Solution XPLR
Overview
Solution XPLR is dedicated to the detailed design of specific AI solutions. It provides a structured workflow that guides users through the complete solution development process, from initial requirements gathering to comprehensive implementation planning. At its core, solution XPLR enables organizations to transform high-level AI opportunities identified in the Taxonomy XPLR/ AI solutions library into solution blueprints.
Solution XPLR supports the solution development lifecycle through three key phases:
Research: Identifying and validating business needs and potential approaches
Evaluate: Assessing feasibility, benefits, and alignment with organizational goals
Optimize: Refining the solution design for maximum impact and implementation readiness
This bridges the critical gap between AI opportunity identification and designing an actual solution, ensuring that valuable insights from the assessment phase translate into executable implementation plans.
Adding solutions to Solution XPLR
You can add a solution to Solution XPLR using two different methods:
Method 1: Using the AI solution library
Navigate to the AI solution library
From the Industry XPLR page, click on 'AI solution library.'
You will be directed to the AI solutions page, showcasing a collection of enterprise-ready GenAI solution ideas across multiple industries and functional areas.
Browse and select a solution
Click the dropdown near the total number of solutions to expand the filter
Use filters to categorize available solutions by industry, functions, vendors, benefit area, or search manually with keywords.
Select the solution that best aligns with your use case by clicking on it.
Review solution details
On the solution entry page, you can review comprehensive information about the solution:
Impact type: The nature of impact: incremental (gradual improvement), breakthrough (significant advancement), or transformative (fundamental change)
Overview: A high-level description of the solution and its purpose
Data requirements: Necessary data inputs for successful implementation
Data sources: Specific sources where required data can be found
Implementation considerations: Factors to consider during deployment
Benefits: Expected business outcomes and value drivers
AI agents: Both essential and optional AI agents needed
Apply enterprise context
Click 'Apply Enterprise Context ' to enable tailoring the solution to the organization's technology and data landscape, ensuring relevance, scalability, and alignment with enterprise goals.
Add to favorites (Optional)
Click the ⭐ star icon to add the solution to your favorite solutions for easy access later.
Add to solution XPLR
Click the '+ Add to Solution XPLR' button.
A confirmation pop-up will appear.
Click '+ Add' to confirm your selection.
Edit and finalize the solution entry
You will be redirected to the Solution XPLR page.
Complete the Solution Details section with auto-populated information:
Solution name: Review the pre-filled solution title (e.g., "Automated Issue Resolution and Notification System")
Industry: Select the appropriate industry from the dropdown menu
Taxonomy: Choose the relevant organizational classification (optional)
Strategic Objectives/Pain Points: Review the auto-generated business outcomes
Configure the Detailed Description section:
Detailed Overview: Review and customize the AI solution description to align with your specific implementation requirements
Data Sources: Select the relevant data sources from the dropdown menu that will feed into your solution
Technology: Choose the appropriate technology stack from the available options
Review and edit these fields if needed to better align with your specific requirements.
Configure optional settings:
Search Existing Solutions: Toggle on to search for similar implementations
Use Best Practice Process: Toggle on to leverage recommended implementation approaches
Upload supporting documentation by clicking ‘Attach File’ to include relevant requirements, specifications, or reference materials.
Click 'Create' to proceed to solution design.
Method 2: Using the Taxonomy XPLR
Select a functional area
In Taxonomy XPLR, navigate to the organizational structure section.
Choose the appropriate functional area:
Front office: Customer-facing functions (Marketing, Sales, Services)
Mid office: Operational functions (Supply chain)
Back office: Administrative functions (Finance, HR, IT, Procurement)
Choose a function and process
Select the specific function within your chosen area.
Navigate to the process related to your business use case.
Explore AI solutions
Click on the AI solutions section to view available solutions for the selected process.
Select and review a solution
Choose the AI solution that best matches your needs.
Review the detailed information about the solution:
Impact: Indicates whether the solution provides a breakthrough, transformative, or incremental impact based on the level of transformation it achieves.
