Iron Software Sees 200% Increase in Agentic AI Adoption for HTML to PDF C# Workflows with IronPDF

A decade of building reliable document processing tools—including the industry-leading IronPDF library for HTML to PDF C# conversion—positions Iron Software at the center of the enterprise AI execution layer

CHICAGO, Feb. 5, 2026 /PRNewswire/ -- Iron Software, a leading provider of .NET document processing libraries and creator of IronPDF, today highlighted its strategic position in the rapidly emerging agentic AI landscape. Major consulting firms' 2026 technology reports confirm what Iron Software has been building toward for a decade: AI agents need reliable, enterprise-grade tools to do real work—and document processing is where that work begins.

Deloitte's Tech Trends 2026 report, published December 10, 2025, identifies agentic AI as one of five interconnected forces reshaping enterprise technology, yet cautions that "only 11% have successfully deployed these systems in production." The report finds that "processes designed for human workers don't work for agents" and calls for enterprises to rebuild rather than merely enhance their foundations.

PwC's 2026 AI Business Predictions report reinforces this shift from experimentation to execution, warning that "crowdsourcing AI efforts can create impressive adoption numbers, but it seldom produces meaningful business outcomes." PwC urges enterprises to "go narrow and deep" on high-value workflows, identifying document-heavy functions like finance, HR, tax, and internal audit as prime candidates for agentic transformation.

The Gap Between Intelligence and Execution

AI agents can reason, plan, and make decisions—but they cannot generate a contract, parse a scanned invoice, or produce a client report without the right tools. Iron Software's product suite, anchored by IronPDF, provides the execution layer that bridges this gap.

IronPDF enables developers to convert HTML to PDF in C# with a single method call—a capability now in high demand as AI agents automate document generation workflows across enterprise environments. When an agent determines that a financial report needs to be created or a customer-facing proposal needs to be rendered, it is libraries like IronPDF that perform the actual work. The broader Iron Software suite—including IronOCR, IronXL, and IronBarcode—extends this execution layer across the full spectrum of enterprise document tasks.

"AI agents are only as capable as the tools they can call upon," said Jacob Mellor, CTO of Iron Software. "Consider a common enterprise workflow: an AI agent needs to pull data from a spreadsheet, generate an HTML report, and convert HTML to PDF in C# for distribution. That agent needs IronXL to read the data and IronPDF to render the final document—reliably, every single time, at scale. When Deloitte reports that enterprises are struggling to move AI from pilots to production, a significant part of that challenge is infrastructure. We've spent ten years building exactly that."

A Decade of Building for This Moment

Iron Software celebrates its 10th anniversary at a moment that validates its founding thesis. Since 2015, the company has grown from a single PDF library into a comprehensive suite of .NET document processing tools used by thousands of enterprise customers worldwide.

Deloitte predicts that by 2028, 33% of enterprise software applications will include agentic AI, compared to less than 1% in 2024. Separately, Deloitte forecasts that as many as 75% of companies may invest in agentic AI by the end of 2026. PwC identifies functions like "finance, HR, IT, tax, and internal audit" as areas especially ripe for agent deployment—all functions that routinely involve the kind of document creation, extraction, and processing that IronPDF and the broader Iron Software suite are built to handle.

"Ten years ago, we made a bet that developers would always need high-quality libraries for document processing," said Cameron Rimington, CEO of Iron Software. "We didn't predict the AI revolution. But we did predict that enterprises would always need to create PDFs, extract text from images, and manipulate spreadsheets. Now AI agents need to do all of those same things. PwC's report makes clear that 'technology delivers only about 20% of an initiative's value.' The other 80% comes from redesigning work around tools that actually perform. That's what we've spent a decade perfecting."

On the Ground: How Enterprises Are Already Building

The reports' findings align with what enterprise technology leaders are already experiencing. Glenn Le Marchant, Head of Technology Strategy at PKF Australia and founder of QWERTY Software Solutions, recently built an automated document processing solution by orchestrating Iron Software libraries alongside traditional code—and found that senior stakeholders assumed it was powered by AI.

"Companies are trying to use large language models to replace human intelligence and automate business processes, but that is the wrong approach," said Le Marchant, who spent 18 years at Commonwealth Bank in senior technology roles before joining PKF. "AI is best used as one tool within a toolkit to re-engineer processes and automate them. Chaining together tools such as IronPDF, IronOCR, AI, and traditional code like API calls and rules engines, allows businesses to streamline and automate processes and orchestrate information across systems."

Le Marchant's experience illustrates a key theme from both reports: the most effective enterprise automation doesn't come from AI alone—it comes from intelligent orchestration of the right tools. As AI agents increasingly enter these workflows, they will depend on the same proven libraries that are already delivering results today.

