Artificial Intelligence Powered Bot for Healthcare Pharmacy Dealer

The Pandemic caused a disruption in the healthcare system including pharmaceutical and medical device manufacturing & distribution. While there was a surge in demand in certain segments of healthcare products others saw a lull. Balancing the abrupt changes in demand and supply put additional strain on existing communication channels including call centers.

Advent of Artificial Intelligence and technologies like Natural Language Processing has open up possibilities to automate and streamline these communication channels.

At Streebo, we have developed a pre-trained bot specifically for Healthcare Pharmacy & Device dealers that is capable of handling major day-to-day operations. Powered by leading NLP engines such as IBM Watson Assistant, Google Dialog Flow and Amazon Lex Streebo Bot allows dealers to perform critical operations to maintain the stock & track the order status among other functions. The pre-trained Bot can assist dealers to review real-time inventory stock of their respective pharmacy stores and can manage the ordering of drugs that are low in inventory. Also, the bot can manage functions such as check out, online payment, order management. The Pre-Trained bots can be deployed on Web, Mobile App, and asynchronous channels such as Facebook Messenger, WhatsApp, Signal, Telegram, and even SMS. The pre-trained bot can even handle user requests from anonymous users by showing them the latest offers on products and answer any FAQs on products.

Business Benefits

Improved Customer Service

Decreased operational cost as the major operations gets taken over by the Bot

Increase in revenue for both Dealers and Pharma companies

Why Streebo’s Healthcare Pharmacy Dealer chatbot?

Streebo, in collaboration with leading technology organizations like IBM, RedHat, Google, and Amazon, has created a powerful and secured Bot solution. This solution can be integrated into most existing ERP/CRM systems such as SAP R/3, Salesforce, ServiceNow and can be extended to various channels.

Key differentiators of Streebo’s Pre-Trained and pre-integrated AI-Powered bot for healthcare pharmacy dealer:

Built-in Domain Intelligence
Streebo, in collaboration with its technology partner, deploys highly intelligent pre-trained bots for healthcare pharmacy dealers that can emulate business processes pertaining to the healthcare pharmacy & device manufacturing industry.

Omni-Channel Experience
Streebo’s pharmacy dealer bot can be deployed across multiple channels apart from its web and a mobile app, such as internal messaging channels like Microsoft Teams, IBM slack, HCL SameTime, and social media channels like Facebook Messenger, Telegram, Signal, WeChat, WhatsApp, and even SMS.

Integrated with Backends
Streebo’s healthcare pharmacy dealer bot can be integrated with most of the ERP systems such as SAP, JD Edwards, Oracle, or customer relationship management systems such as Salesforce or SugarCRM in use.

Flexible Deployment Models
Streebo’s pre-trained bot for healthcare pharmacy dealers can be deployed on-premises or on IBM Cloud, Microsoft Azure, Amazon AWS, or Google Cloud Platform.

99% Intelligent Bot
Streebo chatbot comes with Guaranteed Bot Intelligence Index* of 99% (*BII= No. of questions answered correctly/No. of relevant questions asked)

Ease of Development & Maintenance
Streebo’s Pre-Trained healthcare pharmacy dealer bot is built using open standards such as Java and Javascript. Also comes bundled in with Streebo’s Pre-Tranied Bot a low code no code tooling to assemble, integrate and manage the bot. Thus, making it easy for both Pharma company’s staff and people in IT with minimal or no background in Artificial Intelligence to assemble, integrate and manage the bot moving forward. Streebo’s Pre-Tranied Bot is an optional development only tooling that customer can choose or they can directly develop and manage it using standard IDEs such as Eclipse and Visual Studio

Chat Analytics
Streebo’s analytics dashboard is developed to record and display systemic data, metrics, preferences, and trends which eventually help in monitoring user interactions, and can be adapted accordingly to give relevant responses and take business decisions.