AI-powered CRE underwriting: Watch Smart Capital Center’s live demo video  

Artificial intelligence is transforming commercial real estate (CRE) by speeding up underwriting, improving accuracy, and delivering real-time insights. To show exactly how this works in practice, Smart Capital Center hosted a 48-minute live underwriting demonstration using La Jolla Village Square, a retail property in San Diego, California.

Watch the full video above to see how Smart Capital Center automates financial analysis, reconciles rent rolls, surfaces tenant risks, and equips investment teams with deep research and AI copilots.

For commercial real estate investors and asset managers, this session demonstrates how AI is reshaping underwriting, portfolio monitoring, and tenant analytics across the CRE lifecycle.  

The session was hosted by Amanda Hiebert (Vice President, Marketing) and featured Garrett Brewer (Director of Sales) and Hannah Kidd (Senior Financial Associate). Together they demonstrated how Smart Capital Center brings speed, precision, and proactive intelligence to underwriting and portfolio management.

For those who prefer to read or follow along, below is the entire transcript of the webinar, lightly edited for clarity and readability.  

Welcome to Smart Capital’s live CRE underwriting webinar

Hiebert gave a brief welcome and introduction to the live demonstration of AI-powered CRE underwriting and shared the agenda for the discussion.  

Hiebert:
Hello everyone and good morning or good afternoon depending on where you’re joining us from. Welcome to Smart Capital’s live CRE AI underwriting demonstration. We’ll give it just another minute or so for people to log in and then we’ll dive right in.

Hiebert:
Thank you all so much for joining us today for this live demonstration of what AI can do in the process of underwriting in commercial real estate. My name is Amanda and I lead the marketing team here at Smart Capital Center. I’ll quickly walk you through what to expect in today’s session.

Hiebert:
We’ll start with introductions and then we’ll give a quick overview of Smart Capital Center as the first AI-powered commercial real estate platform. We’ll cover some use cases across the investment lifecycle, with a focus on underwriting. Then we’ll go into a live underwriting demonstration so you can see exactly what this looks like. At the end we’ll have time for questions. If we don’t get through them all we’ll follow up with answers in a takeaway summary after the session.

Hiebert:
I’m pleased to introduce Garrett Brewer, our Director of Sales, and Hannah Kidd, our Senior Financial Associate. Garrett as deep experience in investment underwriting and CRE technology. Hannah works closely with investors to modernize workflows using our platform.

Overview of the Smart Capital Center platform

Brewer explains how Smart Capital Center is purpose-built for CRE, covering the full lifecycle from acquisitions to portfolio monitoring with AI co-pilots.

Brewer:
Thank you, Amanda, and thank you everyone for joining us. My background is in commercial real estate, having spent time in brokerage and in technology with firms like Argus Enterprise and Reonomy. What excites me most about Smart Capital Center is how we use AI to ingest financial documents, extract data, and serve as a co-pilot in the underwriting process.

Brewer:
With real-time data, AI-powered underwriting, and unmatched market intelligence, Smart Capital Center helps teams make smarter, faster decisions, manage risk 24/7, and automate workflows across the entire investment lifecycle.

Brewer:
Our platform is built specifically for commercial real estate. Every feature is designed for CRE workflows and documents, whether you’re analyzing office, retail, multifamily, or specialized assets.

Brewer:
It covers the full lifecycle—acquisition, underwriting, portfolio monitoring, debt management, risk analysis, and disposition. We work with clients such as JLL, RMR Group, Tremont, and KeyBank who are already using the platform for speed, accuracy, and results.

Brewer:
With generative AI we can extract data from structured and unstructured documents—PDFs, scanned files, Excel spreadsheets, appraisals, rent rolls, OMs, leases, and loan agreements. The data is always transparent and traceable back to its source.

Brewer:
Analysts can generate financial analyses and pro formas in minutes instead of hours. To give an example, Fernando Salazar, Director of Asset Management at JLL, said that processing a financial statement used to take 30 to 40 minutes, and now it takes only 1 to 3 minutes with Smart Capital Center.

