removed the contract scenario

Author: Dhruvkumar-Microsoft

README.md

@@ -158,7 +158,6 @@ By using the *Multi-Agent Custom Automation Engine* solution accelerator, users
 | Onboarding Employee | HR Manager | Traditional onboarding involves multiple disconnected steps—HR paperwork, IT setup, compliance training—which often require manual coordination and lead to delays. Manual steps slow collaboration and increase overhead, reducing efficiency and employee experience. | Designed to streamline the complex process of bringing new hires into an organization using a modular, agentic architecture. |
 | Retail Remediation | Customer Success Manager | This approach is seeking a smarter way to manage workflows and ensure customer satisfaction. Challenges include difficulty engaging the right agents, inefficiencies from manual processes, fragmented data, and limited security controls. | Using the Multi-Agent Custom Automation Engine, the Customer Success Manager recruits intelligent agents to analyze satisfaction and recommend steps for remediation. The platform’s modular design and reasoning capabilities allow for analyzing dependencies, planning transitions, and reducing manual rework. |
 | RFP Reviewer  | VP of Finance  | Reviewing RFPs manually under tight deadlines is challenging. Compliance checks and risk assessments slow progress, leaving critical gaps and delaying decisions. | Multi-Agent RFP Reviewer is an intelligent platform addresses these issues by deploying AI agents to review RFPs, identify risks, recommend remediation, and execute actions seamlessly - transforming a labor-intensive process into a fast, accurate, and compliant workflow. |
-| Contract Compliance Reviewer | Compliance Counsel  | Reviewing Contracts for compliance manually under tight deadlines is challenging. Compliance checks and risk assessments slow progress, leaving critical gaps and delaying decisions. | Multi-Agent Contract Compliance Reviewer is an intelligent platform addresses these issues by deploying AI agents to review Contracts, identify risks, recommend remediation, and execute actions seamlessly - transforming a labor-intensive process into a fast, accurate, and compliant workflow. |
 
 </details>
 

TRANSPARENCY_FAQS.md

@@ -10,7 +10,7 @@ It is **not designed or recommended for direct production deployment**.
 - **Ensure all implementation decisions consider security, scalability, and compliance requirements for production.
 
 ## What is the Multi Agent: Custom Automation Engine – Solution Accelerator? 
-Multi Agent: Custom Automation Engine – Solution Accelerator is an open-source GitHub Repository that enables users to solve complex tasks using multiple agents. The accelerator is designed to be generic across business tasks. The user enters a task and a planning LLM formulates a plan to complete that task. The system then dynamically generates agents which can complete the task. The system also allows the user to create actions that agents can take (for example sending emails or scheduling orientation sessions for new employees, drafting a press release, customer retail remediation, reviewing contracts, reviewing proposals). These actions are taken into account by the planner and dynamically created agents may be empowered to take these actions.
+Multi Agent: Custom Automation Engine – Solution Accelerator is an open-source GitHub Repository that enables users to solve complex tasks using multiple agents. The accelerator is designed to be generic across business tasks. The user enters a task and a planning LLM formulates a plan to complete that task. The system then dynamically generates agents which can complete the task. The system also allows the user to create actions that agents can take (for example sending emails or scheduling orientation sessions for new employees, drafting a press release, customer retail remediation, reviewing proposals). These actions are taken into account by the planner and dynamically created agents may be empowered to take these actions.
 
 ## What can the Multi Agent: Custom Automation Engine – Solution Accelerator do? 
 The solution accelerator is designed to replace and enhance enterprise workflows and processes with intelligent automation. Agents can specialize in various functions and work together to achieve an objective as specified by the user. The accelerator will integrate seamlessly with existing systems and is designed to scale according to the needs of the customer. The system allows users to review, reorder and approve steps generated in a plan, ensuring human oversight. The system uses function calling with LLMs to perform actions, users can approve or modify these actions.