Overview: Solution description and purpose
Data requirements: Necessary data inputs
Data sources: Origin of required data
Implementation considerations: Deployment factors
Top benefits: Expected outcomes
AI agents& tools: Required AI agents
Add to favorites (Optional)
Click the ⭐ icon to add the solution to your favorites.
Add to Solution XPLR
Click ‘+ Add to Solution XPLR.’
Confirm your selection by clicking '+ Add' in the popup.
Edit and finalize the solution entry
You will be taken to the Solution XPLR page with pre-filled fields.
Review and customize the solution details as needed.
Select the appropriate industry.
Choose relevant data sources and technology options
Configure the toggle options and add any attachments.
Click 'Create' to initiate the solution design process.
Method 3: Creating a custom AI solution
For organizations requiring a fully tailored AI solution beyond pre-built templates, you can manually input all necessary information to ensure alignment with specific business needs.
Enter solution details
On the Solution XPLR page, provide comprehensive information for your custom solution:
Solution Name: Choose a clear, descriptive name that reflects the purpose and scope of your AI solution.
Strategic Objectives/Pain Points: Explain the strategic objectives or pain points you are addressing with detailed context about business challenges and desired outcomes.
Detailed description: Include a thorough explanation covering:
The business process or challenge being addressed
Existing pain points and inefficiencies
The business objectives you aim to achieve
Stakeholders and teams involved
Required data sources and inputs
Desired outcomes and key success metrics
Data Sources: Select the relevant data sources that will feed into your AI solution from the dropdown menu.
Technology: Choose the appropriate technology stack and platforms for implementation.
Taxonomy: Select the relevant internal classification, if applicable.
Industry: Choose the most appropriate industry from the dropdown list.
Configure solution options
Customize additional settings to enhance solution effectiveness:
Search existing solutions: Enable this toggle to discover similar implementations for inspiration or benchmarking.
Use best practice process: Turn this on to incorporate proven, industry-standard methodologies into your solution design.
Add supporting documentation
Use the ‘Attach file’ option to upload any relevant documents, such as business cases, architecture diagrams, or stakeholder inputs.
Finalize and create your solution
Carefully review all input details for completeness and accuracy.
Click ‘Create’ to initiate the custom solution design process.
The platform will then guide you through the remaining steps to refine and build your AI solution.
Creating the solution
After submitting the base solution information, the system begins the solution design process automatically. This process consists of three main phases:
Research
Evaluate
Optimize
During this process, the system will:
Design the comprehensive solution
Create visual diagrams of workflows and processes
Fetch AI data to populate the components
After processing is complete, you will have access to a fully designed solution with five key components:
Data sources
Process flow
Agentic workflow
Readiness & Impact
Summary overview
Data sources
The Data sources screen provides detailed information about all data sources required for your AI solution.
View data source details
For each data source, you can view:
Data source: Identifier for the data source
Technology: Platform or technology that hosts the data
Essential/optional: Whether the data source is required or supplementary
Access: Internal (within your organization) or External (from outside sources)
Quality: High, Medium, or Low data quality rating
Type: Data format (API/SQL/File) and structure (Structured/Semi-structured/Unstructured)
Data assessment: Current assessment state (Review/Ready)
Modify data sources
Add a data source: Click the '+' button at the bottom of the screen
Delete a data source: Click the three dots (⋮) next to the data source and select 'Delete'
Complete data assessment
Click on the 'Review' status in the data assessment column.
A data assessment questionnaire will open.
Answer all questions regarding the data source's availability, quality, and accessibility.
Click 'Save' when complete.
The status will change from 'Review' to 'Ready' if there are minimal barriers to implementation.
Proceed to the next step
Click the 'Next' button at the bottom right of the screen to continue to Process flow.
Process flow
The Process flow section allows you to visualize and customize the business process that your AI solution will enhance.
Curate the workflow
Update steps to reflect your organization's specific process.
Identify opportunities for AI enhancement at each step of the workflow.
Customize the diagram
Click on the diagram to enter edit mode.
Add, modify, or remove elements to accurately represent your process.
Connect elements to show the process flow.
Click 'Save' when you are finished.
