Kris@Work: AI-Powered Go-To-Market Execution Platform

Kris@Work, an innovative AI-native go-to-market execution platform designed for enterprise revenue teams, has successfully secured $3 million in seed funding. This funding round was led by Info Edge Ventures, with contributions from JN Capital & Growth Advisory (Singapore) and a selection of angel investors. The funds will be allocated towards expanding the enterprise customer base, enhancing go-to-market partnerships, and completing development across all four stages of the platform, as stated in a recent press release.

About Kris@Work

Established by Arun Singh and Ramakrishna Mallya, Kris@Work is conceived as a new system of work and insights aimed at enabling revenue teams to function more effectively while executing tasks with real-time intelligence. The platform leverages extensive SaaS experience to bridge operational gaps encountered by enterprise teams.

Market Position

Kris@Work functions within a swiftly changing sector of enterprise AI platforms focused on go-to-market and revenue execution. It stands alongside a new wave of global companies that are reimagining the operations of sales, marketing, and customer success teams in an AI-centric landscape.

Features and Benefits

This Bengaluru-based startup consolidates numerous tools into a singular intelligent interface that actively assists users throughout sales and go-to-market workflows. It aims to minimise context switching while automating routine tasks on a large scale. Kris@Work is catering to a burgeoning clientele within the technology, financial services, telecom, and various other industries.

Technology and Future Plans

Utilising a blend of agentic architecture and contextual AI, Kris@Work delivers a seamless platform for go-to-market teams, covering everything from lead identification to deal closure and account growth. The platform offers real-time insights and direction, automates workflows from start to finish, and ensures robust governance.

The company announced that the platform is constructed on a modular, agentic architecture that is intended to extend beyond just go-to-market applications. In the coming three years, Kris@Work aims to broaden this execution layer to additional enterprise functions, employing the same AI-native framework across various aspects of work.