Merge development, deployment, monitoring, and governance into a cohesive environment to avoid fragmented tool solution dependency
Engineered with explainability and traceability as core principles to support ethical and regulatory standards
Use pre-built multi-agent networks to reduce development time and minimize risk
Create new multi-agent networks for various use-cases in a matter of hours rather than weeks using natural language.
Use any API and MCP server to integrate tools into multi-agent networks
Switch between any LLM and/or cloud provider while avoiding vendor lock-in and optimizing cost
We’ve developed an intelligent chatbot that can answer any queries about nursing facilities based on pre-defined structured data from our Knowledge Model. This chatbot can answer questions regarding penalties, staffing details, services, and equipment. By retrieving real-time data from a graph database via natural language queries, our solution ensures quick and accurate results from our comprehensive facility information
We’ve built a powerful RAG-based chatbot designed to respond to queries about patient history. Using a database of the patient’s medical records, surgeries, medications, past interactions with doctors, nurses, and other caregivers, our solution provides instant, context-aware answers. Users can communicate using natural language to retrieve any detail from the patient’s history and also download an entire summary of their history directly from the chat interface.