# New AlohaJet browser wants to make agents cheaper > Source: > Published: 2026-09-22 10:00:00+00:00 Agents are performing a growing number of tasks for users and one company is making web browsing a lot easier for them. Aloha, the company behind the privacy-focused Aloha Browser, on Tuesday introduced AlohaJet, a browser designed to allow AI agents to perform complex tasks across the web faster and cheaper. The company said the browser's agent also allows for enterprises to better scale and automate web-based workflows more efficiently. The company claims that the AlohaJet browser cuts token use by 54% and completes tasks 2.2 times faster, while maintaining a task success rate of 88%. Comparatively, agents using Chrome have a task success rate of 51%, according to Aloha. - AlohaJet relies on a technology called LLMdex, which assists AI in finding necessary information and actions on a web page. This helps mitigate one of the biggest factors that eat up tokens: agents needing to assess and reassess entire web pages as they move through tasks. - Along with picking out the relevant pieces of information on a web page, when using multiple models, LLMdex will route the routine steps to lightweight, lower cost models. Users can connect one or multiple models of their choice. - Additionally, AlohaJet will reuse information it's learned in repetitive workflows to optimize and adapt to processes when websites change. Thus, AlohaJet is tackling one of the most pressing challenges that AI agents present: cost efficiency. Though agents are forecasted to be embedded in 40% of AI applications by the end of this year, [according to Gartner](https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2026), these agents eat up a significant amount of tokens, which can get expensive very fast if you use the latest models like Anthropic's Fable 6.1 and OpenAI's GPT-6 Astra. It's a problem that Aloha faced itself, said Andrew Frost, founder of the company, in a statement. A good deal of model capacity was spent by agents simply figuring out what was on a web page. AlohaJet was a result of the company "trying to strip away the waste," he said. "A few dollars for one automated task is easy to dismiss," said Frost. "Run that same task 10,000 times and suddenly you have a very real infrastructure bill." In testing AlohaJet, The Deep View's Editor-in-Chief Jason Hiner said that the browser is simple, fast and effective, allowing him to easily search the publication's website for articles relating to a specific topic and automatically coming up with the idea to create a CSV file for him to export and organize the list. While AlohaJet lacks in-depth bookmarking and organizational tools, it's a promising option as a browser focused on running your agentic tasks. ## Our Deeper *View* It's no secret that enterprises are looking to trim expensive token bills. As a result, a number of alternatives have started to catch the attention of the industry, such as open-source and small, task-specific language models. However, some of these new innovations aren't straightforward innovations, with AlohaJet being an example with its agent-first browser. Another is [Jev, a model released by an OpenAI alum](https://www.thedeepview.com/articles/jev-puts-frontier-ai-price-premium-under-pressure) that's built to interact with other software, rather than chatting with humans, and is orders of magnitude cheaper and faster to run, which has already been adopted by companies like [Vercel, Cloudflare and LangChain](https://www.forbes.com/sites/josipamajic/2026/09/19/jev-cuts-ai-decision-costs-100x-and-vercel-cloudflare-rushed-to-add-it/). These innovations signal that, while enterprises are hungry to use AI, they're actively looking for solutions that allow them not to reduce token use.