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Canner: Unlocking Business Data Potential by AI
Many businesses today are sitting on mountains of data, yet they struggle to make sense of it all. That is where Canner, founded by Howard Chi and William Chang, comes in. With their two key products, Wren AI and Canner Enterprise they are helping companies take control of their data. But what exactly are these tools doing to help companies turn raw data into real, actionable decisions?
How Does Wren AI Help Companies Customize Data Retrieval?
Wren AI is designed to handle queries in multiple languages, responding accurately even when technical or company-specific terminology is used. This feature allows organizations to retrieve data based on their unique criteria, such as custom definitions of customer retention rates. The Wren AI Engine further enhances this by enabling companies to define KPIs and metrics, allowing large language models (LLMs) to analyze data according to specific requirements.
Wren AI Connects Data from Multiple Business Departments
Wren AI helps organizations manage data spread across different departments and platforms. For example, departments like sales, marketing, and customer support may use different software, but Wren AI ensures that consistent terminology is applied across the board. It can analyze tools such as Hotspot, Mailchimp, and GA4, responding to queries like "Who opened my emails over the past 30 days?" or "Show me the top 3 campaigns with the highest open rate in 2023."
Wren AI helps users refine their queries. For instance, if a user asks, "What is the total payroll?" Wren AI may offer alternative questions to ensure clarity, guiding users to ask the right questions for the data they need. It also provides a summary of how the results were obtained, helping users understand the steps involved in the analysis.
Canner runs on a subscription model, working with clients in industries like e-commerce, HR, and CRM. Founded in 2016, the company has a small team of 15 people based in Taiwan. About 60% of their users are from the U.S. and Europe, and they've been putting a lot of focus on expanding internationally, especially in the U.S.
Canner is built to solve the problem of combining data from different databases, like SQL and NoSQL, and handling complicated data management. It works with various formats and has a system that lets engineers access data more easily. However, selling Canner Enterprise to industries like banking and pharmaceuticals can take a long time, usually around six months because of the internal reviews and approvals needed in these sectors.
Simplifying Data Access for Engineers in Complex Industries
One of the main problems Canner helps solve is how hard it can be to organize data from different systems, especially when the data is in different formats. For example, what if one database lists gender data differently than another? It becomes tough to put everything together. Canner Enterprise makes this easier by offering tools that help users, even those without coding skills—organize and manage complex data. So, how does Canner Enterprise help with this? It gives users the ability to streamline data from various systems, making everything easier to manage.
While Canner handles the complicated data needs of large companies, Wren AI is designed to make things easier for startups and smaller businesses. Wren AI allows users to get the data they need without knowing how to code or work with databases. This makes data analysis accessible to more people, even those without technical skills.
In the end, Canner’s goal is clear: to make data easier to access for everyone, whether you're part of a big corporation or a small startup. With Canner for complex needs and Wren AI for simpler tasks, they are working to make data retrieval and analysis something that anyone can do, regardless of their technical background.
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