DCT
1:25-cv-01458
Trax Retail Inc v. Pensa Systems Inc
I. Executive Summary and Procedural Information
- Parties & Counsel:
- Plaintiff: Trax Retail, Inc. (Singapore)
- Defendant: Pensa Systems, Inc. (Delaware)
- Plaintiff’s Counsel: HAYNES AND BOONE, LLP
- Case Identification: 1:25-cv-01458, W.D. Tex., 10/17/2025
- Venue Allegations: Plaintiff alleges venue is proper because Defendant has a regular and established place of business in Austin, Texas, within the judicial district.
- Core Dispute: Plaintiff alleges that Defendant’s Vision AI image recognition technology for retail analytics infringes a patent related to using images captured at different times to determine product availability and customize presentations on electronic displays.
- Technical Context: The technology at issue operates in the retail analytics field, which uses computer vision and machine learning to automate the monitoring of in-store shelf conditions, replacing traditional manual audits.
- Key Procedural History: The complaint alleges Defendant has waived its right to challenge personal jurisdiction and venue by filing a prior motion to dismiss that did not raise those defenses. Plaintiff also alleges sending a notice letter to Defendant regarding the patent-in-suit approximately four months before filing the complaint.
Case Timeline
| Date | Event |
|---|---|
| 2019-07-21 | Priority Date for U.S. Patent No. 12,154,459 |
| 2024-11-26 | Issue Date for U.S. Patent No. 12,154,459 |
| 2025-06-26 | Plaintiff allegedly sent notice letter to Defendant |
| 2025-10-17 | Complaint Filing Date |
II. Technology and Patent(s)-in-Suit Analysis
U.S. Patent No. 12,154,459 - Customized Presentation of Items on Electronic Visual Displays in Retail Stores Based on Availability of Products
- Patent Identification: U.S. Patent No. 12,154,459, issued on November 26, 2024 (the “’459 Patent”).
The Invention Explained
- Problem Addressed: The patent's background describes the monitoring of product placement and compliance in retail stores as often being inefficient, resulting in non-uniform compliance and significant gaps in monitoring dynamically changing product displays (’459 Patent, col. 1:36-44).
- The Patented Solution: The invention proposes a method to automate this process by obtaining a plurality of images of products in a retail store at two different points in time, analyzing these images to determine product availability at each point, and then, based on this temporal availability data, selecting a display parameter to customize how an item is shown on an electronic visual display (’459 Patent, Abstract; col. 3:56-col. 4:4). This allows for dynamic updates to in-store information based on real-world shelf conditions.
- Technical Importance: This approach automates a traditionally manual and labor-intensive process, enabling continuous monitoring of shelf conditions and dynamic presentation of information to improve in-store execution (’459 Patent, col. 1:31-36).
Key Claims at a Glance
- The complaint asserts independent claim 1 (Compl. ¶37).
- The essential elements of Claim 1 are:
- Obtaining a plurality of images of products in a retail store captured using at least one image sensor, with at least a first image from a first point in time and a second image from a second, later point in time.
- Analyzing the first image using a machine learning model to determine the availability of a particular product type at the first point in time.
- Analyzing the second image using the machine learning model to determine the availability of the particular product type at the second point in time.
- Analyzing the second image to determine at least one position associated with the particular product type.
- Using the determined position to select a region of an electronic visual display in the retail store.
- Selecting at least one display parameter for a particular item based on the availability determinations from both the first and second points in time.
- Using the selected display parameter to display the item on the selected region of the electronic visual display.
III. The Accused Instrumentality
Product Identification
The complaint identifies "Pensa's Vision AI image recognition technology" as the accused instrumentality (Compl. ¶12).
Functionality and Market Context
- The accused technology provides "real-time shelf visibility and analytics" by capturing images or video of store shelves using devices like mobile phones and autonomous drones (Compl. ¶¶22, 26). An image in the complaint depicts a mobile phone and a drone scanning consumer goods on a shelf (Compl. p. 6).
- It allegedly uses these images to "digitally reconstruct[] the shelf layout to identify areas of interest, i.e. what's in place and what's missing" (Compl. ¶22).
- The system is alleged to capture data at different points in time, such as three times per day, to detect changes in shelf availability (Compl. ¶28).
- The technology is alleged to use "machine learning models in an automated perception system to analyze the data" (Compl. ¶29).
- The complaint provides a screenshot of the accused system's user interface, which allegedly tracks "Shelf Availability" over time and provides trends in "On Shelf Availability (OSA)" (Compl. p. 7). This dashboard presents "store and shelf-level product availability" metrics to users (Compl. p. 7).
