Genspark, a man-made intelligence search startup that competes with Google LLC, has reportedly raised $100 million in funding.
Reuters today cited sources as saying that the round was led by a gaggle of U.S. and Singapore-based investors. The deal reportedly values Genspark at $530 million, greater than twice what it was value in June.
Genspark, officially Mainfunc Inc., launched last 12 months with $60 million in initial funding. Its namesake search engine topped 1 million monthly users in November. Sources told Reuters that Genspark now has 2 million users, which was likely considered one of the aspects behind the steep increase in the corporate’s valuation.
Genspark’s search engine uses large language models to process queries. When a user types in an issue, the service doesn’t return an inventory of relevant webpages but reasonably displays a natural language answer. Genspark organizes each of its prompt responses right into a webpage called Sparkpages that permits users to ask followup questions.
The corporate also offers a variety of specialized search features. One capability is geared towards browsing e-commerce web sites’ product listings. One other tool, Genspark Finance, visualizes data from earnings reports in graphs to ease evaluation.
One in every of the most recent additions to the search engine’s feature set is a capability called Deep Research. It provides more detailed answers to user queries at the fee of increased wait times: Genspark says that a prompt response can take as much as half-hour to generate. In line with the corporate, the feature spends that point analyzing greater than 1 million words’ value of data from greater than a thousand sources.
Under the hood, Genspark’s search engine is powered by what it describes as a mixture-of-agent architecture. The software sends each user query to LLMs from OpenAI, Anthropic PBC and Google. Genspark removes inconsistencies between the models’ responses after which combines them right into a single answer.
Today’s report didn’t specify how the corporate plans to spend its newly raised funding. One possibility is that Genspark could add reasoning-optimized LLMs to the lineup of models it uses to process prompts.
In line with a Feb. 10 blog post, the corporate’s search engine relies on GPT-4o, Claude 3.5 Sonnet and Gemini 2.0 Flash to reply queries. Those are midrange LLMs that balance output quality with hardware efficiency. Adding a more hardware-intensive, reasoning-optimized model resembling OpenAI’s o1 to the list could potentially help Genspark enhance its search engine’s output.
The corporate’s funding round comes a couple of weeks after Perplexity AI Inc., a competing AI search startup, closed a $500 million investment of its own. The deal reportedly valued the corporate at $9 million. Last week, Perplexity launched a feature much like Genspark’s Deep Research that may generate multipage prompt responses in response to user queries.
Image: Genspark
Your vote of support is vital to us and it helps us keep the content FREE.
One click below supports our mission to supply free, deep, and relevant content.
Join our community on YouTube
Join the community that features greater than 15,000 #CubeAlumni experts, including Amazon.com CEO Andy Jassy, Dell Technologies founder and CEO Michael Dell, Intel CEO Pat Gelsinger, and lots of more luminaries and experts.
THANK YOU
