DCT

2:20-cv-07041

Harper Advance LLC v. ARCHGATE TMS Solutions LLC

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I. Executive Summary and Procedural Information

  • Parties & Counsel:
  • Case Identification: 2:20-cv-07041, C.D. Cal., 05/11/2021
  • Venue Allegations: Venue is alleged to be proper in the Central District of California because Defendants are present and conduct business in the district, have committed tortious acts in the district, and Defendant TAI Software maintains its principal place of business in Huntington Beach, California.
  • Core Dispute: Plaintiff alleges that Defendants’ transportation logistics software infringes a patent that Plaintiff acquired from the lead individual defendant as part of a financial agreement.
  • Technical Context: The technology involves an artificial intelligence and machine learning platform designed to analyze multiple factors in real-time to optimize outcomes in the transportation and logistics industry.
  • Key Procedural History: The complaint outlines an unusual set of circumstances where the patent’s inventor, Defendant William Spencer Askew, allegedly assigned the patent-in-suit to Plaintiff Harper Advance as collateral for a merchant cash advance agreement. Plaintiff alleges that after the Askew Defendants breached the agreement, Plaintiff became the full owner of the patent. The complaint further alleges that TAI Software is a successor-in-interest to the Askew Defendants’ businesses and is continuing the infringing use of the patented technology. The complaint also notes a dispute with a third-party, Vinings Bank, concerning an alleged security interest in the patent.

Case Timeline

Date Event
2017-06-14 ’537 Patent Priority Date
2020-02-18 ’537 Patent Issue Date
2020-06-05 Second Merchant Cash Advance (MCA) Agreement Executed
2020-06-25 Patent Assignment to Plaintiff Recorded with USPTO
2020-08 TAI Software Acquires Askew Defendants' Business Operations
2021-05-11 First Amended Complaint Filing Date

II. Technology and Patent(s)-in-Suit Analysis

U.S. Patent No. 10,565,537 - "Systems, Methods, and Apparatuses for Optimizing Outcomes in a Multi-factor System" (issued Feb. 18, 2020)

The Invention Explained

  • Problem Addressed: The patent addresses the inefficiency of logistics processes that are handled manually or with "rudimentary computer systems that lack the sophistication necessary to identify problems or patterns, analyze better alternatives, and react on-the-fly to changing conditions" (’537 Patent, col. 2:27-33).
  • The Patented Solution: The invention is an integrated software platform that uses artificial intelligence (AI) and machine learning to optimize complex, multi-party logistics workflows (’537 Patent, Abstract). It employs software components called "advisors" to handle user requests and "analyzers" that apply a "divide-and-conquer approach" to analyze different facets of a logistics problem (e.g., customer transactions, departure/arrival locations) to generate an optimized outcome (’537 Patent, col. 5:25-67). The system then presents these optimized outcomes to a user as actionable suggestions within a graphical user interface.
  • Technical Importance: The technology aims to replace static or manual decision-making in logistics with an automated, data-driven system capable of dynamic, real-time optimization based on numerous variables (’537 Patent, col. 6:31-41).

Key Claims at a Glance

  • The complaint asserts independent claims 1 (method) and 6 (system) (Compl. ¶46).
  • Independent Claim 1 (Method) includes the following essential elements:
    • Receiving a user request for optimizing a logistics task.
    • Modifying a display to present "one or more task advisor tickets" that "slidably-expose" onto a graphical user interface (GUI).
    • Identifying the logistics task and one or more corresponding "task analyzers".
    • Retrieving logistics data.
    • Using the task analyzers to determine an "optimized logistics outcome" by applying the data to potential outcomes that are "refined via machine learning techniques."
    • Modifying the GUI to present the optimized outcome as "selectable logistics actions" within the slidably-exposed task advisor tickets.
    • Receiving a user's selection of a logistics action.
    • Initiating the selected action by "notifying one or more third-party entities to modify a preexisting logistics workflow."
  • Independent Claim 6 (System) recites a system with one or more processors configured to perform steps that largely parallel the method of claim 1.
  • The complaint does not explicitly reserve the right to assert dependent claims.

