The idea behind Agentic AI is that many small, task-focused agents can cooperate to finish real work; however, this particular idea has felt more like a promise than a product. Fortunately, the Paris-based H Company wants to change that, announcing 3 major steps forward in bringing our vision of Agentic AI to life, starting with putting their flagship runner on the start line.
Runner H by the is now in public beta, inviting anyone to fire off a single prompt and watch a cascade of sub-agents fill spreadsheets, scrape sites, ping Slack, or even settle an invoice while you scan the results.
The Runner H release comes alongside two more announcements: open-sourcing the visual model that guides Runner H’s browser cousin, Surfer H, and launching a private-beta test platform called Tester H. Together, these three announcements sketch a practical roadmap for bringing multi-agent systems into day-to-day engineering.
What is Runner H?
According to the H Company, Runner H is a state-of-the-art AI agent that lets anyone automate complex, cumbersome, multi-step tasks without repetitive and manual input.
In simple words, Runner H is a coordinator for your digital workload:
You provide a high-level goal, and the internal orchestration system breaks that down. This system intelligently assigns tasks to specialized sub-agents, including their Browse agent, Surfer H, and other connected applications. This allows Runner H to:
- Extract live data, compile it into a spreadsheet, and share that with your teammates via Slack.
- Search for relevant job openings online and proceed with the application process.
- Update your Customer Relationship Management (CRM) system with new lead information and draft custom follow-up emails for that lead.
Runner H’s design answers the two frustrations developers mention most with large language models (LLMs): Fragmented context and weak execution.
Instead of returning a paragraph of advice, Runner H allocates tasks to mini-agents that can plan, call APIs, click through the UI, and keep track of what happened last time. H Company calls the approach “memory + orchestration + execution.” In practice, that means tasks that used to bounce between a shell script, Zapier, and a human checker can live in one chat thread.
Runner H integrates memory, task orchestration, execution capabilities, and deep connections with other software into a single interface.
Here are the key capabilities:
- Agent Orchestration: Users can initiate complete workflows using one prompt. Runner H then coordinates different AI agents to plan and carry out the necessary steps in a synchronized manner.
- App Integration: It connects with popular tools like Slack, Notion, Google Sheets, and various APIs, allowing it to operate directly within your existing software setup for immediate automation.
- Knowledge Uploads: Users can provide PDFs, documents, and data files. Runner H processes this information, turning it into accessible context to inform its actions and generate more accurate results.
- Autonomous Payments (Coming Soon): H Company plans to allow Runner H agents to make purchases from platforms like Amazon and Shopify or subscribe to software services, all without direct human intervention.
According to H Company, Runner H is designed to redefine interaction with AI by creating a more intuitive and potent way to manage digital tasks.
How to use Runner H:
Step 1: Visit the Runner H on the H Company’s website and click on Try Now.
Step 2: Sign up to get started. Enter your prompt and submit.
- Prompt: Visit marktechpost.com and give me summarize of the 3 latest AI research news articles.
Step 3: Runner H will take a few minutes to complete the task, depending on the task’s complexity. You can see and track everything from start to end.
Holo-1: Open weights for visual navigation
Automating the browser means seeing the browser. To make that reliable and cheaper, H Company has released , a family of 3-billion- and 7-billion-parameter action vision-language models.
Paired with , Holo-1 scores 92.2% on the WebVoyager benchmark for UI localization while staying small enough to run on a single GPU. Both the weights and a 1,639-scenario dataset are now live on , giving academics and startups fresh material for training agents that can read and click.
Tester H: Closing the QA gap
If AI cranks out code in seconds, quality assurance cannot rely on weekly manual test plans. Tester H, now in private beta for enterprises, turns plain-English user stories into executable end-to-end tests. ‘
Agents would step through the interface like a real customer and start clicking buttons, opening modals, checking text and layout, and reporting any deviation.
Early tests say they have cut regression cycles while raising confidence in each push. Requests to join the beta are open on H Company’s .
Conclusion
H Company’s recent announcements, particularly the launch of Runner H into public beta, is the first wide-open playground that points to a future where AI agents play a more active role in both personal and professional productivity. Adding an open-source visual model like Holo-1 and a testing agent like Tester H contributes a valuable resource to the broader AI community, aiming directly at DevOps pain points.
H Company is betting that 2025 will be the year agents stop being a demo and start being part of the toolchain. For now, the introduction of more sophisticated agentic AI capabilities is an interesting development to watch in the growing tech story.
