PlanRadar has launched AI Agents across its construction, facility management and real estate platform, giving project teams automated tools for tasks such as searching documents, drafting responses to requests for information and advancing workflow steps. The agents, available on all PlanRadar plans, are designed to act automatically once triggered inside the platform rather than waiting for manual approval.
The launch taps into growing interest in practical AI applications across the built environment, particularly in markets like Singapore where authorities have highlighted document review, workflow automation and automated site reporting as priority use cases.
How the agents work
Customers can build their own agents using natural language prompts or choose pre-built versions. One example is a response agent that reads an incoming request for information, searches project documents and prepares a reply that identifies the source material - cutting the time to a first response from hours to minutes. Every action an agent takes is logged and attributed, and customers can test agents before deploying them on live work.
Each agent operates within the access rights of the person who created it, limiting what it can see or do to that user's permissions. The agents also run inside PlanRadar's existing ISO-certified security and data protection framework, with no change to how project data is stored or processed.
General contractors, specialist contractors and project managers tend to manage large numbers of issues and inspections, making them likely early users of tools that automate follow-up work.
Ibrahim Imam, Group Co-Chief Executive Officer at PlanRadar, said the product is intended to reduce the amount of routine administration carried out by project teams.
"Our customers want the routine work on a project to take care of itself, without giving up any control over what happens, and that is exactly what PlanRadar AI Agents deliver. Our agents catch what could otherwise slip through and turn into rework, so project teams can focus on the judgment calls only people can make," Imam said.
Built into existing workflows
PlanRadar's approach differs from standalone AI tools that require users to switch between systems. The agents are built into its existing software, which already includes document management, reporting and integrations.
Clemens Hammerl, Chief Product Officer at PlanRadar, said customers wanted more work completed within the same system rather than through a separate interface.
"We do not want another system to log into or another workspace to manage. Customers want more of their jobs completed to be in one single system. PlanRadar AI Agents run on existing project data, with each agent checked against its creator's own access every time it runs. Building an AI Agent is like briefing a new teammate, easy to describe in your own words, and ready to act every time you need it, with real autonomy matched with real control," Hammerl said.
For teams still figuring out where to start, PlanRadar's Forward-Deployed Engineers work directly with customers to identify automation use cases and get initial agents into production.
The shift from documentation and reporting to automated action reflects a broader trend in AI for Real Estate & Construction. PlanRadar says more than 200,000 professionals in over 75 markets use the platform. The company is headquartered in Vienna and operates from 13 offices worldwide.
Why this matters for real estate and construction professionals
The practical takeaway for project teams is that AI agents are no longer a future concept - they are now embedded in tools that already handle site data, documentation and workflows. The ability to automate RFI responses and routine follow-ups directly addresses the time drain of manual coordination, and the permission-based design means teams can test automation without handing over decision-making authority.
As these tools develop, the professionals who will benefit most are those who can identify the repetitive tasks in their own workflows and brief an agent to handle them. That starts with understanding how AI Agents & Automation work in practice - not just what they promise.
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