Working with data is one of the most difficult parts of building and running applications. As cloud ecosystems and developer toolsets increase in complexity, managing data sources remains a significant obstacle to developer productivity. Neurelo is a new company that emerged from stealth today to deliver a comprehensive data access platform that streamlines and accelerates cloud application development. To learn more about how Neurelo makes it easier for developers to work with databases, I talked with Chirag Shah, co-founder and CEO.

VMblog:  Databases are complex by nature. What issues are developers facing today?

Chirag Shah:  Developers face a number of challenges working with databases. Given the complexity of these systems as an organization's application and data needs grow, even experienced developers find themselves spending hours or even days debugging and optimizing queries to achieve the desired performance.

One key issue is the "ORM Conundrum." Object-Relational Mapping (ORM) technology aims to bridge the gap between the object-oriented world of programming and relational databases, but often falls short of expectations. It can introduce technical debt, hinder flexibility, and complicate the development process. Developers face performance overhead, because ORM frameworks can generate inefficient SQL queries, leading to suboptimal database performance. As queries get complex, ORM becomes less effective; ORM frameworks also have limited flexibility, as they impose a certain structure on a database schema.

Another major issue is Application Programming Interface (API) development. Building robust APIs on top of databases is essential for modern applications. However, it involves a significant amount of boilerplate work, including configuring routes, writing code for CRUD (Create, Read, Update, Delete) operations, and creating comprehensive documentation. Developers often need to write repetitive code for handling common CRUD operations, validating incoming requests, managing authentication and authorization, and documenting the API endpoints for others to consume.

These challenges are compounded when dealing with advanced database queries, such as aggregations, filtering, or joining multiple tables. Writing efficient and secure code for such scenarios requires a deep understanding of both the database and the application's requirements.

VMblog:  Neurelo introduced its first GA product today. How does Neurelo improve the way developers work with databases?

Shah:  Neurelo improves developer workflows with its comprehensive and extensible data access platform that enhances developer productivity by simplifying and accelerating the way they build and run applications with databases. The Neurelo Cloud Data API Platform delivers four key innovations.

Auto-generated APIs instantly generate purpose-built REST and GraphQL APIs for data access from applications, eliminating developer reliance on ORM and server-side frameworks. Neurelo ensures that its APIs are specifically developed to meet the needs of the application being built. It also automates API documentation and version control, eliminates the need for third-party query builders, and automatically handles changing code and schemas.

AI-generated custom-query endpoints enable developers to use AI to easily generate and fine-tune custom complex queries with optimization recommendations using natural language prompts, regardless of the database type or language. Neurelo trains its AI models on database-specific syntax and semantics, resulting in query code generation efficacy ranging from 75 to 90 percent, well above the industry average of around 50 percent.

Query observability shows developers exactly what is happening with every API as it is called. With Neurelo, every read and write operation gives developers an improved understanding of day-to-day application posture. This helps developers identify and remediate hotspots, bottlenecks, noisy neighbors and other complexities.

Schema as Code automates how developers create, deploy, and evolve their schema, enabling developers to easily manage application and database changes without manual intervention. It provides a centralized, codified repository for automated collection and management of metadata. This eliminates the Visio diagrams and other arduous manual processes developers often must use to capture schema, resulting in faster iteration cycles and a more robust, reliable, and maintainable architecture.

VMblog:  Generative AI is transforming many aspects of the development cycle. How does Neurelo leverage automation and AI?

Shah:  Neurelo's application of AI and automation to API generation empowers developers to leverage the full potential of API gateways and abstractions, transforming the way they build and maintain applications that rely on databases.

As developers embrace GenAI to build and modernize apps, they can simplify their approach by abstracting dependencies between applications and databases through Neurelo's comprehensive data access layer. Neurelo's auto-generated APIs automatically generate REST and GraphQL endpoints directly from users' data models and schemas. These endpoints are designed for a wide range of data operations, and are fully documented and version controlled.

Neurelo's auto-generated Data APIs and AI Assist feature also speeds up the development process and reduces the likelihood of syntax errors and query optimization issues. Developers can use AI in Neurelo to create and customize complex queries using natural language prompts, and this applies to any database or language. Neurelo trains its AI models on database-specific syntax and semantics, meaning its query code generation efficacy is far above the industry standard. This innovative approach to AI-generated queries eliminates the writing of the hundreds of lines of code that complex queries often require; along with the expert analysis, rewriting, manipulation and modification needed to iterate on new application features.

In essence, Neurelo's use of AI and automation shortens time to production and eases ongoing management. This enables developers to leverage the full potential of API gateways and abstractions, transforming the way they build and maintain applications that rely on databases.

VMblog:  You also announced seed funding today. How will that be used?

Shah:  Since securing seed funding, we've built a robust R&D team to bring our vision to life and build the 1.0 product that we announced today. We will continue to expand our R&D team, and increase investments in developer-centric go-to-market functions, emphasizing product-led growth.

VMblog:  What else should VMblog readers know? What should readers expect from Neurelo in the future?

Shah:  This is just the beginning for us. We're confident that our Cloud-based Data API Platform approach to database programming interfaces will streamline complexities in performance, scale, security, optimization and manageability. In constant learning from our users, we're committed to swiftly rolling out new features that further simplify their work. We are seeing compelling opportunities to harness AI capabilities, empowering developers to seamlessly use and operationalize generative AI, thereby simplifying and accelerating their software development lifecycle.

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Chirag Shah is the Co-Founder and CEO at Neurelo. Shah is a dynamic leader with a passion for building projects that deliver business value and improve developer experience. Prior to Neurelo, Shah led MongoDB's database product organization, where he was part of the core product leadership team that helped drive business growth from $350M to $1.2B in ARR. Prior to MongoDB, he worked with the product and go-to-market teams at VMware. Shah received his undergraduate degree from the University of Mumbai and an M.S. in Computer Science from Binghamton University.