CORRESP 1 filename1.htm

Confidential Treatment Requested by Arrowroot Acquisition Corp.

 

Certain confidential information in this letter has been omitted and provided separately in an unredacted version to the Securities and Exchange Commission. Confidential treatment has been requested pursuant to 17 C.F.R. Section 200.83 with respect to the omitted portions, which are identified in this letter as filed via EDGAR with a placeholder identified by the mark “[***].”

 

 

Goodwin Procter LLP

100 Northern Avenue
Boston, MA 02210

 

goodwinlaw.com

 

+1 617 570 1000

 

December 7, 2023

 

BY EDGAR

 

Division of Corporation Finance

Office of Technology

U.S. Securities and Exchange Commission

100 F Street, NE

Washington, D.C. 20549-3628

 

Attention: Amanda Kim
  Stephen Krikorian
  Charli Gibbs-Tabler
  Jan Woo

 

Re: Arrowroot Acquisition Corp.
  Registration Statement on Form S-4
 

Originally Filed September 5, 2023

Amendment No. 1 to Registration Statement on Form S-4

Filed November 6, 2023

  File No. 333-274333

 

Ladies and Gentlemen:

 

This letter is submitted on behalf of Arrowroot Acquisition Corp. (the “Company”) in response to comments from the staff of the Division of Corporation Finance (the “Staff”) of the Securities and Exchange Commission in a letter dated November 29, 2023 (the “Comment Letter”) with respect to the above-referenced Registration Statement on Form S-4 initially filed on September 5, 2023, as amended by the Amendment No. 1 to Registration Statement on Form S-4 filed on November 6, 2023 (the “Registration Statement”). The Company is concurrently submitting Amendment No. 2 to the Registration Statement (the “Amendment No. 2”), which includes changes in response to certain of the Staff’s comments.

 

For your convenience, the Staff’s numbered comments set forth in the Comment Letter have been reproduced in bold with responses immediately following each comment. Unless otherwise indicated, page references in the descriptions of the Staff’s comments refer to the Registration Statement, and page references in the responses below refer to Amendment No. 2. Defined terms used herein but not otherwise defined herein have the meanings given to them in Amendment No. 2.

 

The responses provided herein are based upon information provided to Goodwin Procter LLP by the Company.

 

 

 

 

 

 

Page 2

 

Amendment No. 1 to Registration Statement on Form S-4

 

Customers, page 201

 

  1. You have defined and disclosed the number of contracted customers and licensed users for the periods presented, as well as defined enterprise end customers. Please disclose the number of enterprise end customers for the periods presented.

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that iLearningEngines does not manage or monitor its business based on the number of enterprise end customers, as such number varies in a fiscal period due to changes in the mix of solutions used by iLearningEngines’ contracted customers. In addition, iLearningEngines’ enterprise end customers include iLearningEngines’ VARs’ customers. Accordingly, iLearningEngines does not track enterprise end customer growth on a quarterly basis because enterprise end customers count by quarter is too difficult to determine with reasonable certainty within reporting timeframes.

 

iLearningEngines monitors and intends to disclose recurring revenue growth, contracted customers growth and licensed user growth because iLearningEngines believes they are better indicators of iLearningEngines’ business and consistent with the ways in which iLearningEngines monitors its business internally.

 

iLearningEngines Management’s Discussion and Analysis of Financial Condition and Results of Operations

Key Performance Metrics, page 220

 

  2. Your response to prior comment 9 explains that Annual Recurring Revenue and Net Dollar Retention helps provide information as to the performance of iLearningEngines’ recurring subscription revenue base and impact of revenues from existing customers. However, your disclosure on page 221 explains that the ability to attract and engage new customers is also one of the key factors affecting your performance. In light of this disclosure, please tell us what consideration was given in disclosing the number of customers for the periods presented by new and existing customers. Refer to SEC Release No. 33-10751.

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that it has revised the disclosure on page 203 of Amendment No. 2 to include the number of new contracted customers for each period presented in response to the Staff’s comment. The Company further advises the Staff that it has not included a breakdown of new and existing licensed users because iLearningEngines frequently upsells new use cases inside enterprises (e.g. iLearningEngines implements a new site/instance for different departments or businesses within an enterprise). As such, tracking unique licensed user count changes are too difficult to determine with reasonable certainty within reporting timeframes.

