Like many other SaaS vendors, Freshworks is working to incorporate AI into its solutions. While many other vendors choose to keep AI as open as possible so customers can use it themselves, Freshworks, on the other hand, nails AI down as far as possible. In doing so, Freshworks says it is opting for the best user experience and consistent results.
During the local Freshworks Refresh event in the Netherlands, we spoke with senior vice president of global engineering Mukesh Mirchandani and Chief Customer and Marketing Officer Mika Yamamoto. Mirchandani stated that Freshworks has been developing AI solutions for about six years now. What is paramount at Freshworks is that AI should not become an out-of-control scientific project. AI should primarily provide usable functionality that you can turn on and use immediately. To this, Yamamoto adds that it looks closely at customer business cases and how AI can be applied to them, as opposed to developing generic AI functions.
Freshworks has a large partnership with AWS, primarily for hosting SaaS solutions. For AI, Freshworks currently primarily uses Azure, which offers an enterprise version of OpenAI. However, Freshworks states that developments are going rapidly, and they have also developed proof of concepts with Amazon’s LLMs. Furthermore, projects are also underway with LLMs from other vendors, such as Anthropic, Meta, and Google.
Domain and industry AI models are the future
According to Mirchandani, Freshworks is keeping its options open at this time. Freddy, as Freshworks’ AI is called, is currently performing satisfactorily. Freshworks needs an LLM for text generation, which Azure currently does just fine. Think of generating responses to support tickets, writing knowledge base articles based on support tickets, etc.
Mirchandani says it is working on domain and industry models for other purposes. Such as determining the next step in a process and understanding specific customer questions to match them to functions.
A good example of a domain model is a refund policy. Customers who want a refund from a retail organization and want to return a product are often subject to rules. For one product it is allowed, for another it is not. One organization uses 30 days, the other 90 days. Then, there are steps to go through. According to Mirchandani, this is best captured in a domain-specific model. That way, a chatbot on the website can handle it much better. According to him, this works better than grounding an existing model with a knowledge base article, for example.
Understanding the customer and starting the right processes
The goal is for such a chatbot to understand what the customer wants and, based on that understanding, automatically start a process that resolves the customer’s question fully automatedly. With a refund, such a process is largely predetermined, but situations will always occasionally occur. Suppose someone has received a broken product and complains about it. The company has always refunded the customer based on previous support tickets with similar complaints. A domain model can then decide to follow that line and give customer his money back automatically.
Wrong dress color delivered?
An AI chatbot gives organisations more efficient customer service and higher customer satisfaction. However, not every customer is good at putting their problem into words. A chatbot can often ask for clarification if the problem is unclear. The fact is that sometimes a picture says much more than words. So Freshworks is also working on photo recognition. They showed a demo of a fictional clothing store where someone had ordered a red dress, but ended up getting a blue one delivered. When the picture of the blue dress was sent to the chatbot, it immediately knew there was a delivery error. It offered to send the correct color as yet.
This is clearly where the future lies, especially in retail. Not only can you detect and solve problems faster, but it’s also much less fraud-sensitive. When customers submit their problems with photos, as a supplier, you also have instant proof, which allows you to act faster and more solution-oriented.
Freshworks stands for AI powered software
At Freshworks, they have now updated their mission statement. The goal is now to deliver AI powered software. In other words, AI will always be part of a solution. According to Mirchandani, Freshworks has taken the right technical steps in recent years to prepare for this.
All Freshworks solutions have been partially redeveloped on the new Neo platform. This cloud-native platform consists of a variety of microservices, which allow Freshworks to innovate quickly. It also ensures that all Freshworks solutions are seamlessly integrated and data is centralized in one customer data platform. There is one customer record with all data that all Freshworks solutions can access.
This enables Freshworks to innovate faster than competitors who are still working with different IT stacks.
Developing AI for customer challenges
Yamamoto is mainly concerned with the customer experience at Freshworks. She insists that innovation at Freshworks comes primarily from examining customer challenges and how existing processes can be improved or further automated.
Adding innovation to business problems, with or without AI, ensures high customer satisfaction. At Freshworks, she also looks at how things can be better aligned. For example, she has brought the sales and marketing teams closer together. Previously, both teams had their reports that served specific sales or marketing functions. Now, reports are more customer-based and serve both teams. This also makes sales and marketing work better together.
According to Yamamoto, Freshworks has already made some great strides, but there is still plenty of room for improvement. Self-service clearly has the future in many industries, and AI can play a big role in that. It can greatly improve the customer experience, resulting in more loyal customers. However, this also raises the bar even higher. Without AI, you will lose the competition of those who use AI.
Yamamoto: “Freshworks solutions are suitable for SMEs and small enterprise organizations”
According to Yamamoto, Freshworks has a strong position in the market. Its solutions are aimed at organizations with 10 to 5,000 employees, making them accessible to all SMEs and small enterprise organizations. Organizations can start using them immediately without needing a whole team of data and AI analysts.
Tip: Freshworks remains flexible and accessible, even with AI