AI search engine startup Genspark reportedly raises $100M at $530M valuation

Genspark, an artificial 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 group of U.S. and Singapore-based investors. The deal reportedly values Genspark at $530 million, more than twice what it was worth in June.

Genspark, officially Mainfunc Inc., launched last year with $60 million in initial funding. Its namesake search engine topped one million monthly users in November. Sources told Reuters that Genspark now has two million users, which was likely one of the factors behind the steep increase in the company’s valuation. 

Genspark’s search engine uses large language models to process queries. When a user types in a question, the service doesn’t return a list of relevant webpages but rather displays a natural language answer. Genspark organizes each of its prompt responses into a webpage called Sparkpages that allows users to ask followup questions.

The company also offers a number of specialized search features. One capability is geared towards browsing e-commerce websites’ product listings. Another tool, Genspark Finance, visualizes data from earnings reports in graphs to ease analysis. 

One of the latest additions to the search engine’s feature set is a capability called Deep Research. It provides more detailed answers to user queries at the cost of increased wait times: Genspark says that a prompt response can take up to 30 minutes to generate. According to the company, the feature spends that time analyzing more than one million words’ worth of information from over one 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 and then combines them into a single answer.

Today’s report didn’t specify how the company 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.

According to a Feb. 10 blog post, the company’s search engine relies on GPT-4o, Claude 3.5 Sonnet and Gemini 2.0 Flash to answer queries. Those are midrange LLMs that balance output quality with hardware efficiency. Adding a more hardware-intensive, reasoning-optimized model such as OpenAI’s o1 to the list could potentially help Genspark enhance its search engine’s output. 

The company’s funding round comes a few weeks after Perplexity AI Inc., a competing AI search startup, closed a $500 million investment of its own. The deal reportedly valued the company at $9 million. Last week, Perplexity launched a feature similar to Genspark’s Deep Research that can generate multipage prompt responses in response to user queries. 

Image: Genspark