Key features: AI co-pilots, Deep Research, and Smarty

Kidd introduces core features like automated analysis, document review, and Smarty—the AI analyst that delivers instant, context-aware insights.

Kidd:
Once the data is extracted the platform automatically generates charts, graphs, and property-level analytics. Analysts can create standardized reports in their existing formats with just one click. AI can also review documents, flag anomalies, generate SWOT analyses, and surface tenant research insights.

Kidd:
One of the most exciting parts of the platform is Smarty, our built-in AI analyst. Smarty has full knowledge of your portfolio and properties. It can instantly answer questions using financials, appraisals, inspections, loan agreements, and market data.

Kidd:
Instead of data sitting idle in folders, it becomes dynamic and actionable. Smarty can evaluate deals, perform financial analysis, and deliver analyst-grade insight at scale.

Live demonstration: Underwriting La Jolla Village Square

Smart Capital Center’s team walks through a retail property case study, showing how the platform processes documents, reconciles rent rolls, and generates market intelligence in real-time.

Brewer:
For today’s demo we’re going to walk through La Jolla Village Square, a retail property in San Diego. We’ll start by uploading rent rolls and T12s. The system will automatically extract the data, reconcile it, and standardize it for analysis.

Brewer:
Here on the property page you can see market data including ownership, tax history, surrounding businesses, amenities, foot traffic, and demographics. Analysts can also view population density, business statistics, and top employers. We integrate with third-party market data providers as well, so you get a full picture of the asset.

Brewer:
Generative AI can build SWOT analyses and risk assessments based on the uploaded documents and external data. Analysts can customize these outputs to reflect their own methodology and train the system as they would a junior analyst.

Kidd:
Variance reporting is one of my favorite features. The system highlights financial changes across time periods and explains what’s driving them. For example, it might show that utilities rose seasonally or that tax expenses increased in a particular quarter.

Kidd:
The rent roll reconciliation is also powerful. It automatically flags anomalies like a vacant unit showing rent, or an expired lease that’s still marked active. These are things analysts often have to check manually, but the system can surface them instantly.

Kidd:
Tenant analytics go even deeper. You can see detailed profiles of tenants, their industry classifications, credit exposure, and even news alerts or sentiment analysis. If there’s negative news affecting a tenant, the system notifies analysts and asset managers right away so they can act.

AI powered 24/7 monitoring and financial analysis

This section highlights how Smart Capital Center automates DCFs, projections, comps, and variance analysis, while enabling ongoing tenant and portfolio monitoring.

Brewer:
The system also generates projections and discounted cash flows automatically, but it gives analysts full flexibility to adjust assumptions just as they would in Excel. You can change renewal probabilities, reimbursement structures, and other variables, and every change is fully transparent and traceable.

Brewer:
Smarty can also help streamline this by applying bulk assumptions—for example, renewal probabilities across all anchor tenants—or by answering queries such as what typical expense ratios look like in this submarket.

Brewer:
Another capability is with sales comps. Data from appraisals and OMs can be extracted, standardized, and mapped into a reusable comps database. Analysts can then compare scenarios, run sizing calculations, and evaluate metrics like IRR, cash-on-cash, and equity multiples.

Kidd:
We also see clients using the system heavily for tenant monitoring. The AI continuously scans for tenant credit events, industry shifts, or regulatory changes. If, for example, a major retailer declares bankruptcy, the system will flag all properties in your portfolio that could be impacted.

Kidd:
That makes it possible for asset managers to move from being reactive to proactive. Instead of waiting for issues to show up in financial statements, you can respond to market signals as they happen.

Questions and answers: AI and Deep Research in CRE underwriting

Brewer and Kidd address questions about integration with Excel and Argus, maintaining firms’ unique underwriting approaches, and ensuring data security.

Brewer:
Let’s take a closer look at how this works with La Jolla Village Square. After uploading the documents, you can see that the system reconciles the rent roll with the financials. Any discrepancies, such as missing units or mismatched lease terms, are flagged for review.

Brewer:
On the financial side, variance reporting shows period-over-period changes. For example, if payroll expenses increased by 10 percent, the system will note that and highlight potential reasons—like staffing changes or seasonal adjustments.