.NET Developers: More Essential Than Ever

Iron Software saw the convergence of AI and .NET development firsthand at .NET Conf 2025, the annual Microsoft developer conference held November 11–13, 2025, which Iron Software sponsored again this year. The event's agenda was heavily focused on AI, featuring keynote sessions on agentic development, the Model Context Protocol (MCP), AI-powered development with GitHub Copilot, and building intelligent applications with .NET—a clear signal that the .NET ecosystem is positioning itself at the center of the enterprise AI buildout.

"The rise of agentic AI doesn't diminish the role of .NET developers—it elevates it," said Cameron Rimington, CEO of Iron Software. ".NET developers are still essential. They're the ones building, integrating, and overseeing the systems that AI agents operate within. What's changing is that with the right tools—like IronPDF and our broader suite—those developers can now move quicker and achieve more than ever before. A workflow that once took a team days to build and test can now be orchestrated in hours. The developer isn't being replaced. They're being supercharged."

Enterprise-Ready Means AI-Ready

IronPDF and the Iron Software suite are already integrated into tens of thousands of production environments across financial services, healthcare, legal, and government. The libraries support .NET 10, run across Windows, Linux, macOS, and containerized environments including Docker and Azure, and are designed with the programmatic accessibility that agentic architectures demand. For developers building AI-powered workflows, the path from HTML to PDF in C# through IronPDF is already a well-documented, production-proven capability—not an experiment.

"The AI industry is learning what enterprise software developers have always known," said Jacob Mellor, CTO of Iron Software. "Processing a PDF correctly every single time, handling edge cases in OCR, maintaining backwards compatibility across framework versions—these aren't glamorous problems. But they are exactly the problems AI agents will encounter the moment they start doing real work. Deloitte notes that 'the infrastructure built for cloud-first strategies can't handle AI economics.' We agree. That's why we've always built our tools for the demands of production, not the convenience of demos."

Looking Ahead

As the agentic AI market matures throughout 2026, Iron Software plans to continue investing in developer experience, cross-platform reliability, and seamless integration with AI-driven workflows. The company's roadmap includes enhancements to IronPDF and the broader suite designed to optimize performance in automated, high-throughput environments where AI agents orchestrate complex document pipelines.

About Iron Software

Iron Software, headquartered in Chicago develops professional-grade .NET libraries for document processing. Celebrating its 10th anniversary in 2025, the company's product suite includes IronPDF, IronOCR, IronXL, IronBarcode, IronWord, IronZIP, and other tools trusted by enterprise developers globally. IronPDF is the leading library for HTML to PDF in C# and .NET applications. Learn more at ironsoftware.com.

Source: Deloitte Tech Trends 2026 | Source: PwC 2026 AI Business Predictions

** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **

Iron Software Sees 200% Increase in Agentic AI Adoption for HTML to PDF C# Workflows with IronPDF

From RPO and Romomo to PartyOS, RoboParty is building an open humanoid robotics foundation for developers worldwide.

PITTSBURGH, Oct. 4, 2026 /PRNewswire/ -- On September 28, 2026, RoboParty publicly unveiled RP1 (ROBOTO 01) at IROS 2026, marking the robot's global debut.

In January 2026, RoboParty fully open-sourced RPO (ROBOTO ORIGIN), its first open-source humanoid robotics project. To date, RPO has received more than 2,500 GitHub stars. As a developer-oriented open-source humanoid robot, RPO has attracted broad attention worldwide and inspired multiple community builds and reproductions.

Building on this foundation, RoboParty positions RP1 as the world's first high-performance full-stack open-source bipedal humanoid robot. RP1 is designed for researchers, educators, robotics developers and embodied AI teams, with the goal of providing a humanoid robotics system that can be used, modified, trained and continuously extended in real development workflows.

Kick Me: Putting Dynamic Stability to the Test

At RoboParty's IROS booth, the "Kick Me" interactive demonstration was one of the most direct ways for visitors to experience RP1's capabilities.

During the demonstration, visitors could directly apply external disturbances to the robot. When pushed or kicked, RP1 rapidly adjusted its posture and recovered its balance. Unlike demonstrations based only on predefined motions, this open interaction allowed visitors to observe the robot's dynamic stability and control performance under external disturbances.

The repeated high-intensity interactions also provided a direct test of the robot's body performance and system-level robustness.

RP1's dynamic motion and disturbance-recovery capabilities at IROS were supported by PartyOS, RoboParty's open R&D foundation for humanoid robotics, which integrates the UFO framework.

UFO — short for "A General Unsupervised Reinforcement Learning Framework for Humanoid Control" — is a training framework for discovering humanoid motor skills through unsupervised reinforcement learning. It trains low-level motion policies that allow robots to learn dynamic behaviors without relying entirely on conventional predefined motion trajectories, including skill transitions, disturbance recovery and fall recovery.

