Ironclad launched Ironclad Agent, an AI platform that helps procurement, legal, and sales teams negotiate contracts more effectively by searching and understanding their company's contract history, past decisions, and approved positions through natural language conversations.
- Ironclad Agent provides a conversational interface for teams to search contracts, ask questions, and access specialized AI agents without generic training data.
- Contract Knowledge Graph connects clauses, relationships, obligations, and past decisions across contracts to give AI agents the context needed for smarter recommendations.
- Policy-Based Access Control replaces traditional role-based permissions with shared policies, making security more scalable as organizations grow.
- Workflow Designer Agent uses guided conversations to help teams build and refine contract workflows faster with automatic compliance to company standards.
- The platform serves customers across software, healthcare, financial services, restaurants, agriculture, and education industries.
Ironclad announced Ironclad Agent, a place for legal, procurement, and sales teams to search, understand, and act on their contracts and workflows using natural language.
The company also announced Contract Knowledge Graph (CKG), which powers Ironclad Agent and grounds all interactions in context from each customer’s contracts, approved positions, and past decisions to surface relationship patterns and potential risks while protecting sensitive data.
“Every business has years of hard-won knowledge in its contracts, including past negotiations, decisions, and learnings,” says Dan Springer, CEO of Ironclad. “That history is a competitive advantage, but only if teams can find and use it when needed. Ironclad Agent helps teams understand the full picture, know where to push, and act with confidence.”
Key takeaways:
● Ironclad Agent serves as the front door to the AI platform, giving teams a single conversational interface to access their contracts and workflows, ask questions about their contracts, and orchestrate specialized AI agents. Ironclad Agent understands your company’s contracts through context from past deals, negotiation decisions, counterparty positions, and internal benchmarks, not generic AI training data or isolated documents.
● Contract Knowledge Graph connects information like clauses, relationships, obligations, and past decisions across a company’s contracts and workflows and organizes it into commercial context for Ironclad Agent. Agents have the context they need to understand how agreements relate to each other, and to learn an organization’s established positions and business practices. This knowledge stays within the company even when the people who have negotiated contracts have moved on.
● Policy-Based Access Control (PBAC) is designed to make AI access more secure and easier to scale as your organization grows, since one policy replaces hundreds of one-off permissions. Most companies use traditional role-based access control (RBAC), which gets harder to maintain because every new team, region, or contract type requires separate permission settings. PBAC replaces these one-off configurations with shared policies that apply to people who meet defined criteria. Whenever teams change, or new regions are added, admins only need to update one policy, making the process more precise, auditable, and scalable. For example, regional teams can only see the contracts relevant to them, without admins needing to create separate setups for each team.
● Workflow Designer Agent builds on Ironclad’s no-code Workflow Designer to make it even easier for teams to build and refine contract workflows faster using a guided conversational interface. Teams describe the process they want, such as who should approve a contract, when a request should be escalated, and where work should be routed, and the agent automatically updates the workflows. Teams can make bulk changes to workflows, and the agent ensures that all new workflows match company standards to prevent them from breaking due to inconsistent or incomplete data.
· These AI agents span customers across industries such as software, business services, medical devices, healthcare, wellness, restaurants, utilities, agriculture, financial services, and education.