  

  3. Your response to prior comment 11 and revisions to the disclosures on page 220 explain that you do not exclude prior year contracted customers that were not retained in the current year. However, your response to prior comment 9 explains that Net Dollar Retention helps provide information as to the performance of iLearningEngines’ recurring subscription revenue base and impact of revenues from existing customers. Please tell us how including prior year contracted customers that were not retained in the current year provides useful information on existing customers given that those customers have not been retained.

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that iLearningEngines includes prior period contracted customers that were not retained in the current year in the calculation of Net Dollar Retention as this formulation captures the impact of any customer churn. iLearningEngines believes this metric provides useful information about its overall ability to retain and grow its customer base while reflecting the impact of any customer losses. The Company believes this definition of Net Dollar Retention provides investors with a more fulsome picture of iLearningEngines’ customer relationships than a definition without the effect of customer losses would provide.

 

 

 

 

 

 

Page 3

 

Comparison of Six Months Ended June 30, 2023 and 2022, page 225

 

  4. In response to prior comment 15, you have revised your disclosure to state that revenue increased due to thirteen new contracts. However, your disclosure continues to state that the cost of revenue increased due to fourteen new contracts. Please revise or advise.

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that it has revised the disclosure on pages 227, 230 and 232 of Amendment No. 2 to discuss changes in global revenue prior to a discussion of changes by region. This change allows the reader to reconcile the total change in number of contracts listed by region to those discussed on a global basis in the cost of revenue section.

 

Notes to Consolidated Financial Statements

Combined software license and maintenance, page F-15

 

5.Your response to prior comment 18 states that you determine SSP for the combined software license and maintenance performance obligation using the residual approach because iLearningEngines sells the iLearningEngines AI platform and related maintenance services to different customers for a broad range of amounts, such that there is not a discernible standalone selling price from past transactions. Please provide a comprehensive, quantitative discussion of such variability to support your conclusion. As part of your response, please quantify the amount of revenue recognized for where the residual method is used. Refer to ASC 606-10-32-34.

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that sales of the iLearningEngines AI platform involve the transfer to the customer of a combined software license and maintenance performance obligation, the standalone selling price (“SSP”) of which is determined using the residual approach. Under ASC 606-10-32-34(c), an entity may use the residual approach to estimate SSP by referencing the total transaction price less the sum of the observable standalone selling prices of other goods or services promised in the contract. The residual approach may only be used if one of the following criteria is met:

 

1.The entity sells the same good or service to different customers (at or near the same time) for a broad range of amounts (that is, the selling price is highly variable because a representative standalone selling price is not discernable from past transactions or other observable evidence).

 

2.The entity has not yet established a price for that good or service, and the good or service has not previously been sold on a standalone basis (that is, the selling price is uncertain).

 

iLearningEngines has concluded that the selling price of the combined software license and maintenance performance obligation is highly variable and therefore that the use of the residual approach to estimate the SSP of the combined software license and maintenance performance obligation is appropriate.

 

When iLearningEngines sells its AI platform and related maintenance services to customers, it presents the price of the license and maintenance to the customer by quoting both a price per user per month and per expert per month. There are a number of factors that affect the per user and per expert prices charged to different customers including, but not limited to, the customer’s bespoke products which the AI platform is replacing, the complexity of the use case for which the AI platform is meant to solve, the number of customer systems into which the platform is integrated, the number of dedicated support personnel required to provide maintenance services, and the outcome of contract negotiations with the customer. Due to the novelty of AI products, iLearningEngines does not have an existing price list or competitor pricing to benchmark its pricing against. Rather, iLearningEngines creates a per user and per expert price customized to the customer’s specific use case and the customer’s budget. The high degree of variability in the per user and per expert prices per month charged to different customers served as the basis for using the residual approach.

 

 

 

 

 

 

Page 4

 

iLearningEngines’ evaluation of whether the pricing for the license and maintenance is highly variable was primarily a quantitative approach involving an analysis of its license and maintenance pricing across all active contracts from 2018 to 2023 (inclusive of renewals), as iLearningEngines has a history of charging different customers a broad range of amounts for the license and maintenance. iLearningEngines considered the discussion in the American Institute of Certified Public Accountant’s Audit & Accounting Guide, Revenue Recognition, Chapter 9—Software Entities, paragraph 9.4.05:

 

In order to use the residual approach for the software license in the contract, an entity will first need to evaluate whether the software license sold to the customer is the “same” software sold to other customers and whether the selling price of the same license has been highly variable or uncertain in other transactions.

