Category Archives: Cloud Data

A.I. Bot ChatGPT Explains How Corporate Legal Can Streamline eDiscovery Processes

By John Patzakis

Over the weekend I was about to write a blog post on how corporate legal departments can streamline and improve their internal eDiscovery processes. I instead asked ChatGPT to write it. ChatGPT did a better job of it. So If anyone needs me this week, I will be at the beach.


Here is the full transcript:


My Prompt: Please write a memo explaining how corporate legal departments can streamline their eDiscovery processes to reduce costs and improve compliance.


Response from ChatGPT:

Subject: Streamlining eDiscovery Processes for Corporate Legal Departments

Dear All,

As technology continues to advance and the amount of electronic data generated by companies grows, the eDiscovery process can become increasingly complex and costly. However, there are steps that corporate legal departments can take to streamline their eDiscovery processes and reduce costs while also improving compliance.
1. Invest in eDiscovery Technology Solutions: Utilizing technology solutions, such as automated data collection and review tools, can help reduce the time and cost associated with manual review processes. These solutions can also improve accuracy and consistency in data collection and review, reducing the risk of non-compliance.
2. Establish Clear Protocols and Guidelines: Having clear protocols and guidelines in place for data collection and preservation will help ensure that relevant data is preserved and collected in a timely manner, reducing the risk of spoliation and ensuring compliance with legal obligations.
3. Employee Training: Regular training for employees on best practices for managing electronic data will help ensure that data is properly preserved and collected, reducing the risk of non-compliance.
4. Regular Process Reviews: It is important to regularly review and update processes to ensure they align with changes in regulations and technology. This will help ensure that eDiscovery processes remain efficient and effective, reducing costs and improving compliance.
5. Consider Alternative Service Providers: Utilizing alternative service providers, such as managed eDiscovery service providers, can help reduce costs while also improving compliance. Negotiating service level agreements that meet both cost and compliance goals will ensure that eDiscovery initiatives are managed in a cost-effective and compliant manner.
6. Utilize Project Management Techniques: Using project management techniques, such as setting clear goals, tracking progress, and monitoring budgets, will help keep eDiscovery initiatives on track and within budget, reducing costs and improving compliance.
In conclusion, streamlining eDiscovery processes can help reduce costs and improve compliance. By utilizing technology solutions, establishing clear protocols and guidelines, training employees, regularly reviewing processes, considering alternative service providers, and utilizing project management techniques, corporate legal departments can ensure that their eDiscovery processes are efficient and effective.

If you have any questions or would like to discuss these recommendations further, please do not hesitate to reach out.

Best regards,
[Your Name]

Couldn’t have said it better myself. And if you agree with ChatGPT’s recommendation to invest in automated collection technologies to reduce costs and reduce the risk of non-compliance, please see this information about our X1 Enterprise Collect platform.

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Filed under Best Practices, Cloud Data, Corporations, eDiscovery, Enterprise eDiscovery, ESI

Move to the Left and Targeted Collection Featured Widely as a Key 2023 eDiscovery Trend

By John Patzakis

It is prediction season for trends in the eDiscovery space for 2023. While many good eDiscovery scribes have published their prognostications in recent days, the annual predictions and overall analysis from Doug Austin in eDiscovery Today are invariably insightful. As a top industry analyst, Austin is in constant contact with eDiscovery executives and professionals and thus has a good finger on the industry pulse.

One of his key predictions this year, which notably appears in several trending 2023 forecasts, centers around the upstream focus on information governance and targeted collection. “I’m hearing more legal and eDiscovery professionals than ever talk about the importance of information governance, early data assessment (EDA) and targeted collections in discovery,” reports Austin, who then poses a very good question about the ramifications of this trend: “What happens when eDiscovery professionals are no longer routinely collecting the entire data corpus of custodians to sort out downstream? The growth of data for eDiscovery hosting providers to host slows dramatically – which jeopardizes growth in hosting revenue that is based on gigabytes (GBs) online.”

There is a lot going on in terms of takeaways from this paragraph. The “collect everything and sort it out later” is still the dominant model for service providers and, as Austin points out, it can be difficult for them to pivot from this economic model. However, this highlights a key reason why many in house legal departments are now routinely deploying in-house collection and EDA solutions. There are significant cost savings and efficiencies to be gained by narrowing the data funnel upstream before the data is sent out for data hosting. And this approach is favored by the courts in applying the principles of proportionality now ensconced in the Federal Rules of Civil Procedure, with a wealth of case law establishing that ESI preservation efforts should be reasonable, proportionate, and targeted to only relevant information, as opposed to being overly broad and unduly burdensome.

