Hubbler is helping businesses to convert their complex data into a web or mobile application literally overnight with no-code apps.
DQ Channels conducted an exclusive interaction with Vinay Agrrawal, founder of Hubler, exploring how the platform helps businesses convert complex operational data into functional web and mobile applications. The discussion covers Hubler's approach, target market, and the broader opportunity in enterprise no-code platforms.
Agrrawal discusses Hubler's core thesis: enterprise organisations accumulate enormous operational complexity over time, and this complexity is routinely managed through spreadsheets, emails, and manual coordination rather than purpose-built software. The reason is not a lack of awareness — it's that custom software development is expensive, slow, and hard to maintain as requirements change.
No-code platforms like Hubler solve this by giving the people who understand the processes — operations managers, finance teams, procurement leads — the tools to build their own applications directly. Hubler's platform provides workflow builders, form designers, database management, approval routing, and reporting dashboards that can be assembled without programming knowledge.
The DQ Channels conversation explores Hubler's channel strategy and how the platform reaches enterprise customers. Distribution partnerships, system integrator relationships, and direct enterprise sales each play a role in building the customer base. Agrrawal discusses how Hubler's approach to partner enablement helps enterprise customers deploy the platform and build their own internal no-code capability.
Hubler's no-code platform serves enterprise organisations in retail, manufacturing, logistics, and financial services, enabling operations teams to convert complex business processes into web and mobile applications without writing code. Through its channel partner and direct enterprise sales programmes, Hubler helps organisations build internal no-code capability and deploy workflow automation solutions across their operational functions at scale.