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Perplexity’s Carbon integration will make it easier for enterprises to connect their data to AI search

Dec 20, 2024 - venturebeat.com
In 2024, AI search startup Perplexity, valued at $9 billion, acquired the startup Carbon to address the "data gap" enterprises face with AI search. Carbon's retrieval framework allows users to connect external data sources to large language models (LLMs) through a universal API or SDKs, supporting over 20 data connectors and file formats. This acquisition aims to enhance Perplexity's AI search capabilities by integrating Carbon's technology, enabling users to access and retrieve data from diverse sources like Google Docs, Notion, and Slack, thereby making responses more comprehensive and personalized.

The integration of Carbon's technology will streamline enterprise workflows by allowing Perplexity to parse through various data sources to provide direct answers to queries without needing to pinpoint specific documents. This setup is expected to improve customer service, document processing, and other AI use cases. However, the success of this integration depends on execution, particularly in maintaining data privacy and security. Perplexity assures that all internal and private data is encrypted, with additional protections in place. Carbon's managed API operations will cease by March 31, 2025, with existing customers being assisted in the transition.

Key takeaways:

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  • Perplexity, an AI search startup, has acquired Carbon to address the "data gap" enterprises face with AI search, enhancing its knowledge discovery process.
  • Carbon's retrieval framework allows users to connect external data sources to LLMs, supporting over 20 data connectors and file formats, which will be integrated into Perplexity's platform.
  • The integration aims to improve enterprise workflows by providing comprehensive, relevant, and personalized responses without needing to pinpoint specific data sources.
  • Execution and data security are crucial for the integration, with Perplexity ensuring encryption and governance controls to protect proprietary data.
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