-- Aloha, the company behind the privacy-focused Aloha Browser, which has served more than 300 million users, has launched AlohaJet, a browser designed for AI agents to complete complex tasks across websites and web-based applications.
AlohaJet makes web automation faster and less resource-intensive, helping individual users handle everyday web tasks and businesses automate large-scale workflows more efficiently.
Task-specific AI agents are expected to be embedded in 40% of enterprise applications by the end of 2026. As adoption grows, so does the cost of running them. More than 40% of agentic AI projects are expected to be canceled by the end of 2027, with escalating costs, unclear business value and inadequate risk controls among the main reasons. One reason is how resource-intensive AI agents can be. Agentic tasks can consume roughly 1,000 times more tokens than conventional AI interactions, and web tasks add to that workload because AI may need to reassess the page as it moves from one step to the next.
AlohaJet addresses this through LLMdex, a technology that helps AI find the information and actions it needs on a webpage. Instead of making AI repeatedly interpret raw page data or screenshots, LLMdex directs it to the relevant parts of the page and identifies what it needs to do next. When multiple models are connected, LLMdex can route routine steps to smaller, lower-cost models and more complex ones to more powerful models. For recurring workflows, AlohaJet can reuse what it has already learned about the process instead of depending on fixed instructions that can become outdated when a website changes. This helps tasks keep running as layouts or designs change, which is a common reliability challenge for web agents.
The impact becomes more significant when the same tasks are repeated at scale. Completing six common web tasks, including search, form filling, data extraction and multi-page navigation, can require up to 94,000 tokens, depending on the automation approach used. With frontier models costing up to $30 per million output tokens, that processing directly affects the cost of running web automation. In AlohaJet’s benchmark, the same workload used 54% fewer tokens and ran 2.2x faster, with an 88% task success rate versus 51% using standard Chrome automation and 11% using Playwright, a widely used browser automation framework.
“A few dollars for one automated task is easy to dismiss. Run that same task 10,000 times and suddenly you have a very real infrastructure bill,” said Andrew Frost, Founder of Aloha. “We ran into this problem ourselves at Aloha. Too much model capacity was being spent just figuring out what was on the page instead of completing the work. AlohaJet came out of trying to strip away that waste and make web automation faster, cheaper and more efficient at scale.”
Users can connect a single AI model or several models of their choice, including frontier, open-source or self-hosted models. For an individual user, that could mean asking AlohaJet to search multiple websites for a specific item, compare options and find sellers that deliver to their location. For enterprise use, AlohaJet can also be deployed inside a company’s own infrastructure, giving businesses control over where their workflows and data are processed. When configured entirely within the customer’s environment, browser sessions, credentials and prompts can remain inside the company’s network.
The pressure is already visible in enterprise AI budgets. 93% of organizations have already exceeded them, while spending rose nearly fourfold as AI expanded from isolated use cases to enterprise-wide adoption. AlohaJet is designed to make web-based AI workflows more efficient to scale, whether they are run by individual users or across large business operations.
Contact Info:
Name: Dasha Plishko
Email: Send Email
Organization: Aloha
Website: https://alohajet.com/
Release ID: 89204059
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