Kidd:
Another key feature is the ability to benchmark assumptions against market data. If you’re modeling a DCF and assuming a certain expense growth rate or renewal probability, the system checks that against comparable properties in the same submarket.

Kidd:
This gives analysts more confidence in their underwriting because they’re not relying on static or outdated assumptions. They can see how their inputs stack up against real-time market intelligence.

Brewer:
It also ties into scenario analysis. You can run sensitivities across variables like occupancy, rent growth, or cap rates, and instantly see the effect on NOI, DSCR, and IRR. That level of flexibility used to take hours of spreadsheet work, and now it happens in seconds.

Kidd:
One of the things our clients appreciate is that the platform doesn’t replace their existing models—it complements them. If you have Excel models or Argus workflows that you rely on, Smart Capital integrates with those seamlessly.

Kidd:
That means you can export the data back into your templates, preserving your firm’s unique methodology and “secret sauce,” while still saving significant time on data ingestion and reconciliation.

Brewer:
Exactly. We hear from clients that this balance is key. They want the efficiency and automation that AI delivers, but they also want to maintain control over their underwriting process. With Smart Capital, you get both.

Brewer:
Another area worth highlighting is security. We work with regulated entities such as banks, insurance companies, and government agencies, so data protection is foundational. The platform is SOC 2 Type 2 compliant, with strict controls and audits in place.

Brewer:
Clients also decide which AI models to use—whether that’s private LLMs, third-party providers, or our internal AI. Nothing you upload ever leaks into public training data, so you maintain full ownership and control.

Kidd:
Another point that comes up often is transparency. Every data point in the system is linked back to its original source document. If you’re looking at an expense number, you can click and immediately see the exact line in the financial statement it came from.

Kidd:
That gives analysts confidence because they don’t have to wonder where numbers are coming from. It also helps when you’re presenting to an investment committee or an external stakeholder—you can always back up your analysis with source documentation.

Brewer:
And beyond transparency, it’s about scalability. Teams can process more deals in parallel without adding headcount. What used to take days now takes minutes, which means firms can look at a broader pipeline and move faster on opportunities.

Brewer:
We’ve seen firms that used to underwrite maybe three or four deals a week now able to evaluate ten or more with the same team. That’s a huge competitive advantage in a market where speed often determines whether you win or lose a deal.

Kidd:
It also frees up analysts to focus on higher-value work. Instead of spending hours cleaning data, they can spend their time interpreting results, refining assumptions, and making strategic recommendations.

Brewer:
Let’s go back to La Jolla Village Square for a moment. On the market intelligence side, the platform brings in property history, foot traffic, demographics, and business statistics. You can layer all of this into a single view of the asset.

Brewer:
That helps when you’re assessing tenant performance or planning leasing strategies. For example, you can see how population density or income levels in the trade area have changed, and how that might impact demand.

Kidd:
And the tenant analytics add another dimension. You’re not just looking at the rent roll, you’re looking at real-time monitoring of tenant health. That includes financial exposure, industry conditions, credit ratings, and even online sentiment.

Kidd:
If negative news comes out about a tenant, the system notifies the analyst immediately. That way you can act before it shows up in the financials or before the tenant defaults on rent.

Brewer:
This is what we mean by moving from reactive to proactive workflows. Instead of waiting for problems to happen, you’re getting signals early enough to mitigate risk and protect NOI.

Kidd:
Another key area is financial variance analysis. The AI compares performance period over period and explains the differences. Instead of just showing that expenses went up, it will highlight the likely drivers—things like a tax reassessment, seasonal utilities, or maintenance timing.

Kidd:
That saves analysts from having to dig through line items manually and piece together the story themselves. It’s a big time-saver, but it also improves the quality of reporting because the analysis is consistent and thorough.

Brewer:
And again, everything can be exported back into Excel or other systems. That means you can generate automated variance reports but still package them in the format your firm or your stakeholders are used to.

Brewer:
It’s also useful for ongoing asset management. Surveillance analysts can set up continuous monitoring, so the system automatically flags anomalies or changes each month. That way, instead of doing manual quarterly reviews, you have AI agents working for you 24/7.