data/agent_teams/contract_compliance_team.json

@@ -1550,9 +1550,7 @@ param storageContainerNameRetailOrder string = 'retail-dataset-order'
 param storageContainerNameRFPSummary string = 'rfp-summary-dataset'
 param storageContainerNameRFPRisk string = 'rfp-risk-dataset'
 param storageContainerNameRFPCompliance string = 'rfp-compliance-dataset'
-param storageContainerNameContractSummary string = 'contract-summary-dataset'
-param storageContainerNameContractRisk string = 'contract-risk-dataset'
-param storageContainerNameContractCompliance string = 'contract-compliance-dataset'
+
 module avmStorageAccount 'br/public:avm/res/storage/storage-account:0.20.0' = {
   name: take('avm.res.storage.storage-account.${storageAccountName}', 64)
   params: {
@@ -1630,18 +1628,7 @@ module avmStorageAccount 'br/public:avm/res/storage/storage-account:0.20.0' = {
           name: storageContainerNameRFPCompliance
           publicAccess: 'None'
         }
-        {
-          name: storageContainerNameContractSummary
-          publicAccess: 'None'
-        }
-        {
-          name: storageContainerNameContractRisk
-          publicAccess: 'None'
-        }
-        {
-          name: storageContainerNameContractCompliance
-          publicAccess: 'None'
-        }
+        
       ]
       deleteRetentionPolicyDays: 9
       deleteRetentionPolicyEnabled: true
@@ -1653,9 +1640,6 @@ module avmStorageAccount 'br/public:avm/res/storage/storage-account:0.20.0' = {
 // ========== Search Service ========== //
 
 var searchServiceName = 'srch-${solutionSuffix}'
-var aiSearchIndexNameForContractSummary = 'contract-summary-doc-index'
-var aiSearchIndexNameForContractRisk = 'contract-risk-doc-index'
-var aiSearchIndexNameForContractCompliance = 'contract-compliance-doc-index'
 var aiSearchIndexNameForRetailCustomer = 'macae-retail-customer-index'
 var aiSearchIndexNameForRetailOrder = 'macae-retail-order-index'
 var aiSearchIndexNameForRFPSummary = 'macae-rfp-summary-index'
@@ -1867,15 +1851,10 @@ output AZURE_STORAGE_CONTAINER_NAME_RETAIL_ORDER string = storageContainerNameRe
 output AZURE_STORAGE_CONTAINER_NAME_RFP_SUMMARY string = storageContainerNameRFPSummary
 output AZURE_STORAGE_CONTAINER_NAME_RFP_RISK string = storageContainerNameRFPRisk
 output AZURE_STORAGE_CONTAINER_NAME_RFP_COMPLIANCE string = storageContainerNameRFPCompliance
-output AZURE_STORAGE_CONTAINER_NAME_CONTRACT_SUMMARY string = storageContainerNameContractSummary
-output AZURE_STORAGE_CONTAINER_NAME_CONTRACT_RISK string = storageContainerNameContractRisk
-output AZURE_STORAGE_CONTAINER_NAME_CONTRACT_COMPLIANCE string = storageContainerNameContractCompliance
+
 output AZURE_AI_SEARCH_INDEX_NAME_RETAIL_CUSTOMER string = aiSearchIndexNameForRetailCustomer
 output AZURE_AI_SEARCH_INDEX_NAME_RETAIL_ORDER string = aiSearchIndexNameForRetailOrder
 output AZURE_AI_SEARCH_INDEX_NAME_RFP_SUMMARY string = aiSearchIndexNameForRFPSummary
 output AZURE_AI_SEARCH_INDEX_NAME_RFP_RISK string = aiSearchIndexNameForRFPRisk
 output AZURE_AI_SEARCH_INDEX_NAME_RFP_COMPLIANCE string = aiSearchIndexNameForRFPCompliance
-output AZURE_AI_SEARCH_INDEX_NAME_CONTRACT_SUMMARY string = aiSearchIndexNameForContractSummary
-output AZURE_AI_SEARCH_INDEX_NAME_CONTRACT_RISK string = aiSearchIndexNameForContractRisk
-output AZURE_AI_SEARCH_INDEX_NAME_CONTRACT_COMPLIANCE string = aiSearchIndexNameForContractCompliance
 

