To continue building on our strong base of intelligent automation, Levelpath’s AI Agents are a new category of autonomous, outcome-driven capabilities. They are designed to solve complex procurement challenges without requiring manual intervention or rules-based automation.
At their core, Levelpath’s AI Agents are designed to act autonomously and proactively on behalf of users, solving real procurement challenges such as sourcing event creation, supplier onboarding, and risk assessments to drive exponential productivity. They empower procurement teams to create autonomous assistants that can solve complex procurement challenges and adjust based on real-time considerations, business requirement changes, and stakeholder requests.
These agents do not simply support rigid and fragile task automation; they deliver smarter workflows, faster deployment, and predictable outcomes from day one. With preconfigured agents available out of the box, teams can immediately benefit from enhanced decision-making and operational efficiency without the need for complex IT support.
What truly sets Levelpath’s AI Agents apart is their foundation: they are powered by Hyperbridge, Levelpath’s AI-native architecture that unifies model grounding, context management, agent orchestration, and lifecycle oversight, ensuring seamless data connectivity and compliance-readiness from day one. From ensuring high-quality supplier data to accelerating analysis within the request workflow, Levelpath’s AI-native platform brings intelligence to every step of the procurement process. By identifying the relevant business context, routing queries to the most suitable large language models, and tailoring outputs to specific organizational needs, Levelpath empowers procurement teams to achieve greater efficiency and impact, with fewer resources.
As foundational AI model vendors innovate on a weekly or monthly basis, Levelpath customers can reap the benefits of a platform-centric approach to stay technologically up-to-date while eliminating the need to conduct constant due diligence on the models, protocols, and integrations needed to make AI work.