IP Library Granted Patent US 12,566,913
Granted Patent B2
US 12,566,913 · App. 18/909,068 · Granted Mar 3, 2026

Artificial intelligence agents to automate multimodal interface task workflows

Inventors: Rohan Bavishi (San Francisco, CA); Lina Lukyantseva (San Francisco, CA); Shaya Zarkesh (San Francisco, CA); David Luan (San Francisco, CA); Basil Safwat (San Francisco, CA); Amelia Wattenberger (San Francisco, CA); Kadhir Manickam (San Francisco, CA); Inigo Beitia Arevalo (San Francisco, CA); James Lu (San Francisco, CA); Omkar Savant (San Francisco, CA); Zach Brock (San Francisco, CA); Jacob van Gogh (San Francisco, CA); Rick Liu (San Francisco, CA); Deepak Moparthi (San Francisco, CA); Claire Pajot (San Francisco, CA); Joe Gershenson (San Francisco, CA); Arushi Somani (San Francisco, CA); Armaan Goel (San Francisco, CA); Kevin Keller (San Francisco, CA); Erich Elsen (San Francisco, CA); Curtis Hawthorne (San Francisco, CA)
Assignee: Anthropic, PBC
G06F40/166G06F3/0481G06F3/0484G06F16/951G06F40/174G06F40/284G06N3/0455G06N3/091G06N5/04G06N20/00G06V10/7715G06V10/774G06V10/803G06V10/82G06V20/40G06V30/19147G06V30/41G06F9/451
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Quick Facts
Patent No.
US 12,566,913
App. No.
18/909,068
Granted
Mar 3, 2026
Kind
B2
Abstract

A system for interface automation includes an agent. The agent is configured to process an input that specifies an interface workflow, wherein the interface workflow is otherwise implementable by one or more user-actuated actions directed towards an interface by a user. The agent is also configured to generate an output that specifies a sequence of actuation commands, wherein the sequence of actuation commands triggers one or more machine-actuated actions that replicate the user-actuated actions on the interface and cause automation of the interface workflow.

Claims (23)

1 . A system for interface automation, comprising:

at least one central processing unit:

a memory device storing programming and data constructs that when executed by the at least one processing unit, cause the system to configure an agent;

the agent configured to:

process an input including multimodal data that specifies an interface workflow including contextual metadata and a state of the interface prior to execution of the interface workflow, wherein the multimodal data includes at least a combination of a natural language description and a prescriptive command; and

segment the interface workflow into a plurality of sub-tasks wherein each sub-task depends on the completion of a preceding sub-task;

generate an output, responsive to the multimodal input data, that specifies a sequence of actuation commands expressed in a custom domain-specific language (DSL) that supports both model calls and action executions, wherein the sequence of actuation commands triggers one or more machine-actuated actions that replicate user-actuated actions on the interface and cause automation of the interface workflow by translating model instructions into real web or application events, including at least localization;

actuate the sequence of multimodal actuation commands by an actuator, wherein the actuator is configured to receive the sequence of actuation commands from the agent, and to perform the machine-actuated actions based on the sequence of actuation commands as synthetic actions that automate the interface workflow; and

provide feedback including interface screenshots and action histories for iterative workflow execution and refinement.

2 . The system of claim 1 , wherein the natural language description is a natural language description of the interface workflow provided by the user and processed by a trained multimodal transformer model to identify intent and specific interface elements involved.

3 . The system of claim 1 , wherein the prescriptive command translates the interface workflow into one or more functions and one or more parameters using a custom-designed Domain Specific Language (DSL).

4 . The system of claim 3 , wherein the parameters are key-value pairs.

5 . The system of claim 3 , wherein the parameters include descriptions of the functions.

6 . The system of claim 1 , wherein the input includes the state of the interface prior to the execution of the interface workflow captured as structured contextual metadata, wherein said metadata is dynamically updated based on real-time interface interactions.

7 . The system of claim 1 , wherein the state of the interface prior to the execution of the interface workflow includes one or more snapshots of the interface processed as image tokens using a vision transformer module.

8 . The system of claim 1 , wherein the state of the interface prior to the execution of the interface workflow includes metadata about the interface.

9 . The system of claim 1 , wherein the state of the interface prior to the execution of the interface workflow receives one or more hints from the user as the input that contextualize the interface workflow.

10 . The system of claim 1 , wherein the state of the interface prior to the execution of the interface workflow includes a description of the interface workflow.

11 . The system of claim 1 , wherein the interface workflow includes a plurality of sub-tasks.

12 . The system of claim 11 , wherein a current sub-task in the plurality of sub-tasks is a result of executing one or more preceding sub-tasks in the plurality of sub-tasks.

