Fortress: AI-Powered Legal Deal Workflow Automation Platform on Salesforce
Challenge
Project Fortress needed to manage complex legal transactions involving large volumes of unstructured data, including contracts, emails, and compliance documents. Legal teams relied on manual processes to extract, structure, and track information, creating delays and increasing the risk of errors.
Workflow coordination across stakeholders required constant manual updates, while maintaining Salesforce as the system of record imposed strict requirements on data integrity, security, and access control. Introducing AI into these workflows required a system that could automate document processing and task management without compromising compliance or removing necessary human oversight.
Project Fortress needed to manage complex legal transactions involving large volumes of unstructured data, including contracts, emails, and compliance documents. Legal teams relied on manual processes to extract, structure, and track information, creating delays and increasing the risk of errors.
Workflow coordination across stakeholders required constant manual updates, while maintaining Salesforce as the system of record imposed strict requirements on data integrity, security, and access control. Introducing AI into these workflows required a system that could automate document processing and task management without compromising compliance or removing necessary human oversight.
Solution
A multi-agent AI system was built using Wippy to automate document processing, workflow execution, and data synchronization with Salesforce. Agents parse and structure unstructured legal documents, extract key information, and convert it into queryable data used across deal workflows.
The system integrates with Salesforce through secure APIs, enabling real-time synchronization while preserving role-based access control and maintaining Salesforce as the authoritative data source. Temporal-based orchestration supports long-running workflows with auditability, failure recovery, and controlled execution.
Agents coordinate across tasks such as checklist generation, issue tracking, and task assignment, reducing manual coordination. Human oversight is built into the system, allowing legal professionals to review and intervene when needed.
The architecture supports multiple AI models and includes a modular registry system for managing agents, tools, and workflows across different legal use cases.
A multi-agent AI system was built using Wippy to automate document processing, workflow execution, and data synchronization with Salesforce. Agents parse and structure unstructured legal documents, extract key information, and convert it into queryable data used across deal workflows.
The system integrates with Salesforce through secure APIs, enabling real-time synchronization while preserving role-based access control and maintaining Salesforce as the authoritative data source. Temporal-based orchestration supports long-running workflows with auditability, failure recovery, and controlled execution.
Agents coordinate across tasks such as checklist generation, issue tracking, and task assignment, reducing manual coordination. Human oversight is built into the system, allowing legal professionals to review and intervene when needed.
The architecture supports multiple AI models and includes a modular registry system for managing agents, tools, and workflows across different legal use cases.
Results
The platform runs in production as a legal transaction management system that automates document analysis and workflow coordination. It includes over 50 agents and 800 tools operating across deal workflows.
Manual data entry was reduced by 80%, while document parsing accuracy reached up to 90%, accelerating contract analysis. Deal processing speed increased by up to three times, enabling legal teams to focus on higher-value work.
The system maintains strict data security and compliance standards while supporting scalable, multi-tenant deployment and ongoing extension by the client’s team without external dependency.
The platform runs in production as a legal transaction management system that automates document analysis and workflow coordination. It includes over 50 agents and 800 tools operating across deal workflows.
Manual data entry was reduced by 80%, while document parsing accuracy reached up to 90%, accelerating contract analysis. Deal processing speed increased by up to three times, enabling legal teams to focus on higher-value work.
The system maintains strict data security and compliance standards while supporting scalable, multi-tenant deployment and ongoing extension by the client’s team without external dependency.