Discover use cases#
QCentroid platform includes an AI-powered agent designed to help you identify and explore high-impact use cases for quantum and quantum-inspired computing in your organization.
This tool is ideal for users who are just beginning their quantum journey or want to expand their innovation pipeline with data-driven, sector-relevant opportunities.
Step-by-step: Discovering use cases with the AI Agent#
1. Start a discovery session#
Navigate to the section Use cases > My use cases through the left side menu.
Then, on the top-right corner, click on the button arrow and then on the Find use cases button.
The “Use cases discovery section” will appear and the agent will guide you through a short, conversational session to understand your context, such as:
- Sector and subsector of your organization
- Key operational or strategic challenges
- Current goals (e.g., cost reduction, sustainability, optimization)
- Available data and resources
Tip
The more detailed your responses, the better tailored the generated use cases will be.
2. Review your suggested use cases#
After the session, the AI agent will show a list of suggested use cases based on your inputs and QCentroid’s knowledge base, which is trained on:
- Scientific literature
- Real-world quantum case studies
- Industry-specific challenges
- QCentroid’s proprietary models and experience
Each use case includes a title and a short description.
3. Perform deep research on the proposed use cases#
Once your use cases are generated, the AI agent will suggest to perform a deep research analysis on all of them. This analysis includes:
- Feasibility with today’s quantum and quantum-inspired techniques
- References to existing scientific publications or benchmarks
- Type of algorithms that could be applied (e.g., QAOA, quantum annealing, tensor networks)
- Hardware or data requirements
- Comparative advantages over classical approaches
This step helps you prioritize and validate which use cases are promising enough to move forward.
Each use case is marked with a green tick ✅ or a red cross ❌ indicating their feasibility/applicability:
The following image shows the Quantum feasibility/applicability report generated for one of the use cases:
4. Save use cases to your workspace#
After reviewing the research, you can choose to save use cases that are interesting to you to your workspace within the platform.
From there, you can:
- Further describe them with deeper business information about each use case.
- Assign business and technical metrics (impact, priority, data availability, etc.)
- Include them in your quantum roadmap.
- Add the Mathematical definition and the Technical specification such as input and output formats.
- Add sample datasets to help better understand the use case to the technical development team.
- Explore potential promising solutions based on the different quantum software technicss and hardware architectures.
- Track their evolution through the QC-Ops cycle (from discovery to prototyping and production)
Benefits of the Use Case Discovery Tool#
- Quickly identify relevant use cases without needing quantum expertise
- Explore feasibility backed by scientific evidence
- Build a custom roadmap tailored to your organization and your sector and readiness
- Accelerate alignment across business and technical teams
Next steps#
Once your use cases are added to the platform, continue with:
- Scoring and prioritization in the “Metrics” section
- Roadmap planning in the “Roadmap” section
- Experimentation and benchmarking using QCentroid’s QC sandbox environment
Annex: Sample conversation#
The following is a real conversation with the AI assistant that shows how it gathers the necessary information to be able to deeply analyze the needs of the user, their interests, challenges and goals to propose use cases that are relevant.
Agent
I see you work in the finance sector. Could you tell me more about the specific area or sub-sector within finance that you focus on? For example, are you involved in retail banking, investment management, insurance, risk analysis, trading, or financial technology (fintech)? This will help me better understand your business context.
User
We are mainly focused on investment management and risk analysis
Agent
Thank you for clarifying that your focus is mainly on investment management and risk analysis. Within these areas, could you share more about the types of activities or processes that are most important to your organization? For example, are you involved in portfolio construction, asset allocation, risk assessment, regulatory compliance, or performance monitoring? This will help me understand where advanced modeling or optimization might be relevant to your work.
User
We’re interested on portfolio optimization, asset allocation and risk assessment
Agent
Thank you for sharing that your interests are in portfolio construction, asset allocation, and risk assessment. Could you tell me if your organization has any specific goals related to these activities? For example, are you aiming to improve returns, reduce risk, enhance decision-making speed, or better adapt to changing market conditions? If you’re not sure, feel free to mention any general objectives you have in mind.
User
Our goals are to improve returns and reduce risk
Agent
Thank you for specifying that your goals are to improve returns and reduce risk. To better understand your current approach, could you describe the methods or tools your organization currently uses for portfolio construction, asset allocation, and risk assessment? For example, do you rely on spreadsheets, specialized financial software, or in-house models?
User
We are currently using a custom made specialized financial software and in-house models
Agent
Thank you for explaining that you use custom in-house specialized financial software and models. Could you share some of the main challenges or difficulties your team faces with these current methods? For example, do you encounter issues with scalability, computational speed, data integration, or adapting to new market scenarios? Any details you can provide will help me understand where improvements might be possible.
We almost have all the information we need. Just a few more questions to clarify your needs.
User
Mainly computational speed
Agent
Thank you for highlighting that computational speed is the main challenge with your current methods. Just to clarify, does this issue arise when you are handling large numbers of assets, running complex simulations, or processing real-time data? Understanding when these slowdowns occur will help identify where advanced techniques could be most beneficial.
We almost have all the information we need. Just a few more questions to clarify your needs.
User
This happens during optimizations with a large number of restrictions
Agent
Thank you for specifying that the computational speed issue mainly occurs during optimizations with a large number of restrictions. This is a common challenge in portfolio construction and risk assessment, especially as the complexity of constraints increases.
To summarize our conversation:
- Sector: Finance, with a focus on investment management and risk analysis.
- Key Activities: Portfolio construction, asset allocation, and risk assessment.
- Business Goals: Improve returns and reduce risk.
- Current Methods: Custom in-house specialized financial software and models.
- Main Challenge: Computational speed, particularly during optimizations involving many restrictions.
Understood. I will proceed to generate your use cases based on the information you’ve provided.
Agent
I have found 5 use cases that might be useful for your organization. Check them out!
Agent
You can select the use cases that are most relevant to your needs, or click the button below to restart the process and explore other options.
Agent
Would you like me to conduct a Deep Research analysis to identify any previous studies related to these use cases?
User
Yes
Agent
Starting Deep Research. This process may take a few minutes, so we appreciate your patience.
Agent
Deep Research completed. You can now review an in-depth analysis of the use cases, including references to previous studies.