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2024 has been a banner year for Perplexity. The AI search startup, founded by former DeepMind and OpenAI researcher Aravind Srinivas, raised hundreds of millions of dollars -- its latest funding round reportedly valuing the company at $9 billion -- and introduced several notable features, including Pages, Spaces, and innovative shopping experiences.
These developments have solidified Perplexity's reputation as an "AI-first" knowledge discovery engine, standing apart from traditional search giants like Google and Bing, which are bolting AI capabilities onto their existing engines.
However, the journey is far from over.
Facing intensifying competition, Perplexity is broadening its scope with a new addition to its portfolio: Carbon. The company has just acquired this startup, for an undisclosed sum, to address the "data gap" enterprises encounter with AI search and streamline the knowledge discovery process in their workflows.
Carbon has developed a comprehensive retrieval framework that streamlines the process of connecting external data sources to LLMs. Users can tap the Carbon universal API or SDKs to sync their data sources and retrieve the data to use with LLMs. It offers native integrations with over 20 data connectors and supports more than 20 file formats, including text, audio and video files.
The expanding scope of AI search
From individuals to business users, almost everyone today uses AI search as part of their workflows. The idea of the technology is pretty simple -- you don't have to go through a swathe of links and content to find relevant insights and information. Instead, the information will come to you as the direct answer to your query.
Perplexity has thrived on this approach, using a range of large language models to retrieve information from the web and simplifying how users work. It even allows teams to extract information from their personal or business files such as PDFs and Word documents.
But, here's the thing. The web is home to public information, and uploading internal files -- PDFs, conversations, images -- individually is not feasible for business users dealing with large volumes of proprietary data. This affects the quality of answers, keeping them generic and devoid of important organization-relevant contexts.
Highlighting this "data gap," Sanjeev Mohan, the former Gartner Research VP for data and analytics, told VentureBeat that one of the biggest AI trends for 2025 will be ETL for unstructured data. It will allow teams to extract and transform data from dispersed internal sources, ultimately powering their LLMs to generate highly relevant and accurate responses.
Now, this is exactly what Perplexity pla ...