III. The Accused Instrumentality

  • Product Identification: The accused instrumentalities are the products and services of the Askew Defendants and their alleged successor-in-interest, TAI Software (Compl. ¶¶ 46-47). TAI Software's product is described as an "All in platform, built for speed and scalability" and an "AI enabled platform" for transportation management (Compl. ¶49).
  • Functionality and Market Context: The complaint alleges the TAI Software platform is a "computer-based system for optimizing transportation management systems (TMS) and logistics processes" (Compl. ¶47). Its functionality is described as allowing a user to submit an online request, after which the system generates a quote or ticket on a GUI (Compl. ¶51). The system allegedly uses an "artificial intelligence (AI) aspect" to compare task parameters and optimize a logistics task, then presents the optimized action to the user via the GUI (Compl. ¶51). The complaint alleges TAI Software is a re-brand of the Askew Defendants' prior companies and continues their business operations (Compl. ¶¶ 42, 48). No probative visual evidence provided in complaint.

IV. Analysis of Infringement Allegations

’537 Patent Infringement Allegations

The complaint alleges infringement of claims 1 and 6. The following chart summarizes the allegations for the representative method claim 1.

Claim Element (from Independent Claim 1) Alleged Infringing Functionality Complaint Citation Patent Citation
receiving a request from a user of the electronic computing device for identifying a logistics task for optimization A user submits a request online via a computer. ¶51 col. 18:4-7
the self-service computer application modifies a display at the electronic computing device to present one or more task advisor tickets to the user, wherein the one or more task advisor tickets... visually overlay at least a portion of a self-service computer application graphical user interface ("GUI"), wherein the one or more task advisor tickets are slidably-exposed onto the GUI The system generates a quote or ticket, which appears on the graphical user interface. ¶51 col. 18:8-19
identifying... one or more task analyzers for processing the optimization of the identified logistics task The AI aspect of TAI's software product then compares one or more task parameters... using a task analyzer. ¶51 col. 18:24-31
retrieving logistics task data corresponding to the identified logistics task The system uses "task parameters" to "optimize the identified logistics task". ¶51 col. 18:32-34
determining, via the one or more task analyzers, an optimized logistics outcome, wherein determining the optimized logistics outcome comprises applying the logistics task data and the one or more task parameters to a plurality of potential outcomes, wherein the potential outcomes are included in a data set refined via machine learning techniques The AI aspect of TAI's software is used to optimize the identified logistics task. The complaint asserts that "machine learning" is synonymous with AI. ¶¶51, 27 col. 18:35-46
modifying the self-service computer application GUI for presenting the user with the optimized logistics outcome... by slidably exposing the one or more task advisor tickets comprising the one or more selectable logistics actions onto the GUI Once the optimized task is determined, it is presented to the user of the TAI system via the graphic user interface... which informs the user about the optimized logistics action. ¶¶51, 1 col. 18:47-57
initiating the respective logistics action selected by the user, wherein initiating the respective logistics action... comprises notifying one or more third-party entities to modify a preexisting logistics workflow The optimized logistics action can be selected by the user and acted upon, including notifying one or more third-party entities to modify a pre-existing logistics workflow. ¶1 col. 18:61-65
  • Identified Points of Contention:
    • Scope Questions: Claim 1 requires a specific user interface element: "task advisor tickets" that are "slidably-exposed onto the GUI." The complaint does not provide visual evidence of the accused interface. A central dispute may be whether the accused TAI Software GUI literally meets this structural limitation or if Plaintiff must rely on the doctrine of equivalents. The construction of "slidably-exposed" will be critical.
    • Technical Questions: The claims require a specific analytical process: using "task analyzers" to apply "logistics task data" to a "plurality of potential outcomes" that are "refined via machine learning techniques." The complaint alleges the accused "AI aspect" performs this function (Compl. ¶51). An evidentiary question will be whether the accused system performs this specific multi-step computational method or a more generic analysis, raising questions of both literal infringement and equivalence.

