Preconstruction

We’ve all heard it: Trust the process. 

Much of our work with our construction clients involves process development and implementation around every facet of their business. The benefits of using well-documented and thoroughly trained processes are hard to overstate. 

Not only do uniformly adopted processes consistently lead to positive results, there's also a significant increase in the velocity of new hire productivity. When a new hire is handed a comprehensive playbook for their role, trained on that playbook and the company follows up to make sure people use the playbook, new hires succeed quickly. 

Another plus is that when everyone knows the process and follows it, veteran employees are freed up to focus on growth. That’s exciting stuff.

Avoid rigidity

That said, don't make the mistake of completely swapping out a culture of individual decision-making and situational flexibility with one of rigidity and compliance. When the situation calls for it, deviations from the process aren't just acceptable. They are necessary and preferred.

For example, we often implement a structured go/no-go criterion with our construction clients to help decide which projects they should invest their extremely valuable and limited preconstruction resources on. 

This process, which must be completely customized to their unique companies and regularly reviewed and updated to reflect current and future business conditions, helps contractors spend time on the healthiest opportunities available. 

The process also saves time by skipping projects that don't fit and using that time for more comprehensive preconstruction efforts on target projects. The result is almost always higher capture rates on project pursuits and better margins at the time of sale. 

Once this process is in place, it should be used consistently to provide a dispassionate, objective scorecard for the project you are invited to pursue. The scorecard is there to help companies make decisions. 

Notice that I did not say the process makes the decision for them.

It should be up to the judgment of the smart, experienced people in the business to determine whether they will pursue a given project. Therefore, when the scorecard says that a project is a poor fit, that negative against taking the job should be considered an extremely valid data point in a go/no-go decision. However, I still encourage companies to make what they believe is the right judgment for their company on each project regardless of the scorecard output.

Imagine a situation in which a project failed to meet go status based on the scorecard, but this project was the first opportunity to pursue a project with a high-value client. The project is slightly too small to be considered a target job, the competitive circumstances are less than ideal and the project is not in the preferred geographic footprint. 

When the theoretical CEO of this company calls me to ask if he should follow the process or listen to his judgment to bid the job, I respond by saying it sounds like you have compelling strategic reasons to deviate from your process on this one… go for it!

Strategy over process

In other words, strategy outweighs process every single time.

Deviations from your established processes have value. Whether you have strategic business reasons for a deviation, or you merely wish to experiment with another approach, there's absolutely nothing wrong with knowingly deviating from the process. 

But “knowingly” is the key term here. It’s essential that leadership knows the why behind the deviation as well as acknowledgment of any risks associated with not following the standard. When deviations go well, we often make new discoveries that allow us to improve our processes. However, if a deviation produces a negative result, instead of casting blame, it can be a powerful lesson that reinforces the importance of following our processes. 

It’s a leader’s job to walk the line between strategy and process, between rigidity and being opportunistic. 

Please document, train and actively supervise effective processes in every facet of your business for all the reasons listed above and more. Just don't allow your processes to create a rigidity that gets in the way of sound judgment, creativity and intuition in executive decision-making.

Artificial intelligence has dominated the construction technology conversation in recent years. Amid that push, solutions that use AI for scheduling, permitting and preconstruction appealed to investors as 2025 drew to a close.

Here are six contech firms that pulled in fresh funding in Q4 of 2025.

PermitFlow

$54 million

New York City-based PermitFlow, a contech firm that aims to streamline the permitting process via artificial intelligence, has raised $54 million in a Series B funding round, according to a Dec. 2 news release. The round was led by Accel, with participation from Kleiner Perkins, Felicis and other existing investors.

Founded in 2021, PermitFlow says it has a proprietary set of more than 12 million permitting data points that it uses to feed AI agents to streamline automation in the permitting process.

Additionally, the firm provides a submission agent that helps contractors complete forms and file documents directly, per its website.

With the new funding, PermitFlow plans to expand its team, per the announcement.

Attentive.AI

$30.5 million

Wilmington, Delaware-based Attentive.AI, the company behind takeoff software firm Beam AI, raised $30.5 million in a Series B funding round, according to a Nov. 12 news release. The round was led by global software investor Insight Partners, with participation from Vertex Ventures, Tenacity Ventures and InfoEdge Venture Fund.

