How B2B Companies Are Using AI Inside Custom Web Applications

AI is no longer a futuristic concept or a buzzword reserved for marketing teams. It’s becoming a core component of how B2B companies streamline operations, improve decision-making, and scale internal processes. And increasingly, that transformation is happening inside custom web applications, not in third-party platforms or consumer-facing tools.

From document automation to predictive analytics, B2B organizations are embedding AI directly into their workflows by building custom apps tailored to their business. These aren’t off-the-shelf solutions. They’re purpose-built systems designed to integrate with internal data, support specific use cases, and deliver real operational value.

In this article, we’ll explore how B2B companies are applying AI in their own .NET-based web applications and how Marcel Digital helps make these innovations a reality.

What’s Driving AI Adoption in B2B Web Development

B2B environments are complex. Teams often manage long sales cycles, heavy documentation, multiple internal tools, and layers of decision-makers. Efficiency isn’t a nice-to-have - it’s essential.

AI has the power to streamline repetitive tasks, surface actionable insights, and remove friction across internal operations. But to unlock that potential, it needs to be implemented thoughtfully, within tools that reflect how your business actually runs.

Custom .NET web applications are uniquely well-suited for this. They offer the flexibility to integrate with legacy systems, tailor workflows to specific roles, and scale as business needs evolve. By embedding AI directly into these systems, B2B teams can make data-driven decisions, automate manual work, and optimize performance, all without leaving their internal platforms.

Automating Document Processing with AI

If your teams are still manually entering data from invoices, contracts, or technical documents, you’re leaving time and accuracy on the table.

With AI-powered document processing, businesses can use natural language processing (NLP) and optical character recognition (OCR) to extract structured data from unstructured documents. This enables web applications to:

• Auto-populate fields in CRMs, ERPs, or compliance systems
• Flag discrepancies between documents and system entries
• Standardize formats across suppliers or vendors

For example, Marcel Digital is currently leading the web development for the American College of Surgeons (ACS), where we're integrating AI directly into their custom Umbraco CMS implementation. One standout feature allows ACS staff to upload PDFs into the media library, where AI automatically generates a summary to populate the description field used in internal search. This not only saves time for content managers but also improves search accuracy and content discoverability for end users.

Building Intelligent Workflow Automation

AI doesn't just make existing workflows faster, it makes them smarter. Inside a custom web application, AI can detect patterns, anticipate needs, and trigger actions automatically.

Let’s say a support platform receives a high volume of inquiries. AI can:

• Analyze sentiment to prioritize responses
• Auto-assign tickets based on issue type or urgency
• Flag repeat requests for escalation or process review

This type of intelligence can be built directly into a .NET-based workflow system, enabling real-time routing and decisioning. By automating routine steps, businesses reduce bottlenecks and empower teams to focus on exceptions, not every task.

Enhancing Decision-Making with AI Insights

Dashboards are only as useful as the insights they provide. AI helps transform raw data into clear, actionable recommendations - right inside the tools your team already uses.

For example, a logistics company might use an internal application that applies AI to identify the most cost-effective shipping routes based on real-time variables like fuel prices, inventory levels, and weather forecasts. That recommendation appears directly in the planner’s interface, allowing for faster, smarter decisions without toggling between systems.

This kind of AI-assisted decision support helps teams:

• Respond faster to changing conditions
• Avoid unnecessary costs or delays
• Make consistent, data-backed choices

Powering Predictive Reporting and Forecasting

Traditional reporting tells you what already happened. AI-powered reporting shows you what’s likely to happen next.

By embedding machine learning models into custom applications, B2B companies can forecast trends, allocate resources more efficiently, and get ahead of risk. Common examples include:

• Sales forecasts based on deal velocity and seasonality
• Inventory planning based on historical usage patterns
• Maintenance alerts triggered by sensor or usage data

When these insights are delivered through a custom .NET interface built for your workflows, they become part of everyday planning, not a separate analytics project.

Why Custom .NET Applications Are Built for This

Off-the-shelf solutions often struggle to accommodate B2B complexity. With custom .NET development, businesses gain full control over features, access, data integration, and performance.

Key advantages include:

• Seamless integration with internal tools like CRMs, ERPs, and document systems
• Role-based access and user permission models across departments or partners
• Scalable architecture that can evolve with your business and your AI models
• Security and compliance tailored to your industry’s requirements

In short, a custom .NET application doesn’t just support AI. It gives you a secure, flexible foundation to grow with AI.