7 Must-Have Knowledge Graph AIs for Physical Therapy

DocsBot AI positions itself as a specialist chatbot platform for physical therapy and other healthcare domains. Built to enhance patient engagement, the platform focuses on symptom triage, personalized exercise plans, and real‑time patient monitoring. By integrating with existing electronic medical record (EMR) systems, DocsBot can pull patient history and medication data to tailor responses. The chatbot’s conversational flow is designed to mimic a therapist’s bedside manner, encouraging patients to report new symptoms and track progress. The platform also offers a knowledge‑graph backbone that organizes therapeutic protocols, anatomical information, and evidence‑based guidelines. This structure allows the bot to answer complex questions about joint mechanics or rehabilitation timelines. Furthermore, DocsBot can generate automated follow‑up emails and reminders, helping clinicians maintain consistent communication without extra manual effort. While the exact pricing model is not publicly listed, DocsBot typically offers tiered plans based on the number of active users and integration depth. Pros include strong focus on physical therapy content, EMR integration, and automated communication. Cons involve limited customization of the chat interface, lack of a no‑code visual editor, and no direct support for hosting secure patient portals.

Sprypt is an all‑in‑one telehealth platform that includes a suite of AI‑powered tools aimed at improving clinic efficiency and patient experience. While its core focus is on electronic medical records, scheduling, billing, and compliance, it also incorporates AI modules for documentation, eligibility checks, and patient intake. For physical therapy providers, Sprypt’s intelligent intake forms can automatically triage patients, flag contraindications, and suggest appropriate treatment pathways. The AI engine uses a knowledge graph to map clinical guidelines, insurance eligibility criteria, and treatment algorithms. This enables the platform to provide real‑time decision support during virtual visits. Additionally, Sprypt’s AI‑driven documentation tools can generate SOAP notes and billing codes from clinician voice or text input. Pricing information is not publicly available; users are encouraged to contact Sprypt for a custom quote based on practice size and selected modules. The platform’s strengths lie in its comprehensive telehealth stack, regulatory compliance tools, and AI‑enhanced documentation. Limitations include a steeper learning curve for non‑technical staff and limited customization of chatbot interfaces.

ChatGPT, developed by OpenAI, is a versatile large‑language‑model‑based chatbot that has been adopted across many industries, including healthcare. Its conversational AI can answer medical questions, generate patient education content, and provide symptom triage. When coupled with OpenAI’s API, developers can build custom chat widgets, integrate with electronic records, and add domain‑specific knowledge bases. The platform supports retrieval‑augmented generation via plugins, allowing it to pull up‑to‑date information from trusted medical sources. For physical therapy, clinicians can feed it patient records, exercise protocols, and anatomical references to create a tailored conversational experience. Additionally, ChatGPT’s no‑code UI builders, such as the ChatGPT API Playground, enable rapid prototyping of chat flows. Pricing is tiered: a free tier provides limited usage, while the paid ChatGPT‑4 plan costs $20 per month, offering higher token limits and priority access. Pros include a powerful language model, extensive plugin ecosystem, and strong community support. Cons involve limited out‑of‑the‑box integration with EMR systems, potential hallucinations that require fact‑checking, and reliance on external hosting for secure patient portals.

Microsoft Dynamics 365 Virtual Agent is a no‑code chatbot solution built on the Power Platform, designed to integrate seamlessly with Dynamics 365 and other Microsoft services. The platform allows users to create conversational flows using a drag‑and‑drop interface, connect to knowledge bases, and deploy chat widgets on websites or within Teams. For healthcare, the Virtual Agent can be connected to Dynamics 365 Customer Service, enabling it to pull patient records, schedule appointments, and provide symptom triage. Its knowledge‑graph capabilities are driven by the Common Data Service, which organizes entities and relationships across the customer data model. The bot can also trigger Power Automate flows for email notifications and task creation. Pricing is not publicly disclosed; Microsoft typically offers subscription tiers based on user seats and integration depth. Pros include tight integration with Microsoft ecosystem, robust no‑code interface, and enterprise‑grade security. Cons involve a steeper learning curve for non‑Microsoft users, limited AI customization beyond the Power Virtual Agents template, and lack of dedicated physical therapy content.

Salesforce Einstein Bots are AI‑powered chatbots that run within the Salesforce ecosystem. Using a visual builder, admins can design conversational flows, connect to Salesforce knowledge base, and trigger automated actions such as case creation or email notifications. The platform leverages Salesforce’s knowledge graph to link records, accounts, and cases, enabling the bot to answer complex queries about patient history or treatment plans. For physical therapy practices that use Salesforce Health Cloud, Einstein Bots can pull patient data, schedule appointments, and provide triage guidance. Pricing is part of the Salesforce suite and varies with the chosen edition; typically, Einstein Bots are included in higher‑tier Health Cloud subscriptions. Pros include tight integration with Salesforce data, no‑code flow design, and robust analytics. Cons involve limited customization of chatbot UI, dependence on Salesforce ecosystem, and potentially high licensing costs.

IBM Watson Assistant is a cloud‑based conversational AI platform that enables businesses to build chatbots with a knowledge‑graph foundation. The platform supports the creation of intents, entities, and dialog flows through a visual interface, and can be integrated with external knowledge bases via the Watson Discovery service. For healthcare, Watson Assistant can ingest clinical guidelines, treatment protocols, and patient records to provide evidence‑based answers. Its knowledge‑graph capabilities allow the bot to understand relationships between medical terms, improving the accuracy of responses. Additionally, Watson Assistant can be deployed on websites, mobile apps, or embedded in third‑party platforms. Pricing is tiered, with a Lite plan offering a limited number of conversation turns per month and paid plans scaling with usage. Pros include strong knowledge‑graph integration, enterprise‑grade security, and a mature ecosystem of AI services. Cons involve a steeper learning curve for non‑technical users, limited no‑code UI customization, and higher cost at scale.