Commodities
We partner with businesses to unlock the power of AI. We will work with you to investigate and implement tailored AI solutions for your business.
Artificial Intelligence for Commodities
Data Analysis and Visualization
We offer data analysis and visualization services to help companies make informed decisions based on the trends and patterns in commodity markets. By providing easy-to-understand visualizations and insights, we make sure you stay on top of market changes and identify new opportunities.
Market Research
Our deep learning algorithms learn from market trends and historical data to identify emerging trends and potential opportunities in commodity markets. This analysis could include, for example, the effect of factors such as global supply and demand, geopolitical events, and market volatility.
Supply Chain Optimisation
Mercury Labs' AI-powered supply chain optimisation tools provide a comprehensive approach to maximising efficiency and profitability in commodities trading. AI can help to reduce costs, improve risk management, and increase agility, giving our clients a competitive edge in the market.
Methodology
How we turn your idea into your creation.
Define the project objectives and scope
Begin by identifying the specific challenges your financial company faces and the goals you want to achieve through the AI project. Determine the key performance indicators (KPIs) that will be used to measure the success of the project. Establish a clear project scope, including a timeline, budget, and resource requirements.
Collect and preprocess data
Gather relevant data from various sources, such as customer demographics, transaction history, credit data, and market trends. Clean, preprocess, and consolidate the data to ensure its accuracy, completeness, and consistency. The quality of your data plays a crucial role in the effectiveness of your AI solution, so invest time in preparing it properly.
Develop, test, and deploy the AI solution
We design and develop the AI solution, leveraging machine learning algorithms and models tailored to address your financial company's challenges and objectives. Train and fine-tune the models using the prepared data. Rigorously test the AI solution to ensure its performance meets the established KPIs, and iteratively refine it based on feedback and testing results. Once the AI solution meets the desired criteria, deploy it to your financial environment and monitor its performance to ensure its effectiveness and alignment with your business goals.
Evaluate and refine the AI solution
After deployment, continuously evaluate the AI solution's performance by comparing its results against the pre-defined KPIs. Collect feedback from users, stakeholders, and customers to identify any areas for improvement. Use this feedback and performance data to further refine and optimise the AI solution, making adjustments as necessary to enhance its effectiveness and ensure it continues to meet your financial company's objectives. Establish a regular review process to ensure ongoing alignment with your business goals and changing market conditions.
Getting Started with AI for Business
Rapid AI Prototypes
Our proof of concept service is not just about demonstrating what's possible, it's about establishing what's practical, profitable and tailored to your business needs.
Build an AI MVP
Our AI Minimum Viable Products (MVPs) rapidly validate your most promising ideas, focusing on the core functionalities that matter most to your business.
Scale your AI
Our AI solutions go beyond proof of concepts to deliver scaled, production-ready systems tailored to drive measurable ROI. With our expertise in building for the real world, we rapidly deploy reliable AI that integrates seamlessly, delivering the operational efficiencies and bottom line returns you expect.