IV. Analysis of Infringement Allegations
’459 Patent Infringement Allegations
| Claim Element (from Independent Claim 1) | Alleged Infringing Functionality | Complaint Citation | Patent Citation |
|---|---|---|---|
| obtaining a plurality of images of products in a retail store captured using at least one image sensor, the plurality of images comprises at least a first image corresponding to a first point in time and a second image corresponding to a second point in time... | The Pensa system obtains images of retail products using image sensors (e.g., mobile phones, drones) and captures data multiple times per day, constituting images at first and second points in time. | ¶¶25, 26, 28 | col. 3:59-65 |
| analyzing, using a machine learning model..., the first image to determine whether products of a particular product type are available at the first point in time; | Pensa's system uses machine learning models to analyze image data to track "Shelf Availability" and "On Shelf Availability (OSA)," which requires determining availability at an initial point in time. | ¶¶27, 29 | col. 3:66-col. 4:2 |
| analyzing, using the machine learning model, the second image to determine whether products of the particular product type are available at the second point in time; | Pensa's system takes images at different points in time to detect changes in availability, which requires analyzing a subsequent image to determine availability at a second point in time. | ¶¶28, 29 | col. 4:3-6 |
| analyzing the second image to determine at least one position associated with the particular product type; | The system "visually recognizes products" and reconstructs the shelf layout to determine "what's missing" and how the shelf is organized. A visual from the complaint shows product recognition with bounding boxes, indicating position detection. | ¶¶22, 30; p. 6 | col. 4:7-9 |
| using the determined at least one position associated with the particular product type to select a region of an electronic visual display in the retail store; | Pensa provides "customized presentations of retail items on electronic visual displays," such as an annotated image on a handheld device, where bounding boxes represent selected regions of the display. | ¶¶21, 26; p. 6 | col. 4:10-13 |
| based on the determination of whether products... are available at the first point in time and... at the second point in time, selecting at least one display parameter for a particular item; and | The system tracks "Shelf Availability" over time and provides "trends in OSA." The dashboard presents analytics based on this temporal data, which suggests the selection of display parameters (e.g., trend lines, statistical values, colors) based on the availability determination. | ¶27; p. 7 | col. 4:14-20 |
| using the selected at least one display parameter to display the particular item on the selected region of the electronic visual display in the retail store. | The system presents its analysis on an electronic display, such as a dashboard showing OSA trends or an annotated image on a handheld device showing product information. | ¶¶26, 27; pp. 6-7 | col. 4:21-24 |
- Identified Points of Contention:
- Scope Questions: The infringement theory may raise the question of whether the claim term "electronic visual display in the retail store" can be construed to cover a backend analytics dashboard (Compl. p. 7) that may be viewed remotely, or if its scope is limited to devices physically present within the retail store, such as the handheld device shown in the complaint (Compl. p. 6).
- Technical Questions: A central question may be what evidence the complaint provides that the accused system performs the specific step of "selecting at least one display parameter" because of the change in availability between two distinct points in time, as required by the claim. The analysis will likely focus on whether displaying a historical trend line or an availability percentage constitutes the claimed selection and display of a parameter for a "particular item."
V. Key Claim Terms for Construction
The Term: "selecting at least one display parameter for a particular item"
Context and Importance: This term is critical as it defines the specific action taken in response to the temporal availability analysis. The infringement case may turn on whether the accused system's output—such as displaying a trend line or a status indicator—meets this functional requirement.
Intrinsic Evidence for Interpretation:
- Evidence for a Broader Interpretation: The specification provides several examples of display parameters, including "a display size," "a motion pattern," "a display position on the electronic visual display," and "a color scheme" (’459 Patent, col. 7:45-50). This list may support a broad interpretation that covers various forms of visual modification.
- Evidence for a Narrower Interpretation: The claim requires the selection to be "based on the determination of whether products...are available at the first point in time and the determination of whether products...are available at the second point in time" (’459 Patent, col. 4:14-19). A defendant might argue this language requires a direct causal link, suggesting the parameter must explicitly represent the change or comparison between the two states, rather than just being a general visualization of historical data.
The Term: "electronic visual display in the retail store"
Context and Importance: The construction of this term's geographic limitation will be central to determining the scope of infringing acts. Practitioners may focus on this term because the accused technology includes a cloud-based dashboard that may be accessed outside of a physical retail store.
Intrinsic Evidence for Interpretation:
- Evidence for a Broader Interpretation: The patent describes a system architecture that includes a remote "image processing unit" and communication networks, which may suggest that components of the system can operate outside the physical store while still being part of a system for use "in the retail store" (’459 Patent, Fig. 1).
- Evidence for a Narrower Interpretation: The plain language suggests the display itself must be physically located within the store. Embodiments described in the specification, such as displays on refrigerator doors or handheld devices used by store employees, are physically located in the retail environment (’459 Patent, col. 2:1-11; Fig. 11D).
VI. Other Allegations
- Indirect Infringement: The complaint alleges both induced and contributory infringement.
- Inducement: The complaint alleges that Pensa instructs its customers and partners on how to use its technology in a manner that directly infringes the ’459 Patent (Compl. ¶49).
- Contributory: The complaint alleges that Pensa’s Vision AI technology is "specially made and adapted for use in retail locations" and is not a staple article of commerce suitable for substantial non-infringing use (Compl. ¶58).
- Willful Infringement: The complaint alleges willful infringement based on Pensa’s continued infringing activities after receiving a notice letter dated June 26, 2025, which allegedly provided knowledge of the ’459 Patent and the infringing nature of its technology (Compl. ¶¶33, 42).
VII. Analyst’s Conclusion: Key Questions for the Case
- A core issue will be one of locational scope: can the claim limitation "in the retail store" be construed to read on a system where key analytical outputs are presented on a cloud-based dashboard potentially accessed from anywhere, or is infringement strictly limited to actions involving displays physically present within the four walls of the store?
- A key evidentiary question will be one of functional specificity: does the accused system's function of tracking and displaying historical "On Shelf Availability" trends perform the specific, two-part logical operation required by Claim 1—namely, "selecting" a "display parameter" for an item based on a comparison of its availability at two distinct points in time—or does this general analytic reporting fall short of the claimed causal action?