While there is keen awareness of proportionality in the legal community, attaining the benefits requires the ability to operationalize workflows as far upstream in the eDiscovery process as possible. The case law and the Federal Rules provide that the duty to preserve only applies to potentially relevant information, but unless you have the right operational processes in place, you’re losing out on the ability to attain the benefits of proportionality. And with the proliferation of enterprise cloud data sources, it’s important that holistic and targeted collections encompass Microsoft 365 data as well as laptops and file shares.

To answer this unmet critical need, X1 has added MS 365 data connectors to our X1 Enterprise Collect platform. X1 Enterprise Collect provides users the unique ability to search and collect MS 365 data in-place. X1’s optimized approach of iterative search and targeted collection enables organizations to apply proportionality principles across both cloud and on-premise data sources with clear and consistent results for effective eDiscovery. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%).

The X1 Enterprise Collect Platform is available now from X1 and its global channel network in the cloud, on-premise, and with our services available on-demand. For a demonstration of the X1 Enterprise Collect Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/x1-enterprise-collect-platform.

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Filed under Best Practices, Cloud Data, Corporations, eDiscovery, Enterprise eDiscovery, Information Governance, Preservation & Collection, proportionality

Significant Microsoft 365 eDiscovery Challenges Require a New Approach

By John Patzakis

The adoption of cloud-based Microsoft 365 (“MS 365”) by enterprises continues to grow exponentially, with the company recently reporting 300 million monthly active users, and the addition of over 100 petabytes of new content each month. There is no question that MS 365 is now a major data source for eDiscovery, second only to file-shares and laptops, and as such provides challenges to every legal and eDiscovery practitioner.

While MS 365 includes built-in eDiscovery tools in the Security and Compliance Center, many users look to third party alternatives due to the high cost, perceived concerns over the accuracy of search results, and other key challenges. However, most non-MS eDiscovery tools collect from MS 365 by simply making bulk copies of data associated with individual accounts, and then attempting to transfer that data en masse to their own proprietary processing and/or review platform. This problematic approach is counter-productive to the very purpose of why you put data in the cloud.

Such an effort is very costly, time consuming, and inefficient for many reasons. For one, this bulk transfer triggers data transfer throttling by Microsoft, causing significant time delays. But the main problem is that clients who are investing in MS 365 do not want to see all their data routinely exported out of its native environment every time there is an eDiscovery or compliance investigation. Organizations are fine with a targeted set of potentially relevant ESI leaving MS 365. What they do not want is a mass bulk export of terabytes of data at great expense because eDiscovery and processing tools need to first broadly ingest that data in their disparate platform in order to even begin the indexing, culling and searching process.

Additionally, organizations, especially larger enterprises, rarely house all or even most of their data within MS 365, with hybrid cloud and on-premise environments being the norm. MS 365 eDiscovery tools can only address what is contained within MS 365. Any on-premise data, including on-premise Microsoft sources (SharePoint, Exchange) cannot be readily consolidated by MS 365, and neither can data from other cloud sources such as Google Drive, Box, Dropbox, etc. And of course, laptops and file-shares are critical to eDiscovery collections and are also not supported by the MS 365 eDiscovery tools, with Microsoft indicating that they do not have any plans to address all of these non-MS 365 data sources.

So, eDiscovery software providers need to have a good process to perform unified search and collection of MS 365 and non-MS 365 sources. To achieve requisite efficiency and the minimization of data transfer, this process should be based upon a targeted search and collection in-place capability, and not simply involve mass export of data out of MS 365 for downstream processing and searching.

To answer this unmet critical need, X1 has added MS 365 data connectors to our X1 Enterprise Collect platform. X1 Enterprise Collect provides users the unique ability to search and collect MS 365 data in-place. X1’s optimized approach of iterative search and targeted collection enables organizations to apply proportionality principles across both cloud and on-premise data sources with clear and consistent results for effective eDiscovery. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%).

The X1 Enterprise Collect Platform is available now from X1 and its global channel network in the cloud, on-premise, and with our services available on-demand. For a demonstration of the X1 Enterprise Collect Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/x1-enterprise-collect-platform.

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Filed under Best Practices, Cloud Data, Corporations, Data Audit, ECA, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, ESI, Information Governance, Information Management, OneDrive, Preservation & Collection, SharePoint

Important SaaS Architecture Considerations for Legal Tech Software

by Kunjan Zaveri

With nearly all eDiscovery software now being offered on a SaaS basis, the cloud architecture decisions supporting the vendor’s platform are pivotal. Decisions on architecture design can lead to either very successful or very poor outcomes. The right architecture depends on the company’s SaaS delivery strategy, their customer profile and size, and the volume and nature of their anticipated transactions. These considerations are especially important in the legal tech space, which has some unique requirements and market dynamics such as heighted security and customization for large clients, and channel support (requiring platform portability), which are generally not as relevant to general SaaS architecture considerations.