 

With respect to whether the software license is the “same” software licensed to other customers, iLearningEngines considered the various factors noted in paragraph 9.4.06, i.e.,

 

whether the license is perpetual or time-based (and, if time-based, the duration of the license term, for example, three years versus seven years), exclusive or nonexclusive, or restricted regarding permitted uses.

 

iLearningEngines noted that the platform is typically licensed to customers for multi-year terms and that there were no significant differences in license attributes from customer to customer. iLearningEngines further considered whether any stratification of the customer population was appropriate, noting that ASC 606-10-32-32 states that the “best evidence of a standalone selling price is the observable price of a good or service when the entity sells that good or service separately in similar circumstances and to similar customers” (emphasis added). iLearningEngines sells its AI platform to customers in several different industry sectors, but it did not identify significant differences in pricing characteristics when examining pricing data by customer industry sector. iLearningEngines also analyzed whether stratifying its customer population by channel contracts, those customers contracted through iLearningEngines’ channel partners (“Channel Contracts”), and direct contracts, those customers who have contracted directly with iLearningEngines (“Direct Contracts”), would result in differences in the variability of pricing. Channel Contracts are those contracts in which a channel partner is iLearningEngines’ customer, while Direct Contracts are those contracts in which the end customer is iLearningEngines’ customer. There was not a significant difference in the variability of pricing between Channel Contracts and Direct Contracts. However, iLearningEngines determined that presenting its analysis on the basis of all contracts, as well as Channel Contracts and Direct Contracts, would be useful for illustrative purposes.

 

Accordingly, the tables below reflect iLearningEngines’ analysis of pricing on a per user and per expert pricing per month, with customer contracts stratified by (1) Channel Contracts and (2) Direct Contracts. The analysis was performed using a population of all past and current customer contracts. iLearningEngines utilized the bell-shaped curve approach to examine the per user and per expert per month pricing in its contracts by identifying a median price in the relevant population, then determining whether prices are sufficiently clustered within a narrow range.

 

 

 

 

 

 

Page 5

 

iLearningEngines considered the following discussion in Question 6-3 in EY’s Financial Reporting Developments publication, Revenue from contracts with customers (ASC 606) (issued September 2023), with respect using a range of observed prices to determine a standalone selling price:

 

An estimate of the standalone selling price could be established when a large portion of the standalone sales fall within a narrow range (e.g., when the entity could demonstrate that the pricing of 80% of the standalone sales fall within a range of plus or minus 15% from the midpoint of the range), since this approach is consistent with the standard’s principle that an entity must maximize its use of observable inputs.

 

While the use of a range may be appropriate for estimating the standalone selling price, we believe that some approaches to identifying this range do not meet the requirements of the guidance. For example, it wouldn’t be appropriate for an entity to determine a range by estimating a single price point for the standalone selling price and then adding an arbitrary range on either side of that point estimate or by taking the historical prices and expanding the range around the midpoint until a significant portion of the historical transactions fall within that band.

 

To illustrate, assume that an entity determines that 60% of its historical prices fall within +/-15% of [***] (i.e., [***] to [***]). However, the entity determines that 80% of the historical prices fall within +/- 30% of [***] and proposes a range for the standalone selling price estimate of [***] to [***]. The wider the range necessary to capture a high proportion of historical transactions, the less relevant the range is in terms of providing a useful data point for estimating standalone selling prices.

 

iLearningEngines’ approach in the analysis below was to determine the median price per user and per expert and then to identify how many contracts fall within a range of +/- 20% of the median. iLearningEngines then expanded the range by 10% increments to determine how many transactions cumulatively fall within those additional ranges. The analysis shows that the per user and per expert pricing for the license and maintenance across customers is highly variable, as the per user and per expert prices for the contracts are not closely distributed around the median prices but rather fall within a wide range of amounts. As noted by EY, “the wider the range necessary to capture a high proportion of historical transactions, the less relevant the range is in terms of providing a useful data point for estimating standalone selling prices.” Also, a comparison of the results for the Direct Contracts and Channel Contracts demonstrates similar variability in the pricing across different types of customers that are purchasing the same underlying software license and related maintenance services.

