Integration of Financial Forecasting Module into Amana Pilot
Budget: $30 – $250 USD
Integration of Financial Forecasting Module into Amana Pilot
Description:
This project involves developing a comprehensive feature for financial forecasting within the Amana Pilot platform. The feature encompasses both front-end and back-end development, enabling the processing and display of forecasted results based on a company's historical cash flow data. Forecasts will be generated using machine learning models, such as regression, leveraging financial data from previous months.
Front-End Features:
- Implementation of a cash flow tracking table, displaying the evolution of cash flow for previous months and forecasts for upcoming months (e.g., 4 months, 6 months, etc.). Past data will be represented by solid bars, while forecasted data will be represented by empty or hashed bars.
- Allowance for user modification of forecasted values. For example, users can adjust predicted values by modifying a cell previously predicted by the algorithm, automatically updating the forecast (chart). However, modification of past month values directly in the tracking table is not permitted.
- Management of constant value categories, such as fixed expenses, to limit manual updates on certain categories.
- Retention of both forecasts and actuals on the chart for comparison.
Back-End Features:
- Utilization of JSON data from our Amana Pilot API to develop forecasting, updating, and recording functionality for forecasted data. This includes employing machine learning models, like linear regression, to generate forecasts for each transaction category.
Resources:
- Addition of a 'status' attribute ('Actual', 'Forecast') to update the database.
- Provision of API access and documentation for developers to utilize our API.
- Reference cash flow tracking table snippets (source code).
Maximum Budget: $150 - $200
Description:
This project involves developing a comprehensive feature for financial forecasting within the Amana Pilot platform. The feature encompasses both front-end and back-end development, enabling the processing and display of forecasted results based on a company's historical cash flow data. Forecasts will be generated using machine learning models, such as regression, leveraging financial data from previous months.
Front-End Features:
- Implementation of a cash flow tracking table, displaying the evolution of cash flow for previous months and forecasts for upcoming months (e.g., 4 months, 6 months, etc.). Past data will be represented by solid bars, while forecasted data will be represented by empty or hashed bars.
- Allowance for user modification of forecasted values. For example, users can adjust predicted values by modifying a cell previously predicted by the algorithm, automatically updating the forecast (chart). However, modification of past month values directly in the tracking table is not permitted.
- Management of constant value categories, such as fixed expenses, to limit manual updates on certain categories.
- Retention of both forecasts and actuals on the chart for comparison.
Back-End Features:
- Utilization of JSON data from our Amana Pilot API to develop forecasting, updating, and recording functionality for forecasted data. This includes employing machine learning models, like linear regression, to generate forecasts for each transaction category.
Resources:
- Addition of a 'status' attribute ('Actual', 'Forecast') to update the database.
- Provision of API access and documentation for developers to utilize our API.
- Reference cash flow tracking table snippets (source code).
Maximum Budget: $150 - $200