Rather than treating motion control as an isolated algorithmic module, RoboParty is integrating the robot body, actuator modules, low-level control and embodied AI algorithms into one system for continuous joint validation. The goal is to ensure that algorithmic capabilities are built on a stable and reproducible humanoid robotics platform.

The IROS demonstration marked an important validation milestone for this technical direction.

Throughout the exhibition, researchers, university faculty and students, robotics developers and industry professionals from different countries and regions visited RoboParty's booth. Discussions extended beyond motion performance to RP1's robot body, Romomo actuator modules, motion control, modular design and future open-source plans.

Multiple research teams and developers also discussed the procurement of robots and core components, algorithm reproduction, embodied AI research and open-source collaboration with the RoboParty team.

From Closed Systems to Full-Stack Open Source

With RP1, RoboParty is exploring an alternative path for humanoid robotics.

Today, high-performance humanoid robots are typically delivered as complete products or closed systems. Researchers and developers may be able to use or observe these robots, but the underlying hardware, motion-control systems, simulation environments and software stacks are often difficult to inspect, modify, reproduce or extend.

RP1 is designed to redefine how humanoid robots are developed — from a developer's perspective.

For RoboParty, "full-stack open source" does not mean releasing only mechanical files or a single software module. In addition to the robot body and core actuator modules, RoboParty plans to progressively open its motion-control systems, simulation environments, SDKs, training tools and PartyOS development foundation.

This will allow developers to participate more deeply in humanoid robotics development, from hardware and low-level control to model training and deployment.

"Humanoid robots should not be closed systems that only a small number of teams can build while everyone else can do little more than watch," said Yi Huang, founder of RoboParty. "We want RP1 to become an open foundation that developers can access, modify, train and continuously improve. Full-stack open source has been our technical direction since the RPO project."

RoboParty plans to announce further details of RP1's open-source roadmap in October 2026, with broader software and hardware releases and a mass-production program to follow later in Q4.

RP1: A High-Performance Open-Source Body for Embodied AI

RP1 is designed to provide a high-performance humanoid platform for dynamic motion, embodied AI model training, validation and deployment, data collection and continuous development.

RP1 delivers peak joint torque of up to 160 N•m. From its in-house-developed Romomo actuator modules and mechanical structure to its real-time motion-control system, RP1 is designed around the requirements of dynamic motion, disturbance recovery and long-term development experiments.

These capabilities were demonstrated live at IROS. During the "Kick Me" interaction, visitors directly applied external disturbances while RP1 adjusted its posture and regained its balance. The robot also demonstrated continuous motion, disturbance recovery and fall recovery. These behaviors reflected not only algorithmic performance but also the coordination of the robot body, actuator modules and motion-control system.

RP1 builds on RoboParty's broader full-stack open-source roadmap.

RoboParty began with RPO, its fully open-source bipedal humanoid robotics project. Through the development and community adoption of RPO, RoboParty expanded its technical capabilities to cover core actuators, robot bodies, motion control, dexterous manipulation and robotics software systems.

RoboParty subsequently introduced the Romomo actuator modules and its dexterous RP Hand while continuing to build PartyOS.

RPO validated an open-source bipedal robot body, motion-control system and developer workflow. Romomo expanded the technical foundation to cover core actuator modules. RP Hand extended the stack into dexterous manipulation and human-robot interaction. RP1 now brings these capabilities together into a humanoid robotics system designed for research and development.

Based on these capabilities, PartyOS is evolving across humanoid locomotion, perceptual interaction, whole-body manipulation and autonomous intelligent humanoids.

By bringing the robot body, actuators, motion control, perception, manipulation and intelligent software into one coordinated development system, RoboParty is building a full-stack open-source humanoid robotics platform from low-level hardware to high-level intelligence.

Building a Global Developer Community

RoboParty's team spans robot hardware, motion control, artificial intelligence, systems software and manufacturing engineering. Core team members studied at Tsinghua University's Yao Class, Peking University's Zhi Class, Harbin Institute of Technology, Stanford University, Carnegie Mellon University, Zhejiang University and other leading institutions.

RoboParty has already built a global community of more than 5,000 developers across research, education and maker communities.

As RP1 becomes progressively more open, RoboParty aims to further develop this community into an open ecosystem spanning robot hardware, algorithms, data and applications, enabling more researchers, model-development teams and developers to participate in building and advancing humanoid robotics.

Media Contact: marketing@roboparty.com 

GitHub: https://github.com/Roboparty/roboto_origin

Website: https://roboparty.com/

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RoboParty Unveils RP1, a High-Performance Full-Stack Open-Source Humanoid Robot at IROS