13 . The system of claim 12 , wherein the state of the interface prior to the execution of the current sub-task includes one or more snapshots of the interface corresponding to the current sub-task, one or more snapshots of the interface corresponding to the preceding sub-tasks, and one or more sequences of actuation commands corresponding to the preceding sub-tasks.

14 . The system of claim 1 , wherein the actuator is implemented by an actuation layer configured to translate the sequence of actuation commands into real-time synthetic interactions with interface elements, wherein the actuator is configured to receive the sequence of actuation commands from the agent, and to perform the machine-actuated actions based on the sequence of actuation commands as synthetic actions that automate the interface workflow.

15 . The system of claim 1 , wherein the user-actuated actions include clicks, hovers, scrolls, picks, text entries, and form fills.

Assignments (3)
CORRECTIVE ASSIGNMENT TO CORRECT THE THE NAME OF THE ASSIGNEE TO ANTHROPIC, PBC PREVIOUSLY RECORDED ON REEL 70785 FRAME 275. ASSIGNOR(S) HEREBY CONFIRMS THE THE ASSIGNMENT.. Recorded Apr 17, 2025
From: ADEPT AL LABS INC.
To: ANTHROPIC, PBC
Reel/Frame 071101/0374 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 9, 2025
From: ADEPT AL LABS INC.
To: ANTHROPIC, PBNC
Reel/Frame 070785/0275 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 17, 2025
From: BAVISHI, ROHAN; LUKYANTSEVA, LINA; ZARKESH, SHAYA; LUAN, DAVID; SAFWAT, BASIL; WATTENBERGER, AMELIA; MANICKAM, KADHIR; AREVALO, IÑIGO; LU, JAMES; SAVANT, OMKAR; BROCK, ZACH; GOGH, JACOB VAN; LIU, RICK; MOPARTHI, DEEPAK; PAJOT, CLAIRE; GERSHENSON, JOE; SOMANI, ARUSHI; GOEL, ARMAAN; KELLER, KEVIN; ELSEN, ERICH; HAWTHORNE, CURTIS
To: ADEPT AI LABS INC.
Reel/Frame 070529/0768 →
Continuity (9)
Provisional Application 63638613 · Apr 25, 2024
Provisional Application 63638631 · Apr 25, 2024
Provisional Application 63638644 · Apr 25, 2024
Provisional Application 63567667 · Mar 20, 2024
Provisional Application 63567681 · Mar 20, 2024
Provisional Application 63567698 · Mar 20, 2024
Provisional Application 63567721 · Mar 20, 2024
Provisional Application 63567714 · Mar 20, 2024
Related Publication 20250298495A1 · Sep 25, 2025
References Cited (142)
US 6012030A · French-St. George et al. · 2000 [cited by applicant]
US 6226785B1 · Peterson · 2001 [cited by examiner]
US 6859451B1 · Pasternack et al. · 2005 [cited by applicant]
US 8185544B2 · Oztekin et al. · 2012 [cited by applicant]
US 8493406B2 · Rubin et al. · 2013 [cited by applicant]
US 8855684B2 · Bellver et al. · 2014 [cited by applicant]
US 9218128B1 · Yuschik et al. · 2015 [cited by applicant]
US 9269048B1 · Chen · 2016 [cited by applicant]
US 10257225B1 · Sites · 2019 [cited by applicant]
US 10587708B2 · Laird-Mcconnell et al. · 2020 [cited by applicant]
US 11077320B1 · Hibbard · 2021 [cited by applicant]
US 11645564B2 · Wu et al. · 2023 [cited by applicant]
US 11809887B2 · Hinton · 2023 [cited by examiner]
US 11907864B2 · Wu et al. · 2024 [cited by applicant]
US 12293272B1 · Poulis et al. · 2025 [cited by applicant]
US 20020062475A1 · Iborra et al. · 2002 [cited by applicant]
US 20030217054A1 · Bachman et al. · 2003 [cited by applicant]
US 20040054690A1 · Hillerbrand et al. · 2004 [cited by applicant]
US 20040078787A1 · Borek et al. · 2004 [cited by applicant]
US 20040215665A1 · Edgar et al. · 2004 [cited by applicant]
US 20050010418A1 · McNair et al. · 2005 [cited by applicant]
US 20060155954A1 · Haynes · 2006 [cited by examiner]
US 20060161878A1 · Koh et al. · 2006 [cited by applicant]
US 20070233495A1 · Agapi et al. · 2007 [cited by applicant]
US 20080065388A1 · Cross et al. · 2008 [cited by applicant]
