.svg)
DURATION
4 weeks
This project involved transforming a traditional support-heavy B2B order system into a seamless, AI-powered WhatsApp assistant. The client, a Germany-based automotive eCommerce company, aimed to simplify how recurring clients placed part orders, eliminating manual lookups and delays.
To solve this, Linnify created an AI bot that was able to handle full conversational flows and dynamically assist users with smart product inquiries, order processing, and recommendations. The result was a dramatically more efficient, human-like experience for repeat buyers.
In the automotive B2B sector, clients often reorder parts with incomplete data or poor context, requiring back-and-forth communication with support teams. Traditional channels like email or phone introduce delays, frustration, and lost opportunities. Moreover, most businesses lack automation tailored to domain-specific questions, slowing down transactions and decreasing customer satisfaction.
The platform targets the broader European market, with strategic emphasis on the DACH region (Germany, Austria, and Switzerland) and Eastern European countries.
B2B clients prioritize reliability, speed, and professionalism. The chatbot was designed to offer instant results while maintaining a clear, informative tone that aligns with local business etiquette and expectations.
The client’s B2B ordering process was heavily dependent on manual support via WhatsApp or email, requiring multiple asynchronous exchanges to clarify product details, compatibility, and availability.Clients would often start with vague requests that demanded time-consuming clarifications from human agents.
This led to:
The client needed a scalable, intelligent solution that could guide users through the ordering flow without the need for manual back-and-forth, while still delivering accurate, relevant, and context-aware results.
Create an AI Bot that can handle the order processing flow, respond to questions, and assist the user with the right questions to search the relevant products or address any questions regarding the product information.
Our goal was to enhance the user experience by making interactions with the bot more human-like. This included guiding users through the order process, addressing their questions or concerns proactively, and streamlining the conversation flow.For users interested in purchasing specific products, the chatbot engages more conversationally, asking questions such as:
Botpress served as the foundational framework for the solution, ensuring seamless WhatsApp integration and the capacity to address general inquiries while fostering more naturalistic interactions through its AI Tasks feature. For scenarios demanding nuanced responses to product-related questions, the functionalities of Botpress were augmented with a specialized API that incorporated the OpenAI Assistant API, enabling the AI Bot to accurately answer user questions based on detailed product data.
This innovation has redirected B2B client interactions away from the support team, condensing the order placement process to a mere 2-3 minutes for those familiar with the product. This marks a significant improvement from the prior asynchronous exchanges between clients and the support team, which could potentially lead to client dissatisfaction and lost sales opportunities.
Making the AI chatbot exhibit human-like conversational abilities and linking it seamlessly with an external database for immediate data access posed a significant challenge.
To achieve this, we employed Botpress to refine the AI Bot’s interactions, making them closely resemble human conversations. Additionally, the OpenAI Assistant API provided the bot with a broader context and enabled it to deliver more accurate responses, particularly for complex inquiries related to product specifications.
This required a blend of software engineering and AI integration to ensure the solution could not only engage in natural dialogues but also access and interpret extensive product information effectively, thereby enhancing user engagement and service efficiency.
The whole project, from initial research to the final development, was completed in just 1 month. During this time, a tech lead and a backend engineer worked together to set up Botpress and add a new feature that lets it talk to the OpenAI Assistant.
Their job was to get Botpress up and running, build a special API for the assistant, and add a new microservice to the existing Azure setup using Lambda functions. This effort was key to making sure the AI Bot worked smoothly, offering natural conversations and quick access to a wide range of information.
This project demonstrated how AI-powered tools can dramatically improve B2B ordering experiences. With this solution, Linnify delivered an intuitive WhatsApp assistant that automates complex order flows while maintaining a personal touch, setting a new standard for automotive procurement efficiency.
The project strengthened Linnify’s ability to combine Botpress, AI conversational flows, and external data integrations under tight timelines. It also showcased how AI can be successfully embedded in existing channels (like WhatsApp) to drive speed, accuracy, and customer satisfaction.
The ordering process required multiple asynchronous exchanges via WhatsApp or email to clarify product details. This led to delays, support overload, and inconsistent customer experiences.
The AI bot guides users through the order flow, asks clarifying questions (e.g., car model and year), and responds to product inquiries using data from an external source—reducing support reliance and improving speed.
Linnify used Botpress for WhatsApp integration and conversation design, and integrated the OpenAI Assistant API to enhance product-specific responses with contextual accuracy.
The complete solution—including research, Botpress setup, API integration, and deployment—was delivered in just 4 weeks by a small team (tech lead + backend engineer).
Order processing time dropped from prolonged async conversations to just 2–3 minutes, significantly reducing support team workload and enabling faster, scalable client service.
A custom API and microservice setup allowed the bot to access detailed product information from an external database, ensuring accurate answers during the order conversation.
The solution is built for automotive B2B clients in the DACH and Eastern European regions, where fast, reliable, and professional customer interaction is a priority.