data/datasets/contract_compliance/compliance/Compliance_file.docx

@@ -1598,9 +1598,6 @@ param storageContainerNameRetailOrder string = 'retail-dataset-order'
 param storageContainerNameRFPSummary string = 'rfp-summary-dataset'
 param storageContainerNameRFPRisk string = 'rfp-risk-dataset'
 param storageContainerNameRFPCompliance string = 'rfp-compliance-dataset'
-param storageContainerNameContractSummary string = 'contract-summary-dataset'
-param storageContainerNameContractRisk string = 'contract-risk-dataset'
-param storageContainerNameContractCompliance string = 'contract-compliance-dataset'
 module avmStorageAccount 'br/public:avm/res/storage/storage-account:0.20.0' = {
   name: take('avm.res.storage.storage-account.${storageAccountName}', 64)
   params: {
@@ -1678,18 +1675,7 @@ module avmStorageAccount 'br/public:avm/res/storage/storage-account:0.20.0' = {
           name: storageContainerNameRFPCompliance
           publicAccess: 'None'
         }
-        {
-          name: storageContainerNameContractSummary
-          publicAccess: 'None'
-        }
-        {
-          name: storageContainerNameContractRisk
-          publicAccess: 'None'
-        }
-        {
-          name: storageContainerNameContractCompliance
-          publicAccess: 'None'
-        }
+        
       ]
       deleteRetentionPolicyDays: 9
       deleteRetentionPolicyEnabled: true
@@ -1702,9 +1688,6 @@ module avmStorageAccount 'br/public:avm/res/storage/storage-account:0.20.0' = {
 
 var searchServiceName = 'srch-${solutionSuffix}'
 var aiSearchIndexName = 'sample-dataset-index'
-var aiSearchIndexNameForContractSummary = 'contract-summary-doc-index'
-var aiSearchIndexNameForContractRisk = 'contract-risk-doc-index'
-var aiSearchIndexNameForContractCompliance = 'contract-compliance-doc-index'
 var aiSearchIndexNameForRetailCustomer = 'macae-retail-customer-index'
 var aiSearchIndexNameForRetailOrder = 'macae-retail-order-index'
 var aiSearchIndexNameForRFPSummary = 'macae-rfp-summary-index'
@@ -1917,17 +1900,11 @@ output AZURE_STORAGE_CONTAINER_NAME_RETAIL_ORDER string = storageContainerNameRe
 output AZURE_STORAGE_CONTAINER_NAME_RFP_SUMMARY string = storageContainerNameRFPSummary
 output AZURE_STORAGE_CONTAINER_NAME_RFP_RISK string = storageContainerNameRFPRisk
 output AZURE_STORAGE_CONTAINER_NAME_RFP_COMPLIANCE string = storageContainerNameRFPCompliance
-output AZURE_STORAGE_CONTAINER_NAME_CONTRACT_SUMMARY string = storageContainerNameContractSummary
-output AZURE_STORAGE_CONTAINER_NAME_CONTRACT_RISK string = storageContainerNameContractRisk
-output AZURE_STORAGE_CONTAINER_NAME_CONTRACT_COMPLIANCE string = storageContainerNameContractCompliance
 output AZURE_AI_SEARCH_INDEX_NAME_RETAIL_CUSTOMER string = aiSearchIndexNameForRetailCustomer
 output AZURE_AI_SEARCH_INDEX_NAME_RETAIL_ORDER string = aiSearchIndexNameForRetailOrder
 output AZURE_AI_SEARCH_INDEX_NAME_RFP_SUMMARY string = aiSearchIndexNameForRFPSummary
 output AZURE_AI_SEARCH_INDEX_NAME_RFP_RISK string = aiSearchIndexNameForRFPRisk
 output AZURE_AI_SEARCH_INDEX_NAME_RFP_COMPLIANCE string = aiSearchIndexNameForRFPCompliance
-output AZURE_AI_SEARCH_INDEX_NAME_CONTRACT_SUMMARY string = aiSearchIndexNameForContractSummary
-output AZURE_AI_SEARCH_INDEX_NAME_CONTRACT_RISK string = aiSearchIndexNameForContractRisk
-output AZURE_AI_SEARCH_INDEX_NAME_CONTRACT_COMPLIANCE string = aiSearchIndexNameForContractCompliance
 
 // Container Registry Outputs
 output AZURE_CONTAINER_REGISTRY_ENDPOINT string = containerRegistry.outputs.loginServer