AI hubble panel
When you click on a step within a process flow (represented by a purple-colored box), the Hackett AI Hubble panel opens. It identifies and recommends the most effective AI agents tailored to that specific step. Within this panel, you can navigate to the AI Hubble tab, which allows you to view:
Name: Identifier for the AI opportunity
Description: Detailed explanation of the opportunity
AI enablers: Technologies that can support the opportunity:
Conversational AI: Facilitates human-like interactions through natural language processing, enabling chatbots and virtual assistants to understand and respond to user queries effectively.
Cognitive AI: Emulates human cognitive functions such as learning, reasoning, and problem-solving, allowing systems to perform tasks that typically require human intelligence.
Workflow AI: Streamlines and automates business processes, enhancing operational efficiency by reducing manual intervention and optimizing task management.
Prediction AI: Utilizes historical data and machine learning algorithms to predict future events or trends, aiding businesses in making informed decisions.
Content AI: Assists in the creation, management, and curation of digital content, including text, images, and videos, thereby boosting productivity and creativity.
Insight AI: Analyzes large datasets to extract meaningful insights and patterns, providing valuable information that supports strategic planning and decision-making.
Manage AI opportunities
Click on the AI Opportunities tab to explore AI agents related to the selected step.
Review both essential and optional agents displayed for the current step.
Essential agents are required for the process to function properly. Optional agents can enhance functionality, but are not mandatory.
Each AI agent provides the following information:
Agent name: The name of the AI agent
Description: A detailed explanation of the agent’s functionality
Data sources: Indicates the data the agent utilizes
AI enabler type: Technologies supporting business automation opportunities (e.g., Workflow AI or Content AI)
Priority tag: Marked as Essential or Optional
Plug icon: Indicates the option to generate embedded AI
Select, edit, or delete agents according to your requirements.
Create a new AI opportunity by clicking the '+' button.
Please provide the following information to create a new opportunity:
Name Enter a clear and descriptive name for the opportunity.
Description Briefly describe the purpose and scope of the opportunity.
Technologies Select one or more relevant technologies from the list.
Data Sources Enter the data source(s) and click ‘+’ to add additional entries.
Generate AI opportunities
Click the ✨ (Glitter icon) to generate AI opportunities using LLM. A confirmation dialog will appear with the message "Generate more AI opportunities?" Click ‘Yes’ to proceed with the generation process.
After the generation completes, review suggestions and select those that align with your objectives.
Configure enterprise context
Click the 🏢 (Building icon) to open the enterprise context panel.
Input your industry and industry description in the company tab.
In the Technology/Data landscape tab, define your organization's technological ecosystem:
1. Select applicable enterprise platforms
Browse through the list of technology categories and indicate whether each platform is relevant to your environment by toggling between "Applicable" and "Not Applicable."
2. Configure each applicable platform
For every selected platform, provide the following detailed information:
Technology Vendor (e.g., ZBrain)
Version for the specific technology implementation
Aligned Business Functions using the dropdown menu
Data Source Details, including comprehensive information about the data sources and their characteristics
3. Available platform categories include:
GenAI Development Platform
ERP
CRM
HCM
SCM
Business Intelligence & Analytics
Collaboration & Communication
Cloud Infrastructure
Service Management Platforms
Project Portfolio Management
Marketing Automation
E-commerce
Corporate Performance Management
Procurement Management Platform
4. Add custom platform categories
If your organization uses technologies not covered in the predefined list, you can create custom categories:
Click ‘+ Add Platform Category’ to open a centered modal window
Enter the platform name
Provide a detailed description outlining the platform’s purpose and functionality within your organization
Click ‘Save’ once done.
Import/export data
Click the ≡ (Three lines icon) to access import/export options.
Import options:
TXT format
ZIP archive
XML format
Export options:
XML format
ZIP files
PNG image
SVG vector graphic
Once all configurations are complete, click ‘Save’ to store the process flow.
Proceed to the next step
Click 'Next' to continue to the agentic workflow stage.
Agentic workflow
The agentic workflow page visualizes how AI agents will interact within your business process to create an end-to-end automated solution.
