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OptiCrea Elements – Application for the creation and naming of policy and plan elements

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Added by:   OECD analyst
Added on:   27 Oct 2026
Updated by:   OECD analyst
Updated on:   27 Oct 2026
The initiative consists of a web application developed in R Shiny that integrates AI (via API) to assist specialists in creating and improving indicator names. This ensures their alignment with the results chain and the Guide for the Development of Indicators for National Policies and Strategic Plans.

Name in original language

OptiCrea Elements - Aplicativo para la creación y denominación elementos de políticas y planes

Initiative overview

OptiCrea Elements is a web application developed in R Shiny that integrates artificial intelligence (via the DeepSeek API) to assist planning specialists. Its primary purpose is to create and improve the naming of indicators and strategic elements, ensuring they align with Peru’s Chain of Results and current regulations.

Strategic planning in Peru requires indicator names to meet strict criteria:

a. Specific Structures: Defined by the type of element (Objective or Action).

b. Methodological Alignment: Adherence to the CEPLAN 2024 Guide, SMART criteria and results-based management.

c. The Problem: Manual drafting is time-intensive, highly dependent on individual experience, difficult to standardise and prone to structural errors.

d. Core Functionalities:

  • Multi-Instrument Support: Covers all planning levels, including Sectoral, Regional, Local and Institutional plans.
  • Dual Operating Modes:
    • IMPROVE: Optimises existing names while maintaining required legal structures.
    • CREATE: Generates new names from scratch based on user-provided context (problem, population, territory).
  • Complex Hierarchical Handling: Manages associations between Objectives → Actions → Indicators, ensuring consistency across different levels of the planning tree.
  • Specialised AI Prompts: Features specific prompt engineering for eight distinct scenarios (improving/creating for objectives, actions and their respective indicators).
  • Dynamic Interface: Built for high usability with dynamic inputs, the ability to add/remove groups of elements and structured visualisation of results.
  • DeepSeek API Integration: Uses asynchronous calls with low "temperature" settings to ensure consistent, non-creative and technically rigorous responses.
  • Efficient Exporting: Results can be copied to the clipboard or downloaded in structured TXT formats for integration into other systems.
  • Technological Stack:
    • Frontend/Backend: R Shiny & shinydashboard.
    • Artificial Intelligence: DeepSeek API (deepseek-chat).
    • Data Processing: jsonlite, httr, glue.
    • Interactivity: shinyjs.

Other relevant details

Results, outcomes and impacts: For CEPLAN and the National Planning System, the AI initiative will standardise the quality of indicator naming across all levels of government, significantly reduce the time required to review and improve indicator names and increase methodological consistency among planning instruments. It will also provide implicit training for specialists through modelled examples. For users (regional and local governments and public entities), it will offer a tool to improve indicator names without relying on external consultants, help them understand correct naming structures through generated examples and reduce common formulation errors. Challenges and lessons learned: The main challenges in implementing the AI initiative are: Prompt validation with specialists: Prompts must be refined with the participation of CEPLAN experts to ensure that responses are technically sound. Handling complex cases: Handling names that do not follow any standard structure or that mix concepts in a confusing way. Proper contextualisation: The quality of responses depends on the quality of the context provided by the user. Preservation of the original intent: When improving names, the AI must maintain the original meaning without altering the user’s intent. Scalability: Ensuring the ability to handle multiple simultaneous requests from different users. Security and privacy: The information entered may contain sensitive institutional planning data. Regulatory updates: Keeping prompts aligned with possible changes in the methodological guidelines.

AI Tags

ProductivityGenerative AIAI in Government

About the policy initiative

Peru
Peru

Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • AI use cases/projects in the public sector

Status:

  • Proposed or under development

Start Year:

  • 2025

Target Sectors:

OECD AI Principles:

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