 

All Contracts

 

Per User Pricing

 

Minimum  $[***] 
Maximum  $[***] 
Median  $[***] 

 

Range within +/-X%
of median		  Cumulative contracts
within the range		  Cumulative percentage of
contracts within the range
20%  [***]  [***]
30%  [***]  [***]
40%  [***]  [***]
50%  [***]  [***]
60%  [***]  [***]
70%  [***]  [***]
80%  [***]  [***]
90%  [***]  [***]
Outside 90%  [***]  [***]

 

 

 

 

 

 

Page 6

 

Per Expert Pricing

 

Minimum  $[***] 
Maximum  $[***] 
Median  $[***] 

 

Range within +/-X%
of median		  Cumulative contracts
within the range		  Cumulative percentage of
contracts within the range
20%  [***]  [***]
30%  [***]  [***]
40%  [***]  [***]
50%  [***]  [***]
60%  [***]  [***]
70%  [***]  [***]
80%  [***]  [***]
90%  [***]  [***]
Outside 90%  [***](1)  [***]

 

 

 

(1)One of the channel customer contracts does not include experts and thus only has per user pricing. As a result, the total number of contracts for the per expert analysis of All Contracts and Channel Contracts is [***] and [***], respectively, compared to [***] and [***] contracts for the per user analysis of All Contracts and Channel Contracts, respectively.

 

As noted in the analysis of all contracts noted above, the percentage of contracts that are priced within +/-20% of the median prices for per user and per expert prices is only 41% and 40%, respectively, which is not very relevant in terms of providing a useful data point for estimating standalone selling prices. Further, the range must be expanded to +/-80% and +/-70%, respectively, to include over 70% of the transactions. As a result, iLearningEngines determined that its pricing of its combined software license and maintenance performance obligation is highly variable and that it is appropriate to use the residual approach to determine the standalone selling price of that performance obligation.

 

 

 

 

 

 

Page 7

 

When applying the residual approach, iLearningEngines also considers the guidance in BC 273 of ASU 2014-09 for each contract and evaluates whether the outcome of the residual approach would allocate an unrealistic amount to the software license and maintenance. To date, the amount allocated to the combined software license and maintenance performance obligation has been reasonable and realistic, as the outcome does not result in no, or very little, consideration being allocated to the software license and maintenance in the transaction. As a result, iLearningEngines has not been required to use a different estimation approach to determine a standalone selling price for this performance obligation in its historical transactions.

 

For the years ended December 31, 2022, 2021, and 2020, iLearningEngines recognized $293.3 million, $212.4 million, and $131.1 million, respectively, of combined software license and maintenance revenues using the residual approach.

 

The analyses of the Direct Contracts and Channel Contracts follow. However, iLearningEngines does not believe that these stratifications of its customer population affect its conclusion with respect to the applicability of the residual approach noted above.

 

Direct Contracts

 

Per User Pricing

 

Minimum  $[***] 
Maximum  $[***] 
Median  $[***] 

 

Range within +/-X%
of median		  Cumulative contracts
within the range		  Cumulative percentage of
contracts within the range
20%  [***]  [***]
30%  [***]  [***]
40%  [***]  [***]
50%  [***]  [***]
60%  [***]  [***]
70%  [***]  [***]
80%  [***]  [***]
90%  [***]  [***]
Outside 90%  [***]  [***]

 

 

 

 

 

 

Page 8

 

Per Expert Pricing

 

Minimum  $[***] 
Maximum  $[***] 
Median  $[***] 

 

Range within +/-X%
of median		  Cumulative contracts
within the range		  Cumulative percentage of
contracts within the range
20%  [***]  [***]
30%  [***]  [***]
40%  [***]  [***]
50%  [***]  [***]
60%  [***]  [***]
70%  [***]  [***]
80%  [***]  [***]
90%  [***]  [***]
Outside 90%  [***]  [***]

 

Channel Contracts

 

Per User Pricing

 

Minimum  $[***] 
Maximum  $[***] 
Median  $[***] 

 

Range within +/-X%
of median		  Cumulative contracts
within the range		  Cumulative percentage of
contracts within the range
20%  [***]  [***]
30%  [***]  [***]
40%  [***]  [***]
50%  [***]  [***]
60%  [***]  [***]
70%  [***]  [***]
80%  [***]  [***]
90%  [***]  [***]
Outside 90%  [***]  [***]

 

Per Expert Pricing

 

Minimum  $[***] 
Maximum  $[***] 
Median  $[***] 

 