Beam AI has helped over 1,100 firms streamline the preconstruction process with its human-in-the-loop model, per the release. Users can upload their site plans, define the scope of the work and submit. Then, AI takes quantities of the plans and the QA team at Beam reviews the takeoff before it reaches the builder, per the company’s website. 

With the funds, Attentive will accelerate the development of next-generation AI products and support the expansion into new markets, according to the release.

Unlimited Industries

$12 million

San Francisco-based Unlimited Industries, which calls itself an AI-native construction company, raised a $12 million Seed funding round, according to a Dec. 3 news release. The round was co-led by Andreessen Horowitz and CIV.

Unlimited Industries’ proprietary platform can generate and evaluate hundreds of thousands of design configurations in parallel, per the release. In addition, the platform is designed to identify optimal layouts for metrics such as cost, safety and performance prior to construction. 

The company plans to use the cash to accelerate its expansion and further develop its proprietary AI platform, per the announcement.

ConCntric

$10 million

Greenbrae, California-based ConCntric, an AI-powered preconstruction platform, pulled $10 million in a Series A funding round, according to an Oct. 7 announcement. The round was led by 53 Stations with participation from Argonautic Ventures and other strategic investors.

ConCntric’s platform brings data, workflows and people into a single collaborative environment, allowing users to manage preconstruction in one workspace. Users can keep track of in-progress work using real-time data and move that information across projects, according to the company’s website.

With the money, ConCntric will expand its product capabilities with a focus on its agentic AI, called Amplify. The company also plans to grow its customer success, sales, marketing, product and engineering teams.

Kojo

$10 million

San Francisco-based Kojo, a materials and inventory management platform for the construction industry, received a $10 million Series C extension from Pittsburgh-based distribution and logistics services firm Wesco International, according to an Oct. 16 announcement.

As part of the funding, the companies will combine Kojo’s AI products with Wesco’s distribution network, according to the news release. 

The combination will allow customers to eliminate manual data entry and email-based material tracking across all project phases, access real-time material status and avoid schedule delays, the firms said. Customers will also be able to deploy AI agents to assist in all procurement activities, scheduling tasks and distributor follow ups.

Planera

$8 million

Pleasanton, California-based Planera, a scheduling software provider for the construction industry, raised $8 million in additional funding, according to an Oct. 7 announcement from the company. 

The funding comes as Planera, which helps contractors simplify the often complicated scheduling process, offers a new service geared toward data center construction customers. These include Ralph L. Wadsworth Construction, headquartered in Draper, Utah, and Minneapolis-based Ryan Cos., according to the news release. Both firms use Planera to aid in scheduling with large data center projects.

To that end, Planera has established a dedicated service team with deep data center knowledge to support its customers in the segment, the company said in the release. In addition, Planera has developed new AI tools to help identify potential project delays early and find opportunities to speed up customers’ project schedules.

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By ConCntric

The industry’s biggest risks once went unnoticed until mid-construction—today, they’re visible much earlier and can be solved in preconstruction. What used to be viewed as “just” estimating has become the most strategic and influential phase of the entire project lifecycle. As owners demand greater predictability and contractors navigate tighter labor markets, volatile pricing, and accelerating schedules, the preconstruction phase has emerged as the place where clarity is created, risks are mitigated, and project success is shaped long before the first crew mobilizes.

Preconstruction has undergone more change in the last five years than in the previous fifty. Comparing traditional methods to today’s capabilities reveals just how far the discipline has evolved—and what leaders must embrace next.

1. Concept Phase: From Gut Feel to Data-Backed Decision Making

Then:

Conceptual estimating historically relied on broad comparisons to past projects and the experience of whoever happened to be in the room. Early cost models were pulled from old spreadsheets or paper binders, often missing context about scope, design intent, or shifting market conditions. These early opinions—sometimes well-informed, sometimes not—became the foundation for multimillion-dollar decisions.

Now:

Modern tools centralize cost histories, benchmarks, early design inputs, and market data, giving teams a clearer understanding of the cost landscape from day one. Digital estimating environments make scenario modeling and value analysis faster and more transparent.

