agchouston.org Winter 2025–2026 Cornerstone 15 construction project intelligence, these platforms use artificial intelligence to track early indicators of development long before traditional systems pick them up. Mercator.ai, designed specifically for private-sector construction markets like Texas, has emerged as one of the most widely adopted examples. This guide explains how project intelligence works, why contractors are investing in it, and what firms across Texas and beyond have learned after adopting it. What Project Intelligence Means in Practice Project intelligence is the structured use of external market data to identify, qualify and pursue construction oppor- tunities earlier in their lifecycle. Traditional lead services show projects already in the public domain: announced bids, issued RFPs and formal plan sets. AI shifts the focus upstream to early indicators such as: ] Land and site acquisitions ] Title transfers ] Rezoning and planning submissions ] Environmental or utilities filings ] Early-stage permit activity ] Repeat behavior by known developers or architects The value isn’t in any single record, but in the pattern created when many small signals connect. Mercator.ai, for instance, tracks tens of thousands of active and emerging projects across Texas by collecting these signals and using AI to link related events into cohesive proj- ect profiles. This gives contractors visibility into credible opportunities months before they appear on a bid board — precisely when owners and developers are still forming project direction and are most open to establishing new relationships. External vs. Internal Intelligence Project intelligence is often confused with internal analytics tools, but they solve different problems. ] Internal project intelligence tracks performance after work is won. It mea- sures budget, productivity, schedule and profitability to help firms manage risk and protect margins. ] External project intelligence, which Mercator.ai provides, focuses on iden- tifying, evaluating and pursuing new opportunities. It scans the broader market to show which owners, devel- opers and architects are active; where development is forming; and which opportunities align with a contractor’s strategy. One protects the work you have; the other improves the work you pursue. How Mercator.ai Structures External Signals The core question behind Mercator.ai is simple but difficult to answer: What’s happening across tens of thousands of properties, developers and jurisdictions that indicates a project is forming? Texas illustrates the challenge. The market is large, fragmented and driven heavily by private development. Every city and county handles planning differently, and the earliest signals are scattered across hundreds of jurisdictions. There is no centralized system. Even well-staffed BD teams cannot manually track this reliably. Mercator.ai addresses that by: 1. Collecting records at scale: Zon- ing items, land transfers, planning documents, ownership records and early-stage permit activity. 2. Linking entities: Connecting devel- opers, architects, engineers and own- ers across filings, so activity is visible even when jurisdictions differ. 3. Clustering signals into projects: Identifying when multiple data points reflect a single development. 4. Filtering for relevance: Matching opportunities to each contractor’s market, sector, size and capabilities. The output is a structured, continu- ously updated view of the construction pipeline — information BD teams can use daily without sifting through raw records. How Contractors Use Earlier Intelligence Firms using project intelligence often make three practical adjustments to their business development process. 1. Systematic Early Outreach Instead of waiting for late-stage announcements, BD teams start con- versations earlier, when owners and developers are still evaluating needs. Contractors report that these early engagements lead to: ] Deeper understanding of scope ] Influence over delivery method ] Better alignment with owners ] Stronger negotiation positions The competitive dynamic shifts from “submit numbers against other bidders” to “help shape the project and become the logical partner.” 2. Mapping Relationships to Real Activity Many firms have networks far larger than they use. Project intelligence reveals when known developers or architects begin new work, prompting timely outreach. One Dallas contractor said that before adopting upstream intelligence, “We were pursuing opportunities blind. Now we can see when people we already know start moving on something.” 3. Improving Preconstruction Readiness With earlier visibility, preconstruction teams can begin internal analyses The power isn’t in any single record, but in the pattern created when many small signals connect.