Range within +/-X%
of median		  Cumulative contracts
within the range		  Cumulative percentage of
contracts within the range
20%  [***]  [***]
30%  [***]  [***]
40%  [***]  [***]
50%  [***]  [***]
60%  [***]  [***]
70%  [***]  [***]
80%  [***]  [***]
90%  [***]  [***]
Outside 90%  [***]  [***]

 

 

 

 

 

 

Page 9

 

  6. We note that in your response to prior comment 19 you explain that in some cases the Technology Partner is your customer. Please clarify whether you will provide the maintenance services to the Technology Partner in these arrangements. In this regard, indicate whether the Technology Partner also purchases support services. If so, clarify whether your employees are providing that service. In cases where the end user is the customer, explain how you considered whether Technology Partner is the principal in providing the support services to the customers. In this regard, we note that substantially all the cost of revenue and operating expenses represents reimbursements to the Technology Partner.

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that all of the parties considered to be iLearningEngines’ customers in its revenue contracts, including the Technology Partner, receive the same goods and services from iLearningEngines, i.e., the combined software license and maintenance performance obligation. The maintenance services included in that performance obligation are performed by iLearningEngines employees and various outsourced resources, including resources from the Technology Partner. There are various types of services included in the maintenance services, including knowledge work (i.e., product data fixes, root cause analysis, hot fixes and product issue resolution & product releases), data management (application support related to administration, configuration, integrations and business workflow definition), other types (content support including authoring of content, review of AI augmented content, publishing of content and linking new content repositories for content ingestion), and lower-level support (helpdesk, issue triage and basic L1 support). The knowledge work is performed by iLearningEngines’ employees.  The portion of the maintenance services that may be outsourced is data management and lower-level support. The outsourced resources perform these portions of the maintenance services under the oversight of iLearningEngines employees who have the know-how for the products.

 

With respect to arrangements in which the customer is the end user, and the Technology Partner is involved in providing the support services, iLearningEngines considered the principal-agent guidance in ASC 606, as follows:

 

●iLearningEngines determined that the specified goods or services provided to the customer are the combined software license and maintenance services.

 

●iLearningEngines controls the combined software license and maintenance services before they are transferred to the customer. iLearningEngines notes that, similar to the discussion in ASC 606-10-55-37A(c), it has combined the maintenance services it obtains from the Technology Partner, or other third party, with the software license to create the combined output that is the specified good or service.

 

●iLearningEngines further considered the indicators of control in ASC 606, noting that it is primarily responsible for providing the specified good or service, as the customer looks to iLearningEngines for satisfaction of the performance obligation. iLearningEngines has complete discretion in determining which resources will be utilized to provide services to a customer, e.g., iLearningEngines employees or outsourced resources, and has the ability to replace resources during the term of a contract. In addition, iLearningEngines supervises all outsourced resources. iLearningEngines does not have any minimum commitments with the Technology Partner related to the use of its resources. iLearningEngines has full discretion in determining the price of the good or service to the customer.

 

 

 

 

 

 

Page 10

 

5. Technology Partner, page F-40

 

  7. We note that on page 65, you disclose that as of August 2023, [you] had 92 fulltime employees and 407 contract employees globally. Please clarify whether the contract employees are provided by the Technology Partner. Please describe their function and clarify how their compensation is reported in your Consolidated Statements of Operations

 

Response: The Company respectfully acknowledges the Staff’s comment and advises the Staff that it has revised the disclosure on pages 65 and 208 of Amendment No. 2 in response to the Staff’s comment.

 

The Company further advises the Staff that iLearningEngines’ contracted employees include contract employees provided by the Technology Partner as well as independent consultants and contract employees from other vendors hired directly by iLearningEngines. Contract employees are hired across customer support, selling, general and administrative services and R&D services.

 

Compensation for iLearningEngines’ contract employees is reported in iLearningEngines’ Consolidated Statements of Operations under Cost of Revenue and Operating Expense headings.

 

If you have any questions or would like further information concerning the Company’s responses to your Comment Letter, please do not hesitate to contact me at jmutkoski@goodwinlaw.com or (617) 570-1073.

 

  Sincerely,
   
  /s/ John M. Mutkoski
  John M. Mutkoski, Esq.

 

CC: Matthew Safaii, Chief Executive Officer

 

  Arrowroot Acquisition Corp.
   
  Jocelyn M. Arel
  Justin S. Anslow
  Wei Xu
  Goodwin Procter LLP
   
  Eric Blanchard
  Josh Holleman
  Daniel Peale
  David Silverman
  Cooley LLP