According to the World Economic Forum, Powerful AI applications can help educational institutions serve their communities by streamlining tasks and increasing engagement. EdTech company Element451 seeks to provide these tools to fuel smarter, more connected campuses. Using MongoDB, Element451 developed an advanced AI platform, improved flexibility, and scaled by 80% year over year — all with the aim of helping higher education organizations reach students more effectively.

Element451 launched its first products in 2015. What began as simple solutions for online student applications and event management quickly grew into an all-in-one CRM and student engagement platform for higher education institutions. Now, Element451 uses AI to provide tools and technology to administrative teams to manage communication and data across the student journey — from marketing to prospective students to keeping in touch with alumni.

The earliest version of the platform was built using SQL and a relational database, but Element451 soon realized that SQL was too rigid to meet the needs of its developers and customers. “Using SQL, we needed to preplan everything,” said Petar Djordjevic, chief technology officer at Element451. “It really slowed us down as we were trying to add new types of applications and enrich our data model.”

The team wanted the ability to store all student data in a single place and to quickly add more properties. It saw MongoDB’s document model as a way to gain greater flexibility overall. So in 2013, the company deployed a self-managed MongoDB document database solution through Amazon Web Services. On MongoDB, the company offered its CRM customers the ability to define their own data using custom fields. This meant that higher education facilities could tailor their online application questions, helping them gather everything from a prospective student’s name and contact information to their T-shirt size.

Element451 saw the opportunity to further enhance its platform by using a managed solution, which would eliminate the need for a dedicated team to handle deployments, security, and backups and would grant the team access to advanced features. “We wanted to focus on building our solution and solving problems for schools, not managing a database,” said Djordjevic. In 2020, Element451 decided to migrate to MongoDB Atlas, an integrated suite of cloud database and data services to accelerate and simplify building with data.

Element451 planned its migration to MongoDB Atlas independently, then optimized its strategy with help from the MongoDB Atlas team. “Having the MongoDB Atlas team point out what we were doing well and what we could do better was a big help,” says Djordjevic. “After that, we didn’t need a lot of help to continue using MongoDB Atlas ourselves. We could just focus on building our product.” The company also used the MongoMirror tool to complete the migration with minimal downtime.

After the success of its migration to MongoDB Atlas, Element451 began adopting new MongoDB tools and features. For example, it implemented MongoDB Atlas Search, a relevance-based search tool, in 2021 to conduct fast searches across all contexts in its database. Before, the company used a third-party solution as well as a custom-built syncing engine to conduct searches, which complicated data consistency. Now, it doesn’t need to manage other systems. “We’ve reduced our footprint using MongoDB Atlas Search,” said Djordjevic. “The simpler the system is to manage, the faster we can build new solutions.”

Petar Djordjevic, Chief Technology Officer

The team also adopted Atlas Search Nodes to better optimize performance and continue to provide the best possible product experience to their users. With Search Nodes, Element451 was able to offload the search workload onto its own dedicated, node distinct from the database, to isolate and scale independently. The result was blazingly fast search and operations, with a simultaneous large reduction in lag, especially during peak usage times. After adopting Search Nodes, the team saw CPU usage go from almost complete saturation to 30% to 40% usage during peak hours, while average execution times improved by 10X, dropping down to 10 to 20 milliseconds.

As an AI-first company, Element451 was also eager in 2024 to implement MongoDB Atlas Vector Search, which helps developers build intelligent applications powered by semantic search and generative AI. Element451 also uses Atlas Vector Search to find relevant media in a database, which customers can use to quickly build marketing campaigns and landing pages.

AI is embedded in every workflow of Element451’s platform, from analyzing data to building full marketing campaigns. It also provides AI assistants for students and staff that help with tasks such as answering questions, scheduling appointments, registering for events, and summarizing data. The company’s customers have had more than 100,000 conversations with AI assistants in less than one year, which lightened the load on teachers and administrators and reduced call volume for some customers by 14%. “We wanted to be a company that has AI in its culture,” said Djordjevic. “So, AI needs to be at the core of our platform.”

Since first adopting MongoDB, Element451 has scaled from 15 customers to more than 200, an 80% year-over-year growth since 2020. On MongoDB, the company is far from reaching any scaling limitations.

Its platform is also growing. Element451’s database processes 70,000 jobs per minute, and it has helped institutions complete 2 million tasks and process more than 1 million admission applications. By taking advantage of the flexibility and scalability of MongoDB Atlas, the company’s developer team also rolled out more than 1,200 updates, including brand-new features and tools, in only a year. “It’s really easy to make updates using MongoDB Atlas,” said Djordjevic. “We don’t need to change the data model entirely to accommodate future features.”

Element451’s customers also benefited from the company’s migration to MongoDB Atlas. For example, one college not only saw increased enrollment three years in a row, but it also noted a significant uptick in text and email engagement. The AI-powered bots on the platform even reduced call volume by 14% through efficient inquiry management, saving the college’s staff more than 36,000 minutes.

Using MongoDB tools, Element451 is continually improving its platform, leading to growth for the company and its customers. Moving forward, Element451 plans to expand its platform’s features and reach new customers globally. “We’ll never move away from MongoDB,” said Djordjevic. “It works really well for us, and we have a lot of options that we can use and a lot of tools at our disposal.”

Petar Djordjevic, Chief Technology Officer