V. Key Claim Terms for Construction

  • The Term: "task advisor tickets"

    • Context and Importance: This term appears to be novel to the patent and describes the specific UI mechanism for presenting optimized actions. Its construction is central to infringement, as it defines a key structural limitation of the claimed method and system. Practitioners may focus on this term because the claims repeatedly emphasize the specific "slidably-exposed" nature of these "tickets."
    • Intrinsic Evidence for Interpretation:
      • Evidence for a Broader Interpretation: The specification provides a more general definition of an "advisor" as "a piece of software code that is used to submit queries to databases or other system components" (’537 Patent, col. 5:25-27). A "suggestion" presented to the user is described more broadly as a "digitally visible alert" (’537 Patent, col. 4:57-58).
      • Evidence for a Narrower Interpretation: Claim 1 itself provides significant limiting language, requiring that the tickets "visually overlay" a portion of the GUI, are "slidably-exposed," and are "otherwise not visible until being slidably-exposed" (’537 Patent, col. 18:13-19). This detail within the claim itself could support a narrow construction tied to this specific user interface behavior.

  • The Term: "task analyzers"

    • Context and Importance: This term defines the core data processing engine of the invention. The infringement analysis depends on whether the accused AI system functions as the claimed "task analyzers."
    • Intrinsic Evidence for Interpretation:
      • Evidence for a Broader Interpretation: The specification defines an analyzer in general terms as an "allocated portion of computing processing power... to analyze particular portions of large scale data sets" (’537 Patent, col. 5:47-50).
      • Evidence for a Narrower Interpretation: The specification further describes analyzers as implementing a "divide-and-conquer approach" and provides a specific example where separate analyzers handle distinct data sets (e.g., customer transactions, departure location, arrival location) that are then combined to give a "complete view of the situation context" (’537 Patent, col. 5:55-63). This could support a narrower construction requiring a specific modular, multi-analyzer architecture.

VI. Other Allegations

  • Indirect Infringement: The complaint alleges liability for induced infringement (Compl. ¶54) and the prayer for relief references 35 U.S.C. § 271(b) (Compl. p. 19, ¶1). However, the complaint does not plead specific facts to support the element of intent, such as referencing user manuals or other instructions that would encourage infringing acts.
  • Willful Infringement: The complaint alleges that infringement has been and continues to be willful (Compl. ¶55). The factual allegations may provide a basis for this claim, particularly against Defendant Askew, who was the patent's inventor and assigned it to Plaintiff, suggesting definitive pre-suit knowledge of the patent (Compl. ¶¶ 37-38). Knowledge is imputed to TAI Software through its alleged status as a successor-in-interest continuing the same operations (Compl. ¶¶ 42, 47).

VII. Analyst’s Conclusion: Key Questions for the Case

  • A threshold issue, preceding any technical patent analysis, will be one of standing and ownership: can Plaintiff Harper Advance establish that the alleged breach of the underlying financing agreement validly transferred full and unencumbered title of the ’537 Patent, thereby giving it the right to sue for infringement? The dispute over a third-party bank's security interest adds complexity to this question.
  • A core infringement issue will be one of structural correspondence: does the accused TAI Software user interface, which is described but not depicted in the complaint, incorporate the specific "slidably-exposed task advisor tickets" required by the claims, or is there a structural mismatch that will require the Plaintiff to argue for infringement under the doctrine of equivalents?
  • A key evidentiary question will be one of functional operation: does the accused system's "AI" perform the particular multi-step computational process recited in the claims—using "task analyzers" to apply data to a "plurality of potential outcomes" that are "refined via machine learning"—or does it operate in a technically distinct manner?