At a high level, it is important to understand the two main SaaS architectures: multi-tenancy and single-tenancy. In cloud computing, tenancy refers to the allocation of computing resources in a cloud environment. In SaaS, tenancy is categorized into two formats: single-tenant SaaS and multi-tenant SaaS. In the single-tenant SaaS environment, each client has a dedicated infrastructure. Single-tenant products can’t be shared between clients and the buyer can customize the software according to their requirements. Multi-tenancy is an architecture where a single instance of a software application serves multiple customers. In a multi-tenant SaaS environment, many organizations share the same software and usually the same database (or at least a portion of a common database) to save and store data.

Single-tenancy and multi-tenancy SaaS each have their advantages and disadvantages, and the selection of either approach by a legal tech SaaS vendor should depend on their overall product and go-to-market strategy. Here are some of the advantages of a single-tenancy architecture:

1. Improved Security

With single-tenancy, each customer’s data is completely isolated from other customers with fewer and more trusted points of entry. The result is better overall security from outside threats and the prevention of one customer accessing another’s sensitive information, either intentionally or inadvertently.

2. Reliable Operations and Individual Tenant Scalability

Single-tenant SaaS architectures are considered more reliable as there is not a single point of failure that can affect all customers. For example, if one client uploads a massive amount of corrupt data that taxes resources and crashes the system, it won’t affect another clients’ instances. Single-tenancy is actually more scalable within an individual client instance, while multi-tenancy can better scale the addition and management of many customers.

3. Customization

Many large customers need specific features or unique security measures that require custom development, which can be very difficult in a multi-tenancy environment. Companies that use single-tenancy architecture can upgrade their services individually. Rather than waiting for the software provider to launch a universal update, users can update their accounts as soon as the download is available or decline patches that are not needed by a specific customer.  

4. Portability

With single-tenancy, a vendor can host their platform in their own SaaS environment, a channel partner’s environment, or enable their customers to install the solution behind their firewall or in their private cloud. Multi-tenancy SaaS does not allow for this flexibility.

Multi-tenant SaaS Advantages

Multi-tenancy is commonly utilized as most SaaS offerings are consumer or otherwise high-volume commoditized offerings, which necessitates such an architecture. Here are some of the key advantages of multi-tenant SaaS architecture over single-tenant:

1. Lower Costs

Since computing services are all shared under a multi-tenant architecture, it can cost less than a single-tenant structure. Scaling across the customer base is easier as new users utilize the same uniform software and resources as all the other customers.

2. Efficient Resources Spread Across all Customers

Because all resources are shared and uniform, multi-tenant architecture uses resources that, once engineered, offer optimum efficiency. Since it’s a changing environment where resources are accessed simultaneously, multi-tenant SaaS software needs to be engineered to have the capacity for powering multiple customers at once.

3. Fewer Maintenance Costs

Maintenance costs are usually associated with a SaaS subscription and aren’t passed through to the customer or incurred by the channel partner like with a single-tenant structure.

4. Shared Data Centers

Unlike a single-tenant environment, a vendor doesn’t have to create a new instance within the datacenter for every new user. Customers have to use a common infrastructure that removes the need to continually add partitioned instances for each new tenant.

So which architecture is the right one for a legal tech SaaS vendor? It completely depends on the company’s strategy, pricing, and nature of the offering. To illustrate this point, consider the examples of two hypothetical legal tech SaaS vendors: Acme and Widget.

Acme provides do it yourself data processing on a high-volume, low-cost basis, handling about 700 matters a week at an average project value of $400. Acme’s customer base is primarily small to medium size law firms and service providers who have multiple projects on different cases over the course of a year. Acme’s clients do not want to fuss with hardware or any software maintenance requirements.

Widget offers an enterprise-grade compliance and security data analytics platform, sold at an average sale price (ASP) of $400,000, but as high as $2 million for a dedicated annual license. Widget has 32 active enterprise customers and hopes to grow to 70 customers in three years with an even higher ASP. About a third of Widget’s clients prefer that Widget host the solution in Widget’s cloud instance. Another group of clients are large financial institutions that, for security and governance purposes, insist on self-hosting the platform in their own private cloud. The rest are instances sold through channel partners who prefer to host the platform themselves and provide value added services. Many Widget customers have particularized compliance requirements and other unique circumstances that require customization to support their needs.