US 20080065390A1 · Ativanichayaphong et al. · 2008 [cited by applicant]
US 20080065453A1 · Settuducati · 2008 [cited by applicant]
US 20080118051A1 · Odinak et al. · 2008 [cited by applicant]
US 20080228494A1 · Cross · 2008 [cited by applicant]
US 20080301094A1 · Zhu · 2008 [cited by examiner]
US 20110041140A1 · Harm · 2011 [cited by examiner]
US 20130080641A1 · Lui et al. · 2013 [cited by applicant]
US 20130144682A1 · Dhara et al. · 2013 [cited by applicant]
US 20130226892A1 · Ehsani et al. · 2013 [cited by applicant]
US 20130268260A1 · Lundberg et al. · 2013 [cited by applicant]
US 20140157288A1 · Wong · 2014 [cited by examiner]
US 20140214404A1 · Kalia et al. · 2014 [cited by applicant]
US 20150339712A1 · Koutrika et al. · 2015 [cited by applicant]
US 20160162172A1 · Rathod · 2016 [cited by applicant]
US 20160335331A1 · Schnase et al. · 2016 [cited by applicant]
US 20170048170A1 · Smullen et al. · 2017 [cited by applicant]
US 20170091178A1 · Barbosa et al. · 2017 [cited by applicant]
US 20170255580A1 · Parekh et al. · 2017 [cited by applicant]
US 20170289305A1 · Liensberger et al. · 2017 [cited by applicant]
US 20180012141A1 · Chehreghani et al. · 2018 [cited by applicant]
US 20180060744A1 · Achin et al. · 2018 [cited by applicant]
US 20180137431A1 · Goldfarb et al. · 2018 [cited by applicant]
US 20180157739A1 · Khaitan et al. · 2018 [cited by applicant]
US 20180314943A1 · Liang et al. · 2018 [cited by applicant]
US 20190171984A1 · Irimie et al. · 2019 [cited by applicant]
US 20190187987A1 · Fauchère · 2019 [cited by examiner]
US 20190332686A1 · Lee · 2019 [cited by examiner]
US 20190384807A1 · Dernoncourt et al. · 2019 [cited by applicant]
US 20200342316A1 · Shazeer et al. · 2020 [cited by applicant]
US 20210232992A1 · Disterheft et al. · 2021 [cited by applicant]
US 20220046129A1 · Clodore et al. · 2022 [cited by applicant]
US 20220048525A1 · Tsai et al. · 2022 [cited by applicant]
US 20220051219A1 · Sells et al. · 2022 [cited by applicant]
US 20220058981A1 · Neumann · 2022 [cited by applicant]
US 20220130013A1 · Pottorff et al. · 2022 [cited by applicant]
US 20220215262A1 · Narayanaswami et al. · 2022 [cited by applicant]
US 20220246257A1 · Priestas et al. · 2022 [cited by applicant]
US 20220291966A1 · Masood · 2022 [cited by examiner]
US 20230031702A1 · Li et al. · 2023 [cited by applicant]
US 20230106716A1 · Xiong · 2023 [cited by examiner]
US 20230156075A1 · Brewer et al. · 2023 [cited by applicant]
US 20230206913A1 · Vempaty et al. · 2023 [cited by applicant]
US 20230222285A1 · Zhang et al. · 2023 [cited by applicant]
US 20230222623A1 · Ke et al. · 2023 [cited by applicant]
US 20230281400A1 · Wang et al. · 2023 [cited by applicant]
US 20230306205A1 · Maeder et al. · 2023 [cited by applicant]
US 20230325693A1 · Wu et al. · 2023 [cited by applicant]
US 20230342167A1 · Radkoff · 2023 [cited by examiner]
US 20230351149A1 · Yu et al. · 2023 [cited by applicant]
US 20230360388A1 · Singh · 2023 [cited by applicant]
US 20230386025A1 · Loddenkemper et al. · 2023 [cited by applicant]
US 20230419652A1 · Tiong et al. · 2023 [cited by applicant]
US 20240119257A1 · Guo et al. · 2024 [cited by applicant]
US 20240135232A1 · Betteridge · 2024 [cited by examiner]
US 20240256835A1 · Dehghani et al. · 2024 [cited by applicant]
US 20240281472A1 · LaRhette et al. · 2024 [cited by applicant]
US 20240282084A1 · Serra et al. · 2024 [cited by applicant]
US 20240282094A1 · Tsimpoukelli et al. · 2024 [cited by applicant]
US 20240290065A1 · Park et al. · 2024 [cited by applicant]
US 20240303443A1 · Cheng et al. · 2024 [cited by applicant]
US 20240329943A1 · Sharma · 2024 [cited by examiner]
US 20240338234A1 · Li · 2024 [cited by examiner]
US 20240362272A1 · Lee et al. · 2024 [cited by applicant]
