DevRev: Building the Operating System for the GenAI Revolution
- Marsha Mahira
- Jun 27
- 3 min read
With DevRev, any organization can leverage GenAI to synthesize their data into actionable knowledge.
In the 1980s, Intel and Microsoft collaborated to create the personal computer (PC). Intel developed the hardware, while Microsoft built the Windows operating system on top. This partnership revolutionized access to computing.
A similar principle applies in today's GenAI era. Large Language Models (LLMs) can be seen as the hardware. However, LLMs require a "Windows" to drive significant change.
This conviction led Dheeraj Pandey to build DevRev.ai. "DevRev is like an operating system that makes LLM technology beneficial for all organizations," Dheeraj stated during a recent visit to Jakarta.
Dheeraj's belief is significant given his track record. He co-founded Nutanix, a company that introduced a simpler, software-based infrastructure concept. Now, with former Nutanix colleague Manoj Agarwal, Dheeraj is pioneering DevRev. The core idea remains the same: to build a platform that simplifies LLM adoption within enterprises.
This vision has garnered considerable attention. DevRev achieved unicorn status (a company valued at US$1 billion) in 2024, just three years after its inception, making it one of the fastest AI-based companies to reach this milestone.
What is DevRev?
At its core, DevRev is a platform for building conversational AI on top of enterprise data. It allows users to create specific-task conversational AI agents or applications. Using natural language, anyone within an organization can ask AI to find information, summarize reports, or make predictions.
There are three key capabilities that distinguish DevRev. The first is the ability to search company data. "Similar to how Google Search simplifies finding content, DevRev enables searching internal company data, both structured and unstructured," explained Dheeraj. DevRev can search various data types and locations, including sales, customer, and engineering data.
The second is reasoning or the capacity to understand and synthesize diverse pieces of information into knowledge. This enables agents to provide accurate answers to user queries. And the third is to manage workflow, so AI agents are able to perform tasks that previously required human intervention. "With these three pillars, DevRev can be used to create AI agents that address specific company needs," Dheeraj noted.
To facilitate the adoption of Conversational AI, DevRev offers several ready-to-use AI agents, such as those for customer experience.
A simple scenario: A customer reports an issue with a digital product. An AI agent immediately responds by accessing FAQs, support documents, and similar complaints in support apps (like Zendesk or Slack). Based on this information, the agent can provide the necessary answer to the customer.
Simultaneously, the AI agent can detect if the same complaint is reported by multiple customers. This information is automatically forwarded to a project management application (like Jira), allowing the development team to troubleshoot the issue. This illustrates how an AI agent built on DevRev can perform search, analytics, and manage customer service workflows.
Besides customer experience, DevRev also provides ready-made AI agents for employee experience and developer experience. However, Dheeraj emphasized that DevRev allows companies to build other AI agents according to their specific needs. "For example, you can create revenue operations AI agents to analyze company revenue data," Dheeraj illustrated.
Technology Behind DevRev
To achieve such advanced functionality, DevRev developed proprietary technology tailored to the current reality where companies often have data in different formats scattered across various locations. According to Dheeraj, this is natural. "10-15 years ago, companies adopted standalone solutions like ERP, CRM, and project management," he explained.
Therefore, DevRev developed two proprietary technologies called Airdrop and Knowledge Graph. Airdrop unifies data from various locations and types. "So Airdrop sits next to the existing system and co-exists with the legacy system," Dheeraj clarified.
The Knowledge Graph functions as the "brain," organizing and understanding all collected information. Leveraging LLM technology, it synthesizes all information into a cohesive body of knowledge. "The more data sources connected, the better they are reasoned,” Dheeraj stated.
Commitment to Indonesia
With DevRev's capabilities, Dheeraj hopes to make a significant impact on all organizations, including those in Indonesia. "Indonesia has 3.1 million developers contributing to GitHub, the third largest in Asia," Dheeraj noted. He hopes DevRev can help Indonesian developers create AI applications and agents that address specific needs.
Furthermore, Indonesia has a young workforce familiar with GenAI. DevRev can serve as a tool to enhance the productivity of this generation. "Because I believe the key to increasing productivity is knowledge," Dheeraj added. DevRev's ability to allow employees to use natural language to find knowledge will be a crucial tool in boosting productivity.
However, Dheeraj also emphasized that DevRev requires collaboration from various parties to create impactful AI agents. "Therefore, DevRev is committed to continuously fostering communities in various parts of the world, including Indonesia," Dheeraj concluded.
DevRev is shaping the future by creating an operating system tailored for the GenAI era, streamlining development and customer collaboration. While exploring innovations like this, students working on tech-related research can benefit from reliable Dissertation Abstract Writing Services, which help present complex ideas clearly and effectively in academic formats.