AI-driven takeoff tools such as Togal.AI further accelerate this work by analyzing drawings, classifying scope, and highlighting cost implications with remarkable speed. Early-phase modeling is no longer a “best guess”—it’s an informed strategic exercise that helps owners understand feasibility and risk before committing capital.

2. Budget & Planning Phase: From Siloed Tasks to Integrated, Predictive Planning

Then:

Budget development was once a disjointed relay race. Estimators worked in one set of spreadsheets, operations teams developed schedules and logistics plans in another, procurement managed subcontractor outreach in yet another. Design changes triggered rounds of manual updates with no guarantee that everyone was working from the same assumptions. By the time a budget reached decision-makers, it was often outdated.

Now:

Preconstruction is increasingly practiced as a unified, collaborative discipline. Teams build budgets, evaluate design updates, assess risks, and plan phasing within connected digital environments that maintain a single source of truth. Instead of chasing versions, teams respond to insights.

AI-enabled forecasting now helps anticipate labor availability, future price increases, design impacts, and potential scope gaps. This elevates budget and planning from a reactive exercise to a strategic one—one that considers the interplay between cost, schedule, procurement timing, and constructability long before the project mobilizes.

This shift toward integrated preconstruction is becoming more common as teams look for ways to connect estimating, planning, design coordination, and procurement into a cohesive workflow. ConCntric exemplifies this unified approach, helping structure early-phase decisions so their cost, schedule, and risk implications are easier to understand. With clearer visibility into tradeoffs and potential pitfalls, teams can align sooner and move projects forward with greater confidence and predictability.

3. Procurement Phase: From Manual Bidding to Strategic Partner Engagement

Then:

Procurement was once dominated by email chains, file attachments, and hours spent normalizing bids that arrived in different formats. Subcontractor outreach relied heavily on personal networks, making coverage inconsistent. With labor shortages and increased project complexity, these inefficiencies often translated into cost uncertainty and schedule exposure.

Now:

Procurement has matured into a more systematic, data-driven process. Digital bid management tools—such as BuildingConnected—standardize scopes, streamline outreach, and reduce the administrative burden on both contractors and subcontractors. As a result, teams gain clearer comparisons and better coverage.

But the real transformation is strategic: procurement decisions are now informed by historical performance data, market conditions, design evolution, and risk thresholds. Instead of simply chasing the lowest number, teams can evaluate which partners are most likely to deliver predictably and collaboratively.

The Future: AI-Supported Preconstruction as a Competitive Differentiator

The next leap in preconstruction will not come merely from digitizing tasks, but from connecting them—transforming independent activities into a unified, intelligence-driven ecosystem. As AI matures, it will detect risks earlier, model cost and schedule scenarios instantly, and reveal insights that enhance—not replace—professional expertise.

Those who continue treating preconstruction as a collection of disconnected workflows will struggle to keep pace with rising complexity, shrinking margins, and accelerating delivery models. The leaders of the next decade will be defined by their ability to integrate data, leverage technology, and make better decisions earlier. Preconstruction has evolved—now it’s time for our processes, tools, and mindsets to evolve with it.

The conversation around artificial intelligence in project management is clamorous. A deluge of new tools promises to help individuals draft emails, summarize meetings and analyze data faster. While useful, this focus on personal productivity often obscures a more profound shift. To find the real value, we must look beyond the immediate tools and toward the emerging systems that will change how we govern project delivery.

Deepening AI integration

For most project professionals today, AI shows up as personal augmentation. This is the immediate impact of tools such as Microsoft Copilot, which allows us to use generative AI to draft a project charter or analytical AI to create a quick cost forecast. The outcome is personal efficiency. These tools make individuals faster, but they do not fundamentally change a team’s underlying processes.

Widespread adoption of these tools is essential to build literacy, but it is merely the foundation for the next, more powerful application of AI: a shift from personal efficiency to systemic intelligence. Systemic intelligence embeds AI into the governance of a project, program or portfolio. Instead of simply accelerating individual tasks, the system delivers intelligent signals that enable decision makers to act promptly and with confidence. The key distinction is this: does the AI merely provide data for later analysis or does it help project managers with decision making in real time? 

