Using Agentic AI to Automate Complex Capital Project Workflows

Artificial intelligence has dominated business conversations in recent years, including in the architecture, construction, and engineering (AEC) industry. Most people have interacted with AI in a simple, linear way: we ask a question, AI gives an answer, and that's it. But AI capabilities are already evolving beyond simple information retrieval, summarization, and content generation to tackle the more robust processes that take away teams’ time.

The next step for organizations looking to harness AI is the automation of complex workflows using agentic AI: AI that goes beyond simple tasks to execute entire processes with minimal human involvement. Agentic AI is designed to be goal-oriented, creating a plan and executing a series of tasks without needing a human to constantly guide it.

In this article, we'll explain how agentic AI works, what it means for capital project owners, and how organizations can set themselves up to use AI successfully.

How AI agents work

Unlike basic AI chatbots, which simply predict the appropriate response to an individual prompt, AI agents are goal-oriented programs that are capable of reasoning about the best way to achieve their goal and then executing multiple related tasks to get there.

Goal-oriented planning

This begins with planning. Using the underlying LLM as its "brain," the agent is able to look at the goal provided by the user or another agent within the context of all the information available, and then generate a multi-step plan to achieve that goal. For example, if the agent's goal is to verify that a project has all the required certificates of insurance (COIs), it might autonomously create a plan that looks like this:

1. Find every contract that includes insurance requirements
2. Parse the requirements from the contract
3. Parse all project and contract documents for COIs
4. Extract policy limits and dates from the COIs
5. Check each policy limit against the contractual requirements
6. Validate that each policy is still active
7. Update the "COI" dashboard in Gryps with this information
8. Notify relevant parties as a policy approaches expiration

Specialized sub-agents

Complex workflows often require different "skills" to complete different tasks. In order to execute these different tasks, agentic systems often use sub-agents. These are smaller, specialized models trained to accurately execute a specific type of action.

For example, in a document processing workflow you might have one agent responsible for classifying documents, another agent responsible for extracting data from those documents, and yet another for checking that extracted data against some external standard. A central orchestrating agent coordinates these different sub-agents to ensure the workflow proceeds logically.

Reflection and self-learning

One of the most powerful features of agentic AI is its ability to "reflect" on its own work by comparing the output to the initial goal and determining if it needs to change its process. This continuous learning process allows agents to both improve their own accuracy over time and adapt to the unpredictability inherent in complex, real-world situations.

At Gryps, we use "trainer” models to drive this continuous improvement. These are AI agents that are specifically built to evaluate the work of other agents and identify ways they can become more accurate.

Human-in-the-loop validation

Despite the increasing accuracy and effectiveness of AI agents, many organizations will still want their results validated by a human employee. Many of our agents are designed to include human verification as part of their process, presenting results to a member of your team for final approval. This allows you to accelerate processes and automate tedious work without sacrificing control of the outcome.

Case study: Automating invoice reviews

To illustrate how agentic AI works, let’s look at a specific process that creates a major time drain for capital program owners: invoice review.

Reviewing contractor invoices is a complex, time-consuming task for capital program owners. Invoices can span hundreds of pages, containing documents as varied as schedule of values, payrolls, material receipts, lien waivers and timesheets. Manually checking for each document and verifying its accuracy is tedious and prone to human error, creating the risk of overpayment or even regulatory noncompliance.

Gryps' Invoice Review Agent uses agentic AI to automate the entire review process. It connects directly to your existing systems, retrieves relevant files, and verifies both completeness and accuracy in minutes:

• Document and Data Ingestion: The agent automatically connects to your Project Management Information System (PMIS) and document management systems and retrieves the records, folder and files containing the contractor's submission. Typically the record is a combination of structured and unstructured data.
• Intelligent Classification: The agent identifies and tags distinct document types within the larger packet. It can also verify that all of the necessary document types are included, based on a predetermined list for each contract type.
• Data Extraction: The agent extracts and labels critical financial and project information, turning it into structured data for validation by the agent. This structured data is also available for reporting, use in additional workflows, and transfer into your financial systems.
• Data Validation: The agent validates key information for both completeness (ensuring the required information is included in the documents) and accuracy. Accuracy checks can include tasks such as ensuring contract IDs match your existing records, verifying that subcontractor names align with approved lists, and checking FEINs against company records.
• Calculation Audits: Beyond text matching, the agent can also perform mathematical checks such as verifying line-item totals and checking contractor markups against agreed-upon rates.

By handling the data extraction and validation, the agent is able to flag documentation gaps or rate inconsistencies almost instantly, turning a task that used to take hours into one that takes minutes, and freeing up teams to focus on more impactful work.

Effective AI depends on good data

Like all AI applications, agentic AI is only as good as the data it's using. According to a recent study by Wing Venture Capital, 49% of large enterprises say data is the most important challenge to AI at their companies. If you have incomplete, siloed, or messy data, your AI is likely to produce inaccurate or unhelpful results.

Gryps gives you the data foundation you need to leverage AI effectively. We do this in several ways:

• Connecting your tech stack: Gryps uses both APIs and digital agents to connect to over 30 of the platforms that owners and contractors rely on, bringing together project, financial, scheduling, and other data in one place.
• Unifying structured and unstructured data: We don't just pull in structured data. Gryps also ingests your documents and uses AI to automatically classify them and extract important information, bringing together both structured and unstructured data from across your various systems.
• Building a comprehensive knowledge graph: Knowledge graphs use a graph-based structure used to identify the relationships between different pieces of information, providing the "semantic context" that AI applications need to properly understand your data. Gryps creates a single, construction-specific knowledge graph with all your information, providing the ideal foundation for your AI tools.
• Leveraging retrieval-augmented generation (RAG): We leverage RAG protocols to reduce the risk of AI agents hallucinating. This instructs the model to retrieve specific information from your knowledge graph before generating content, helping the model base its output on your ground-truth data.

Building toward an AI-powered future

The shift from reactive content generation to proactive agents represents an important step forward in the maturity of enterprise AI. Gryps is committed to unlocking the value of agentic AI for our customers, both through specific agents like our Invoice Review Agent and through our Agent Builder tool.

Are you an owner, owner representative, or construction manager ready to leverage AI and make the most of your data? Request a demo of the Gryps platform here.