US 20240370765A1 · Pierucci et al. · 2024 [cited by applicant]
US 20240404238A1 · Yu et al. · 2024 [cited by applicant]
US 20240412720A1 · Vasylyev et al. · 2024 [cited by applicant]
US 20250028759A1 · Castillo et al. · 2025 [cited by applicant]
US 20250217170A1 · Shaw et al. · 2025 [cited by applicant]
US 20250245030A1 · Cyjon · 2025 [cited by examiner]
US 20250272350A1 · Furuta et al. · 2025 [cited by applicant]
US 20250272506A1 · Sassak, Jr. et al. · 2025 [cited by applicant]
WO 2024049607A2 · 2024 [cited by applicant]
WO 2024146961A1 · 2024 [cited by applicant]
Adept Product Team, ‘Building Powerful Agents with Adept’, Aug. 23, 2024, 12 pages. [cited by applicant]
Adept Team, “Adept Fuyu-Heavy: A new multimodal model”, Jan. 24, 2024, 11 pages. [cited by applicant]
Erich Elsen, Augustus Odena, Maxwell Nye, Saǧnak Taşirlar, Tri Dao, Curtis Hawthorne, Deepak Moparthi, Arushi Somani, “Releasing Persimmon-8B”, Sep. 7, 2023, 7 pages. [cited by applicant]
Erich Elsen, Curtis Hawthorne, Arushi Somani, “The Adventure of the Errant Hardware”, Sep. 19, 2023, 14 pages. [cited by applicant]
Rohan Bavishi, Erich Elsen, Curtis Hawthorne, Maxwell Nye, Augustus Odena, Arushi Somani, Saǧnak Taşirlar, “Fuyu-8B: A Multimodal Architecture for AI Agents”, Oct. 17, 2023, 22 pages. [cited by applicant]
Tri Dao, “FlashAttention: Fast Transformer training with long sequences”, Jan. 17, 2023, 9 pages. [cited by applicant]
Sethi, Pooja, et al. “Autonlu: Detecting, root-causing, and fixing nlu model errors.” arXiv preprint arXiv:2110.06384 (2021). (Year:2021) 10 pages. [cited by applicant]
U.S. Appl. No. 18/908,447 Non Final Office Action dated Dec. 13, 2024, 27 pages. [cited by applicant]
Zhou, Shuyan, et al. “Webarena: A realistic web environment for building autonomous agents.” arXiv preprint arXiv:2307.13854 (2023). (Year: 2023) 22 pages. [cited by applicant]
U.S. Appl. No. 18/909,186 Non-final Rejection dated Dec. 9, 2024, 27 pages. [cited by applicant]
U.S. Appl. No. 18/909,455 Non-final Office Action dated Dec. 19, 2024, 30 pages. [cited by applicant]
U.S. Appl. No. 18/909,588 Non-final Office Action dated Dec. 4, 2024, 41 pages. [cited by applicant]
Walker et al. “Neural semantic parsing with anonymization for command understanding in general-purpose service robots.” Robot World Cup. Cham: Springer International Publishing, 2019. 337-350. (Year: 2019) 14 pages. [cited by applicant]
Yin, Pengcheng. Learning Structured Neural Semantic Parsers. Diss. Carnegie Mellon University, 2021. (Year: 2021) 189 pages. [cited by applicant]
Ortiz, Jose Javier Gonzalez, John Guttag, and Adrian Dalca. “Magnitude invariant parametrizations improve hypernetwork learning.” arXiv preprint arXiv:2304.07645 (2023). (Year: 2023). [cited by applicant]
Chen, Delong, Samuel Cahyawijaya, Jianfeng Liu, Baoyuan Wang, and Pascale Fung. “Subobject-level Image Tokenization.” arXiv preprint arXiv:2402.14327 (2024). (Year: 2024). [cited by applicant]
F. Shi, R. Gao, W. Huang and L. Wang, “Dynamic MDETR: A Dynamic Multi modal Transformer Decoder for Visual Grounding,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, No. 2, pp. 1181-1198, Fe… [cited by applicant]
Humbertokramm, “Convert array RGB565 to RGB888 and then to PNG in python”, 2018, GitHub Repository, https://github.com/ humbertokramm/RGB565toRGB888toPNG_-python- (Year: 2018). [cited by applicant]
J. Wu, W. Gan, Z. Chen, S. Wan and P. S. Yu, “Multimodal Large Language Models: A Survey,” 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 2247-2256 (Year: 2023). [cited by applicant]
Li et al, Demonstration+ Natural Language: Multi modal Interfaces for GUI-Based Interactive Task Learning Agents (Year: 2021) 43 pages. [cited by applicant]
