Embrace Generative AI-powered automations to revolutionize your business operations. Drive strategic insights propelling your organization to new heights of success.

Leverage Generative AI to Amplify Automation

5bf65208-3184-4d69-8bd2-4d39bb56d468.png

UiPath use case accelerators are automation frameworks which are custom-built for specific use cases. These frameworks use best practices and pre-built components which can be modified, expanded, and 

Solution Accelerators

We were founded in 2005 in a tiny apartment in Bucharest, Romania as DeskOver.

Fittingly, it was a customer who, in 2012, first saw the immense possibilities for us in the fledgling RPA market. Our desktop automation product launched in 2013. In 2015, we introduced our enterprise platform along with our new name.

Today, UiPath is the fastest-growing enterprise software company in history with scores of offices, thousands of employees, partnerships with the world’s best consulting and BPO firms, a **500,000-strong developer community**, and **5MM+ robots at work** in over **5,000 global enterprises.**

Our mission is to deliver the leading Robotic Process Automation platform to our clients for an automation first mindset.

We build software robots that automate repetitive processes. Our software robots take on the tedious, mind-numbing work and free people to do the more stimulating, creative work worth doing.

But no matter how much we’ve grown, one thing hasn’t changed. We’re still building a company we love to work for

22ac2b39-8e69-4be8-8c56-879cf6d99177.png

a346a27f-1cc1-4314-8dc0-0cdf83707650.zip

Prompt engineering is an artificial intelligence (AI) concept that optimizes the prompts and parameters of a large language model (LLM) to produce precise, context-aware responses. The Prompt Pattern 1 – Reader / Writer Solution Accelerator uses this approach to fine-tune the prompts and retrieve accurate responses from a LLM. Each iteration’s output is clearly presented, enabling the assessment of the AI’s accuracy. Modifications in each iteration can be made to the prompt, AI parameters, AI model, or even AI provider. The engineer can verify each LLM response manually before it’s used in other automations. If satisfied, the engineer can run the prompt against all queue items without additional manual checks.

  

This Solution Accelerator involves sending cold emails marketing UiPath software to potential customers using knowledge of their industry. Initial context is gathered from a CRM and HRIS system, with additional context from a Knowledge Base System based on the initial information. An email is then generated using the context, refined, and verified before being sent to the potential client.

Refine your prompt and alter LLM outcomes with Generative AI parameters for personalized text in the Performer process. This accelerator enables tailored cold emails to potential clients.

762a136d-6ae0-44a1-83e7-d4a24c7a80f2.png

5bbfe346-73b1-4345-9566-c93e26667f41.png

761edaec-a3d2-4e0c-baec-e7a14f7e0ff7.png

5a82d5f5-7532-48e9-91dd-0ad063dc3b08.png

Visual Basic

10524795-382f-4a00-a7cd-d340a40564fe.pdf

21f04536-ecb9-4b4c-a75a-c9841363efe5.zip

5bb43c4b-30b7-49eb-a128-9f7f8560d990.zip

Prompt engineering is an artificial intelligence (AI) concept that optimizes the prompts and parameters of a large language model (LLM) to produce precise, context-aware responses. The Prompt Pattern 1 – Reader / Writer Solution Accelerator uses this approach to fine-tune the prompts and retrieve accurate responses from a LLM. Each iteration’s output is clearly presented, enabling the assessment of the AI’s accuracy. Modifications in each iteration can be made to the prompt, AI parameters, AI model, or even AI provider. The engineer can verify each LLM response manually before it’s used in other automations. If satisfied, the engineer can run the prompt against all queue items without additional manual checks.

This Solution Accelerator involves sending cold emails to potential customers using knowledge of their industry. Initial context is gathered from a CRM and HRIS system, with additional context from a Knowledge Base System based on the initial information. An email is then generated using the context, refined, and verified before being sent to the potential client.

バージョン	リリース日	ダウンロードリンク
1.0.1	2024年5月22日
Changes Inclusion of ProjectId for project.json files required for telemetry Addition of Solutions Management deployment option Updates on Tags, application and features
1.0.0	2023年7月18日
Initial published version

Prompt Pattern 1 - Reader / Writer