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 plans to do with the acquisition of Carbon’s comprehensive, streamlined retrieval framework. Perplexity will integrate Carbon’s retrieval engine and connectors into its tech stack, giving users of the search platform a direct way to plug in their diverse sources of data, from Google Docs and Notion to Hubspot and Slack.
This, the company says, will expand the knowledge pool powering the AI search engine, making its responses more comprehensive, relevant and personalized to users.
What can users expect from Carbon-powered Perplexity?
While Perplexity has just acquired Carbon and the integration is yet to be executed, it’s pretty easy to imagine how the additional data connectors will improve the workflows of enterprise teams using the AI search engine.
For instance, if one has to move the date for a launch and needs to figure out the latest deadline and guidelines set by their team, Perplexity would be able to parse through all the data in Google Docs, Notion, and Slack — and make necessary correlations — to find the information that answers the question.
In essence, there would be no more worrying about stitching together context from the web, individual apps, and messages. The platform does everything on its own to provide the answer.
“The notable benefit of this setup is that our technology can find the answer without making you pinpoint the document/database where that information is stored,” Sara Platnick, who leads communications at Perplexity, told VentureBeat.
Another example, she said, could be extracting customer meeting insights. Perplexity would be able to fetch the details and focus of the conversation from connected CRMs in no time.
Notably, by leveraging Carbon’s retrieval-augmented generation (RAG) workflows, Perplexity is making enterprise search more accessible, saving companies the hassle of building their own RAG pipelines from scratch.
“By finding and interpreting proprietary data with Perplexity and Carbon, companies can address a range of multi-faceted gen AI use cases. We find the leading adopters are most focused on customer service, document processing, image processing and recommendation engines, Kevin Petrie,” VP of research at BARC US, told VentureBeat.
Execution will be key
Acquiring Carbon is just the beginning. The real key will be execution, or how seamlessly and safely the startup’s tech is integrated. After all, we are talking about proprietary data from some of the most critical knowledge repositories that enterprises maintain.
“Companies are rightly wary of exposing their intellectual property to the public. So Perplexity and Carbon will need to provide governance controls that ensure companies can keep their data inside their own firewalls. They have no interest in sharing secrets or training a public model to mimic their intellectual property,” Petrie added.
On Perplexity’s part, Platnick noted that “all information from internal and private sources on the engine is encrypted, as is all data transmitted and stored in Carbon’s data connectors.” She also pointed out that the company has additional protections to ensure that private documents stay private and aren’t accessible to non-authorized users.
As of now, there’s no specific timeline for the integration of Carbon with Perplexity. However, the startup will cease operations of its managed API on March 31, 2025. Existing customers using the API have already been notified for offboarding, with the Carbon team assisting them in the transition.
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