Li et al., “Otter: Deep Diving Into Large Multi-Modality Models”, 2023, GitHub Repository, https://github.com/Luodian/Otter (Year: 2023). [cited by applicant]
Li, Bo, Peiyuan Zhang, Jingkang Yang, Yuanhan Zhang, Fanyi Pu, and Ziwei Liu. “Otterhd: A high-resolution multi-modality model.” arXiv preprint arXiv:2311.04219 (2023). (Year: 2023). [cited by applicant]
Sravanthi, G., and M. GurunadhaBabu. “Design & Implementation of VGA Display System Based on CPLD and Dual Memory.” International Journal of VLSI System Design and Communication System 3.01 (2015): 0005-0009. (Year: 201… [cited by applicant]
Takebayashi et al., Multi modal Interface Agent for Enhancing Knowledge Sharing (Year: 1997) 4 pages. [cited by applicant]
U.S. Appl. No. 18/909,531 Non-final Rejection dated Jan. 3, 2025, 110 pages. [cited by applicant]
Xie et al., OpenAgents: An Open Platform for Language Agents in the Wild, (Year: 2023) 34 pages. [cited by applicant]
Yu, Jiahui, et al. “Vector-quantized image modeling with improved vqgan.” arXiv preprint arXiv:2110.04627 (2021). (Year: 2021). [cited by applicant]
International Search Report and Written Opinion mailed Jul. 1, 2025 in PCT Application No. PCT/US2025/020719 filed Mar. 20, 2025. [cited by applicant]
Lee, Yi-Lun, et al., “Multimodal Prompting with Missing Modalities for Visual Recognition,” 2023, 10 pages. [cited by applicant]
Moran, Douglas B., et al. “Multimodal User Interfaces in the Open Agent Architecture” 1997, 8 pages. [cited by applicant]
Song, Kisub, et al., “Generating multimodal user interfaces for Web services.” 2008, 11 pages. [cited by applicant]
Chen, Weihao, et al. “Miwa: Mixed-initiative web automation for better user control and confidence.” Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. 2023. (Year: 2023). [cited by applicant]
Deng, Xiang, et al. “Mind2web: Towards a generalist agent for the web.” Advances in Neural Information Processing Systems 6 (2023): 28091-28114. (Year: 2023). [cited by applicant]
Gur, Izzeddin, et al. “A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis.” ICLR. 2024. (Year: 2024). [cited by applicant]
He, Hongliang, et al. “WebVoyager: Building and end-to-end web agent with large multi modal models.” arXiv preprint arXiv:2401.13919 (2024). (Year: 2024). [cited by applicant]
Koh, Jing Yu, et al. “Visualwebarena: Evaluating multi modal agents on realistic visual web tasks.” arXiv preprint arXiv:2401.13649 (2024). (Year: 2024). [cited by applicant]
Liu, Junpeng, et al. “Visualwebbench: How far have multi modal llms evolved in web page understanding and grouding?.” arXivpreprint arXiv:2404.05955 (2024). (Year: 2024). [cited by applicant]
Lu, Xing Han, Zdenek Kasner, and Siva Reddy. “Weblinx: Real-world website navigation with multi-turn dialogue.” arXiv preprint arXiv:2402.05930 (2024). (Year: 2024). [cited by applicant]
Zhang, Saizheng, et al. “Personalizing dialogue agents: I have a dog, do you have pets too?.” arXiv preprint arXiv: 1801.07243 (2018). (Year: 2018). [cited by applicant]
Furuta, H., et al. “Multimodal Web Navigation with Instruction-Finetuned Foundation Models,” Feb. 25, 2024, arXiv:2305.11854v4 [cs.LG], 31 pages. [cited by applicant]
“Selenium Documentation Release 1.0”, Aug. 26, 2012, 201 pages. [cited by applicant]
“WebDriver W3C Recommendation,” World Wide Web Consortium, Jun. 5, 2018, 153 pages. Available at https://www.w3.org/TR/webdriver1/. [cited by applicant]
Waibel, A., et al., “Multimodal Interfaces For Multimedia Information Agents,” 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, Munich, Germany, 1997, pp. 167-170 vol. 1, doi: 10.1109/ICAS… [cited by applicant]
Zheng, L., et al., “AgentStudio: A Toolkit for Building General Virtual Agents,” Mar. 26, 2024, arXiv:2403.17918V1 [cs.Al], 12 pages. [cited by applicant]