We can therefore guarantee that our contract solutions will be accurate, trustworthy, and fit for purpose. Our contract intelligence solution, for example, has a 97% score against the CUAD dataset. 

How much does custom-built software cost to maintain? 

One of the thorniest challenges when it comes to software built in-house is the cost to maintain it. It’s an almost-universal problem; when the engineers who built custom software leave the company, they take their institutional knowledge with them, and there often isn’t documentation or community support that can answer questions or fix issues with the product. Important implementation decisions and key workarounds only exist in the developers’ memories, and when they’re gone, so too is that knowledge. The remaining teams have to struggle to comprehend undocumented code or unconventional design patterns without the context of why the technical decisions were made. And as the software ages, the problem gets worse. Integration with evolving business systems, security updates, and compatibility fixes become difficult without developers who understand the original code. None of the solutions are good: companies can hire an expensive consultant to rebuild the software or rebuild from scratch, both of which negate any cost savings of building in-house, or simply stopping the use of the tool altogether, which negates any benefit to adoption in the first place. 

In order to solve the build vs buy question, organizations must honestly figure out not just whether they can build the software today — a thorny question even in the most well-resourced organizations — but also whether or not they can maintain and support it for years to come, even as team members leave the company. Every business needs to ask themselves about the right place to allocate their resources. Is building and maintaining custom software a core strategic business function? Or does that divert valuable engineering resources away from the core business? Being able to clearly assess that question, with dedicated consideration to the factors above, will go a long way to solve the build vs. buy conundrum. 

One of the most common questions we hear from our customers and prospects is whether products like ours can be built in-house or whether they need to be bought from a vendor like Ivo. And it’s a very good question. Many companies, particularly large technology companies, are used to building their own tools, which makes a lot of sense. These are companies with huge amounts of resources, the most talented engineers, and the technical know-how to build successful products. 

One thing we often hear from customers is that they have to go through a robust cost-benefit analysis when considering whether or not to buy these tools. Buying a legal AI solution is not easy right now. There are so many different vendors saying so many different things, and it’s important for legal professionals to make the right decision on which tools will solve the challenges they face. And, in order to select the right tool, contracting teams have to filter through the noise of the myriad of different solutions in the market.

There are three important considerations to think about when calculating whether the right approach is to build a legal tool in-house vs. buying from a vendor. They are:

  1. The cost-effectiveness of building vs buying
  2. The trustworthiness of an in-house tool vs one purchased from a vendor
  3. The technical maintenance of software in your company 

Figuring out the ways your organization would answer all of those questions will make the answer of whether to build or buy an AI legal solution more clear. 

Is it more cost effective to build or buy? 

Companies usually undergo a very robust cost-benefit analysis of whether to buy a software tool, and many, many organizations believe that they can build a tool with the right functionality for their contracting teams more efficiently and effectively than buying from a vendor. There are many factors that go into this economic decision. The choice to purchase software creates costs in the ongoing subscription fees, possible professional services, and additional licensing fees, whereas building in-house requires an upfront investment in development resources as well as the hidden opportunity cost. Will the business decide that it makes sense to divert engineering talent to creating a tool for contracting teams? How will those resources be prioritized? And what happens to the project if something else takes priority? Ultimately this decision rests on whether a tool can be procured at a lesser cost than the time and resources to build it in-house. 

Can you trust a legal AI tool built by a vendor? 

One of our customers told us, “It’s been a while since we’ve had to deal with something that is so new and so powerful and yet could be such a big mistake if not implemented properly.” Legal and contracting professionals need to be able to trust their AI tools; it is a professional necessity. A small mistake could present unacceptable risk. Sometimes companies have the perception that a tool built in-house is created with more sophisticated technology than tools built by external vendors, and will therefore be more accurate and more trustworthy. 

One of the things that we’re particularly proud of at Ivo is that our product is purpose-built for lawyers because lawyers are part of the custom implementation for every customer. We can therefore guarantee that our contract solutions will be accurate, trustworthy, and fit for purpose. Our contract intelligence solution, for example, has a 97% score against the CUAD dataset. 

How much does custom-built software cost to maintain? 

One of the thorniest challenges when it comes to software built in-house is the cost to maintain it. It’s an almost-universal problem; when the engineers who built custom software leave the company, they take their institutional knowledge with them, and there often isn’t documentation or community support that can answer questions or fix issues with the product. Important implementation decisions and key workarounds only exist in the developers’ memories, and when they’re gone, so too is that knowledge. The remaining teams have to struggle to comprehend undocumented code or unconventional design patterns without the context of why the technical decisions were made. And as the software ages, the problem gets worse. Integration with evolving business systems, security updates, and compatibility fixes become difficult without developers who understand the original code. None of the solutions are good: companies can hire an expensive consultant to rebuild the software or rebuild from scratch, both of which negate any cost savings of building in-house, or simply stopping the use of the tool altogether, which negates any benefit to adoption in the first place. 

In order to solve the build vs buy question, organizations must honestly figure out not just whether they can build the software today — a thorny question even in the most well-resourced organizations — but also whether or not they can maintain and support it for years to come, even as team members leave the company. Every business needs to ask themselves about the right place to allocate their resources. Is building and maintaining custom software a core strategic business function? Or does that divert valuable engineering resources away from the core business? Being able to clearly assess that question, with dedicated consideration to the factors above, will go a long way to solve the build vs. buy conundrum.