Sorted AI offers an efficient solution for R&D Advisors to expedite their clients’ R&D submissions. Instead of using multiple, disparate documents and spreadsheets, Sorted AI allows R&D team members to input all relevant R&D project information into an integrated, user-friendly platform. This system streamlines the submission process, ensuring expedient, accurate, and compliant R&D claim preparation.
Sorted AI is platform-agnostic and can be accessed via any Windows or Mac OS desktop through a browser, allowing information to be entered and extracted from any location. This ensures that all R&D project data is current and relevant, and timely reports are maintained. The system also supports version control and ensures data integrity and accuracy.
The Sorted AI platform is exceptionally user-friendly and intuitive, enabling R&D practices to easily gather the necessary information and organise data for straightforward reporting to key stakeholders, both internal and external. This includes the R&D advisory team, managers, clients, and the clients’ tax agents.
The Sorted FQG module will offer a robust framework to capture financial data, collect R&D expenditure from applicants, and categorise items accurately to be entered into the R&D practice’s financial workpapers. This ensures accuracy in R&D claims, enhances data integrity, and structures the R&D claim preparation process for superior results.
Sorted AI streamlines R&D workflows by integrating all R&D project information into a ‘single source of truth’. This reduces the time and effort required for submissions, allowing team members to focus on refining claims and developing client relationships instead of gathering and filing data. Sorted AI’s accessible interface ensures accurate and consistent details, leading to faster and more reliable outcomes.
Set up clients for each R&D Agent.
Enter client information.
Assign R&D consultants to clients
Run workshop (workshop mode) or collect data via client questionnaire.
Generate R&D reports (review mode).
Generate financial queries in Sorted FQG (pending).
Save and track claims over time.
Update client details.
There are five key aspects that drive the Sorted AI platform. These are:
The non-AI mode where the R&D team member collects data from the client, either in the form of notes taken in a workshop, by inputting client-provided R&D project information, or both. It follows a logical workflow covering all R&D project aspects required for submission, acting as a wizard to guide users through the required inputs.
The Style Guide ensures uniform presentation of information, guiding how the content is written to match the specific writing tone of the R&D practice. It imparts standard terminology and applies legislative guidelines where relevant. A professional tone can be customised for each R&D practice to deliver a unique and consistent format for all their team members.
The Lexicon provides a tailored vocabulary for each R&D practice, indicating which words to use and which to avoid. This feature ensures precision and clarity, selecting elements of the R&D project that are compliant with the R&D legislation and aligning the content with the practice’s specific linguistic preferences. Examples from the Lexicon include:
This feature of Sorted AI integrates R&D legislation, case studies, and supporting information into its responses. By referencing current legislative requirements, it ensures that the selected R&D project elements comply with the legislation, generating accurate and compliant R&D claims. This will be fully integrated with the addition of Sorted LGA, the ‘Deep Dive’ legislative module. Sorted LGA will also feature a ‘first of its kind’ Chatbot style feature that will allow users to pose questions about the R&D legislation in natural language, whether they are in a report or simply in the application.
At the heart of Sorted AI is a proprietary, multi-layered Prompt Engine, using the LAIRD computing model to meet specific R&D reporting requirements. It generates clear, compliant responses by selecting relevant descriptions within the Style Guide and Lexicon’s context. This ensures accurate claim preparation and allows users to update responses with their own wording as needed.
