# US 2026/0093560 A1 · Artificial intelligence powered authoring system to create bridge layers for ecosystem application programming interfaces > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2026/0093560 A1 - Document ID: US20260093560A1 - Status: Published application - Kind: A1 - Application number: 18/901,537 - Filed: 2024-09-30 - Published: 2026-04-02 - Earliest claimed: 2024-09-30 - Assignees: Intuit Inc. - Applicants: Intuit Inc. - Inventors: Ronnie Douglas DOUTHIT; Deepankar MOHAPATRA; Prabhavathi KARAVADI; Conrad DE PEUTER - Web page: https://patentgrep.com/patent/US20260093560A1 ## CPC - G06F 9/541: {via adapters, e.g. between incompatible applications} - G06F 9/547: {Remote procedure calls [RPC]; Web services} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Aspects of the present disclosure relate to generating bridge artifacts for computing environments. Embodiments include receiving a natural language prompt that indicates a type of bridge artifact to create and a target computing environment. Embodiments further include determining data retrieval tools relevant to the natural language prompt. Embodiments further include invoking the one or more data retrieval tools, wherein the one or more data retrieval tools are configured to retrieve data that is relevant to the natural language prompt and that is associated with the target computing environment. Embodiments further include invoking a bridge artifact creation tool based on the natural language prompt and the data retrieved by the one or more data retrieval tools. Embodiments further include generating a bridge artifact of the type indicated in the natural language prompt. ## Claims ### Claim 1 A method of generating bridge artifacts for computing environments, comprising: receiving, by an agent component, a natural language prompt that indicates a type of bridge artifact to create and a target computing environment; determining, by the agent component based on providing the natural language prompt as an input to a machine learning model, one or more data retrieval tools relevant to the natural language prompt; invoking, by the agent component, the one or more data retrieval tools, wherein the one or more data retrieval tools are configured to retrieve data that is relevant to the natural language prompt and that is associated with the target computing environment; invoking, by the agent component, a bridge artifact creation tool based on the natural language prompt and the data retrieved by the one or more data retrieval tools; and generating, by the bridge artifact creation tool based on the retrieved data, a bridge artifact of the type indicated in the natural language prompt. ### Claim 2 (depends on 1) The method of claim 1, further comprising using the one or more data retrieval tools to identify the target computing environment. ### Claim 3 (depends on 1) The method of claim 1, wherein determining the one or more data retrieval tools relevant to the natural language prompt is based on a descriptor associated with a given data retrieval tool that enables the machine learning model to identify the given data retrieval tool as being relevant to the natural language prompt. ### Claim 4 (depends on 1) The method of claim 1, wherein the target computing environment comprises an application programming interface (API), wherein a particular data retrieval tool of the one or more data retrieval tools is configured to retrieve data based on the API. ### Claim 5 (depends on 1) The method of claim 1, wherein a particular data retrieval tool of the one or more data retrieval tools is configured to retrieve documentation associated with the target computing environment. ### Claim 6 (depends on 1) The method of claim 1, wherein a particular data retrieval tool of the one or more data retrieval tools comprises an additional machine learning model that is trained to retrieve data associated with the target computing environment. ### Claim 7 (depends on 1) The method of claim 1, wherein invoking the bridge artifact creation tool is based on a descriptor associated with the bridge artifact creation tool that enables the agent component to identify the bridge artifact creation tool as being relevant to the natural language prompt. ### Claim 8 (depends on 1) The method of claim 1, wherein the bridge artifact creation tool comprises a generative machine learning model that is trained to generate bridge artifacts of the type indicated in the natural language prompt. ### Claim 9 (depends on 1) The method of claim 1, wherein the type indicated in the natural language prompt comprises source code for a software artifact. ### Claim 10 (depends on 1) The method of claim 1, wherein the bridge artifact comprises a first software artifact that is configured to interact with the target computing environment and a second software artifact that interacts with the first software artifact based on user input. ### Claim 11 (depends on 1) The method of claim 1, wherein the generating is further based on a bridge artifact template, wherein the bridge artifact template corresponds to the type indicated in the natural language prompt. ### Claim 12 A system for generating bridge artifacts for computing environments, comprising: one or more processors; and a memory comprising instructions that, when executed by the one or more processors, cause the system to: receive, by an agent component, a natural language prompt that indicates a type of bridge artifact to create and a target computing environment; determine, by the agent component based on providing the natural language prompt as an input to a machine learning model, one or more data retrieval tools relevant to the natural language prompt; invoke, by the agent component, the one or more data retrieval tools, wherein the one or more data retrieval tools are configured to retrieve data that is relevant to the natural language prompt and that is associated with the target computing environment; invoke, by the agent component, a bridge artifact creation tool based on the natural language prompt and the data retrieved by the one or more data retrieval tools; and generate, by the bridge artifact creation tool based on the retrieved data, a bridge artifact of the type indicated in the natural language prompt. ### Claim 13 (depends on 1) The system of claim 1, wherein the memory further causes the system to use the one or more data retrieval tools to identify the target computing environment. ### Claim 14 (depends on 1) The method of claim 1, wherein determining the one or more data retrieval tools relevant to the natural language prompt is based on a descriptor associated with a given data retrieval tool that enables the machine learning model to identify the given data retrieval tool as being relevant to the natural language prompt. ### Claim 15 (depends on 1) The method of claim 1, wherein the target computing environment comprises an application programming interface (API), wherein a particular data retrieval tool of the one or more data retrieval tools is configured to retrieve data based on the API. ### Claim 16 (depends on 12) The system of claim 12, wherein a particular data retrieval tool of the one or more data retrieval tools is configured to retrieve documentation associated with the target computing environment. ### Claim 17 (depends on 12) The system of claim 12, wherein a particular data retrieval tool of the one or more data retrieval tools comprises an additional machine learning model that is trained to retrieve data associated with the target computing environment. ### Claim 18 (depends on 1) The method of claim 1, wherein invoking the bridge artifact creation tool is based on a descriptor associated with the bridge artifact creation tool that enables the agent component to identify the bridge artifact creation tool as being relevant to the natural language prompt. ### Claim 19 (depends on 1) The method of claim 1, wherein the bridge artifact creation tool comprises a generative machine learning model that is trained to generate bridge artifacts of the type indicated in the natural language prompt. ### Claim 20 (depends on 12) The system of claim 12, wherein the bridge artifact comprises a first software artifact that is configured to interact with the target computing environment and a second software artifact that interacts with the first software artifact based on user input.