For Acme, the correct choice is multi-tenancy. Acme offers a commoditized SaaS service, and it needs a high volume of individual customers to drive more transactional revenue growth. A single-tenancy architecture would prevent the company from scaling, would be too expensive, and unmanageable. However, some legal tech companies who have opted for this architectural approach have made the mistake of pursuing a more low-market commoditized strategy without making the initial considerable investment in engineering expertise and resources to build such an architecture.

In contrast, single-tenancy is the optimal architecture choice for Widget. While single-tenancy cloud is slightly more challenging to support, Widgets’ premium enterprise offering requires portability for the channel and rigorous security minded clients as well as customization, and thus is a clear fit for single-tenancy. In the future, Widget may have closer to a thousand customers or be acquired by a much larger company that will want to deploy the solution to their extensive client base. It would be a good idea for Widget to architect their single-tenancy platform in a manner, such as employing microservices, that will allow it to readily port it to a multi-tenancy environment when warranted.

So, for legal tech executives, the question to ask is whether your strategy and product offering is more in line with Widget or Acme. But the bottom line is to make sure your strategy drives your choice of architecture and not the other way around.

Kunjan Zaveri is the Chief Technology Officer of X1. (www.x1.com)

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Filed under Best Practices, Cloud Data, eDiscovery, Enterprise eDiscovery, SaaS

Usage-Based Pricing Model Increasingly Driving eDiscovery Software Growth

by John Patzakis

Legal Tech software CEOs often grapple with two competing challenges: Growing revenue in a manner that supports how customers buy their products for their individual cases, while at the same time maximizing shareholder value by recording recurring revenue, which the investor community typically favors. Recurring revenue generally comes in the form of fixed annual or monthly subscription licenses.

However, eDiscovery software providers are increasingly aligning their SaaS pricing strategy with the amount of product usage their customers consume. Instead of paying a fixed rate, the pricing is based upon actual usage. The benefits of this approach include a shorter and simpler purchasing process and increased customer satisfaction and retention.

In the eDiscovery space, customers often prefer to pay by “matter”, i.e., per lawsuit or legal case. Law firms and service providers typically utilize eDiscovery SaaS software specific to an individual case on a pass-through cost basis, where their end-client ultimately pays for the services. In the case of corporate law departments, oftentimes the organization prefers to purchase annual subscriptions for eDiscovery and apply the license over multiple matters in the course of the year. However, such buying decisions vary by organization, with corporate counsel sometimes deferring eDiscovery workflow and tech decisions to their law firms, which favors a usage-based pricing model.

While tech companies with recurring annual term revenue will typically garner higher valuations, eDiscovery software firms with usage-based pricing models are now seeing similarly elevated valuations. Investors are recognizing the very unique economics and buying dynamics specific to the eDiscovery software space. But it is incumbent on eDiscovery software execs, their investment bankers, and board members to educate the broader market on this dynamic unique to the eDiscovery space. In some situations, investors new to this space attempt to apply a steep discount to usage-based SaaS revenue, as it doesn’t fit in with their “paint by the numbers” ARR models. Rick Weber, Managing Director of Legal Tech investment banking firm Arbor Ridge Partners notes, “while the usage model is not annual recurring, it is ‘monthly re-occurring,’ and thus projections and modeling can be made based on company history and industry norms and should be treated like ARR contracts.”

In fact, usage-based pricing is now gaining wider acceptance in the broader SaaS software market beyond legal tech. Cloud infrastructure providers AWS and Microsoft Azure are obvious examples of successful usage-based pricing strategies, but many startups and medium sized companies have successfully implemented the model as well. While usage-based revenue may seem less predictable compared to other pricing models, companies using this model are often growing faster, retaining more revenue, and valued at high revenue multiples. But again, this realization requires a closer look by investors and an intelligent education effort by the companies and their advisors.

One caveat for investors is to confirm that the value of the SaaS usage offering is mostly based upon proprietary software tech versus services that are dressed up as SaaS. Some eDiscovery service providers attempt to position their services as SaaS, without a true standalone propriety software component. An analysis of the cost of sales/gross margins and assessment of the actual proprietary nature of the software is determinative. Gross margins should be at least 80 percent. And while some services are often provided in conjunction with a SaaS usage-based offering, a qualifying factor is whether the software is also separately offered purely as a traditional license to end users without any services required, which is how many customers will opt to buy.

But for true usage-based SaaS offerings, the flexibility, simplicity and supporting of legal customers purchasing dynamics are key to rapid growth and customer satisfaction. As summarized by Weber, “many of the PE firms and investors that have made big bets on such companies in recent years seem to understand the nuance and opportunity while many still lag behind and simply need to think outside of their box.”

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Filed under Best Practices, Cloud Data, Corporations, eDiscovery, Enterprise eDiscovery, Information Management, SaaS, Uncategorized