SiftHub’s AI assistant is built on open-source large language models (LLMs), and is supported by retrieval augmented generation (RAG) technology, which uses additional data sources to fine-tune the quality of content generated by AI.
All that eventually brought her focus to sales and presales teams.
“Sales teams have a shadow team — a presales team or solutions engineers — and they are usually the unsung heroes of the organization.
Sales and presales teams lack the necessary tooling to handle this new selling environment.
We are excited to back the SiftHub team and be a part of their ambitious journey,” said Sanjay Nath, a partner at Blume Ventures.
When Anomalo’s co-founders left Instacart in 2018, they thought they could put machine learning to work to solve data quality problems inherent in large data sets.
Five years later, the company’s idea is even more relevant as data quality takes center stage with large language models.
Today, the startup announced a $33 million Series B, equaling their 2021 Series A and bringing the total raised to $72 million, according to the company.
As companies store increasingly large amounts of data in cloud storage and data warehouses like Databricks and Snowflake, this need has only become more pronounced, he says.
SignalFire led the $33 million Series B investment with participation from strategic investor Databricks Ventures.
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