Focusing on what matters most

Implementing systemic intelligence requires us to move beyond the traditional dashboard. While dashboards visualize data for human interpretation (“look what happened”), systemic intelligence actively uses data to prioritize attention (“decide on this now”).

Consider a complex capital project where the supply chain is integrated into a systemic model. An AI agent, analyzing logistics data and weather, might detect a probable 72-hour delay for a critical steel delivery. In the traditional model, this might surface later during a status update. In a systemic intelligence model, the system compares this signal against an agreed tolerance. Because the delay exceeds that threshold, it automatically opens a time-bound decision window for the procurement manager. The choice presented is clear and accountable: approve expedited shipping for a 15% cost increase or formally accept the schedule slip.

In such a case, the system did not just provide data, it forced a timely, auditable decision. This intelligence is typically triggered by signals falling into specific categories, such as cost forecasts, clash detection anomalies or contractual obligations. Each signal is a machine-generated insight that, by crossing a pre-set line, demands human judgment.

For experienced project managers, this approach codifies the intuition they have used for decades. We often apply implicit tolerances to our projects, knowing intuitively which delays matter and which are noise. Systemic intelligence makes these tolerances explicit. This systematic filtering frees human attention from chasing minor past variances and focuses effectively on the moments when a forecast error signals a genuine need for intervention.

The operational impact: moving from reporting to deciding

When systemic intelligence is in place, the rhythm of management changes. The weekly status ritual, in which teams spend hours narrating what happened last week, transforms into a forum for decision-making. Time traditionally spent on narration is reclaimed, and sessions become focused on clearing the specific decision windows that the system has opened.

Ideally, the system analyzes the cost, schedule and resource impacts of a delay, presenting the project manager with the top three mitigation options. The human role is elevated from problem-finding to using tactical judgment to make the final call. This clarity reduces the need for escalation and enables a true “eyes on, hands off” leadership approach.

Common pitfalls: why AI initiatives stall

When do these initiatives fail? A common pattern is “pilot theater.” This occurs when a project team runs an impressive AI pilot that generates signals, but those signals are not connected to any formal decision point, so nothing actually changes, and enthusiasm drains away. Another barrier is the black box problem. When stakes are high, a leader will rightly refuse to act on a warning if the system’s reasoning is opaque. Trust is the currency of project delivery. If the AI cannot explain its provenance, specifically which data sources it used and why, it will be ignored.

None of these are purely technology failures. They are gaps in governance, process design or data quality.

Foundation first

Ultimately, the transition to systemic intelligence is not just a software installation. It is a redesign of how we value human judgment. The journey begins not with a massive technology investment, but with a simple question: “What is the most important decision we have to make this week, and what single piece of data would help us make it better?”

However, this intelligence cannot exist in a vacuum. It requires a foundation of truth. If our project data is trapped in disconnected files and digital silos, no amount of AI can save the schedule

For months, construction activity at a major New York semiconductor site moved in fits and starts.

Tech company Micron adjusted long-term timelines in November 2025 for when its first fab would begin operations, pushing the date back by two to three years. But even as those dates shifted, early site work quietly progressed in the background.

Providence, Rhode Island-based builder Gilbane won a preconstruction contract in August 2025 to prepare the ground for the site. The award marked the first phase of development at the White Pine Commerce Park site.

Micron announced it will officially break ground Jan. 16, 2026, on its $100 billion megafab in Onondaga County, New York, according to a Jan. 7, 2026, news release. The company received the greenlight to proceed after obtaining "rigorous environmental review and necessary permit approvals,” per the release.

The company said this project marks the largest private investment in New York state history.

Once complete, the campus, which could feature up to four fabs, will house the most advanced memory manufacturing facility in the world, according to Micron. The $100 billion investment will help the tech company meet the growing demands of the artificial intelligence boom, the company added.

“Breaking ground at Micron’s New York megafab is a pivotal moment for Micron and the United States,” said Sanjay Mehrotra, chairman, president and CEO of Micron Technology. “As the global economy enters the AI era, leadership in advanced semiconductors will be the cornerstone in innovation and economic prosperity.”