Workflow visualization
BPMN-style diagram: Business Process Model and Notation diagram showing the complete workflow.
Swim lanes: Horizontal sections representing different roles or departments.
Agent nodes: Icons representing AI agents handling specific tasks.
Decision points: Diamond shapes showing conditional paths based on process conditions.
Agent components
Each agent in the workflow:
Is represented by a distinct icon
Was selected through AI Hubble's intelligent recommendation
Is based on process requirements defined in the previous process flow step
Handles specific tasks within the overall process
Agent overview panel
The right panel displays each agent’s name, designation(required/supplementary), a detailed description, and key benefits.
Workflow interactions
The diagram shows:
Sequential connections between agents
Parallel processes where applicable
Decision points determining different path options
End points for process completion
Proceed to the next step
Click 'Next' to continue to the business & impact assessment step.
Readiness & Impact
The Readiness & Impact section allows you to evaluate the feasibility, benefits, and costs of your AI solution.
Solution overview
This page displays:
Solution name
Estimated ROI (Return on Investment)
Estimated benefits
Feasibility status
Benefits
Preliminary cost estimate
Feasibility assessment
Click the 📗 (Book icon) under feasibility to perform the assessment.
A panel will open with questionnaire pages for:
Security/governance: Data security, compliance, and governance considerations
Infrastructure: Technical infrastructure requirements and readiness
AI talent: Skills and resources needed for implementation
Data: The quality, structure, accessibility, and overall readiness for integration.
For each question, select the appropriate score:
N/A: Not applicable
Low: Minimal readiness
Medium: Partial readiness
High: Full readiness
Add comments for context if needed.
Complete all questionnaire pages by clicking 'Next' to proceed between pages.
Click ‘Review’ in the Data Assessment column to open the questionnaire panel for each data source.
Click 'Save' when all sections are complete.
Based on your responses, the system will generate a readiness score and feasibility status:
Ready: Indicates minimal barriers to implementation
Remediate: Suggests addressing identified gaps before proceeding
Benefits analysis
Click the💲to open the benefit analysis panel.
The interface allows you to quantify expected business value across multiple dimensions:
Revenue growth:
Revenue
Price
Volume
Customer experience:
Customer satisfaction
Customer churn
Customer LTV
Customers (Customer count)
Process productivity:
Speed (Processing speed in hours)
Process volume
Process accuracy
Employee productivity:
Units per FTE
Capacity/creation (time in hours)
Cost savings:
FTEs
Cost reduction
Cost per unit
Working capital:
Days Sales Outstanding (DSO)
Days Payable Outstanding (DPO)
Days Inventory Outstanding (DIO)
For each metric, enter:
Current baseline: Present performance values
Target: Expected future performance after implementation
Comments: Context, assumptions and justification for projections
Click '+ Add benefits' to include additional metrics if needed.
The system will calculate total benefits based on your entries.
Preliminary cost estimation
Click the ✨ (Glitter icon) under preliminary cost.
The system will generate an implementation cost estimate using LLM.
Review the estimated cost.
Proceed to the final step
Upon calculation of the preliminary cost, the system automatically generates and displays the projected ROI percentage, quantified benefits value, and impact levels across five key business dimensions.
Click 'Next' to continue to the summary overview.
Summary overview
This section provides a comprehensive view of your AI solution and its expected impact.
Solution summary
The page displays:
Overview: Summary of all agents in the solution
Impact: Expected business impact areas
Data readiness: Status of data source preparation
Feasibility: Overall implementation readiness
Infrastructure score
AI talent score
Security/Governance score
Total benefits: Calculated financial benefits
ROI: Return on investment percentage
Preliminary cost: Estimated implementation cost
Next steps
Click '+ Send to Portfolio' to add this solution to Portfolio XPLR for prioritization against other AI initiatives.
This enables your organization to compare and rank multiple AI solutions based on business value, feasibility, and strategic alignment.
By following this guide, you can effectively use Solution XPLR to design comprehensive AI solutions tailored to your organization's specific needs. The structured approach ensures that all aspects of the solution, from data requirements to impact, are thoroughly considered and documented before implementation begins.
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