Officials from the Trump administration, Congress and New York state and local government will join Mehrotra during the groundbreaking ceremony on Jan. 16, according to Micron.

For decades, the design-bid-build model has been the backbone of the U.S. construction industry. It has delivered countless successful projects by providing competitive pricing and a clear division of responsibilities between designers and contractors. For many straightforward projects, it remains a reliable and effective choice that deserves credit for shaping much of the built environment we see today.

But the challenges we face now are different from the ones we faced 20 or 30 years ago. Facilities are more complex, labor is tighter, supply chains are unpredictable and extreme weather is a constant concern. These conditions demand a delivery model that emphasizes speed, integration and adaptability. 

That is where design-build stands apart. By bringing designers, engineers and builders together from the beginning, design-build creates a structure where accountability, flexibility and innovation are built into every stage of the process.

Speed and cost certainty

Owners are under pressure to get projects online faster without sacrificing quality. In design-bid-build, each handoff from architect to contractor to subcontractor creates opportunities for delay or misalignment. Design-build eliminates those barriers by uniting the entire team under one contract and one shared set of goals.

The difference is not just about finishing sooner. Early collaboration allows structural systems, layouts and material selections to be evaluated in real time, which often results in measurable cost savings. 

In my experience, the best value decisions are made before a shovel ever hits the ground. Value engineering in a design-build model is not a one-time exercise at the end of design, but a continuous process that runs throughout the project. That constant feedback loop helps protect budgets while improving constructability and long-term performance.

Building for resilience, not completion

In regions where storms, floods or other environmental risks are part of the landscape, resiliency is no longer an added feature. It has become a baseline expectation. Owners want facilities that safeguard investments and recover quickly after disruption.

Design-build gives project teams the ability to plan with that reality in mind. Foundations and structural systems can be phased with weather patterns. Long-lead materials can be ordered earlier to avoid seasonal disruptions. And because the entire team is aligned, schedules can be adapted quickly and efficiently when weather does interrupt progress. I have seen firsthand how early integration helps projects keep moving even in the middle of storm season. 

That kind of resiliency — both in the building itself and in the way it is delivered — has become one of the most important measures of success.

Quality through accountability

Design-bid-build provides owners with valuable checks and balances. Yet the separation of responsibilities can also slow decision-making when unexpected challenges arise. Design-build shifts the mindset from “who is responsible” to “how do we solve this together?”

That collaborative culture is especially important as construction becomes more technology-driven. Many modern facilities rely on advanced equipment, automation and specialized infrastructure. With design-build, engineers, builders and equipment providers are at the same table from the outset. Equipment layouts, clearances, power requirements and structural tolerances can be incorporated into one coordinated model, reducing rework and protecting performance.

The result is greater accountability and a smoother integration of the complex systems that define today’s buildings. Just as important, it creates a working environment where everyone is focused on solutions instead of defending silos.

Going local

Another advantage of design-build is the ability to engage local partners earlier in the process. When subcontractors, engineers and suppliers are included from the start, owners benefit from their regional expertise, whether it is navigating permitting, coordinating utilities or understanding site conditions.

That local engagement pays off twice. It improves the quality and reliability of the finished project and it strengthens the economic impact by keeping more work and jobs in the community. 

For public facilities in particular, this approach demonstrates that the investment is not only in the structure itself, but in the community that surrounds it. As someone who has spent decades working in the same region, I have seen how early involvement of local partners can turn a construction project into a source of pride that lasts far beyond ribbon-cutting.

Looking ahead

Our industry has never stood still, and today’s challenges demand fresh thinking. Owners want more than buildings delivered on time and on budget. They want projects that can adapt, endure and create long-term value.

Design-build provides the framework to do just that. It fosters continuous value engineering, supports resiliency planning, integrates complex technology and strengthens community ties. It is a delivery method that does not just solve today’s problems but anticipates the challenges of tomorrow.

After more than 40 years in this business, I have learned that the most successful projects are the ones that balance innovation with reliability and vision with discipline. Design-build gives us the ability to strike that balance. It is not simply about finishing projects faster. It is about building them smarter and stronger so they stand the test of time.