Kidd:
Exactly. It really is like having a team of junior analysts working around the clock. They don’t replace people, but they extend your capacity so your human analysts can focus on judgment and strategy.

Brewer:
We also want to highlight the role of Smarty in this process. Smarty isn’t just a chatbot—it’s an AI analyst that understands your portfolio. You can ask it direct questions like, “What are the top three tenants by exposure across this deal?” or “Run a SWOT analysis for this property,” and it will instantly deliver answers.

Brewer:
Because Smarty has access to both your internal documents and external market data, the insights are comprehensive. It can combine financials, rent rolls, appraisals, news articles, and benchmarks into a single response.

Kidd:
I’ve seen teams use Smarty during investment committee meetings. Instead of saying, “We’ll need to pull that data and get back to you,” they can just ask Smarty in real-time and get the answer on the spot. That changes the dynamic of those meetings completely.

Kidd:
It’s also interactive. If you want to adjust assumptions or run a new projection, you can do that right within the conversation. Smarty will recalculate and show you the updated outputs immediately.

Brewer:
That kind of flexibility makes underwriting and asset management much more dynamic. Instead of static reports, you have a living system that can answer questions and adapt as conditions change.

Kidd:
We should also talk about scalability. With AI agents and analysts working in the background, you essentially have a limitless workforce. Some of our clients describe it as having 100 analysts working 24/7.

Kidd:
That doesn’t mean replacing people—it means your existing team can focus on higher-value work. The repetitive, manual tasks are handled automatically, while your analysts apply their expertise to strategy and decision-making.

Brewer:
And the measurable results are clear. JLL saw processing times for financial statements shrink from 30–40 minutes to 1–3 minutes. KeyBank reported a 40 percent reduction in the time it takes to prepare financial models for loans.

Brewer:
Those productivity gains translate directly into more deals reviewed, faster execution, and better portfolio performance. It’s not just about saving time—it’s about unlocking capacity and enabling growth.

Kidd:
It also means more consistent analysis. When you have AI generating variance reports or benchmarking assumptions, the methodology is applied uniformly across the portfolio. That reduces errors and ensures comparability.

Brewer:
Another strength of the platform is deep research on assumptions. Traditional DCF models rely on static inputs for things like rent growth, renewal probabilities, and expense ratios. With Smart Capital, every one of those assumptions can be benchmarked against real-time market data.

Brewer:
For example, if you assume a 3 percent expense growth rate, the system will check that against comparable properties in the local market and show whether your assumption is aggressive, conservative, or in line with peers.

Kidd:
That’s a huge shift because it gives analysts confidence that their underwriting is grounded in evidence. Instead of guessing or relying on outdated comps, you have dynamic, data-backed assumptions.

Kidd:
It also helps uncover hidden risks or opportunities. You might see that your renewal assumptions are higher than market averages, or that your expense growth assumptions are too low. Catching those things early can make a big difference in valuation and decision-making.

Brewer:
Exactly. It’s about moving from a “best guess” approach to one that is fully supported by real-time intelligence. That level of precision just hasn’t been possible with manual processes.

Kidd:
We also want to touch on reporting. The platform automates the production of investor-ready reports—things like asset summary reports, portfolio reviews, and investment memos.

Kidd:
Instead of analysts spending hours pulling data and formatting spreadsheets, the system generates clean, compliant reports in minutes. And because everything is linked back to source documents, the outputs are fully auditable.

Brewer:
That’s important for firms that have to meet regulatory requirements or internal governance standards. You can demonstrate not just what the numbers are, but where they came from and how they were calculated.

Brewer:
It also eliminates version control issues. Everyone on the team is working from the same set of data, updated in real-time. No more chasing down the latest spreadsheet or reconciling conflicting files.

Kidd:
And when you integrate this with portfolio monitoring, you get a live view of performance. Analysts can drill into individual properties, run stress tests, and see the impact of changes in rents, vacancies, or cap rates immediately.

Brewer:
Another big advantage is early warning signals. The system can flag things like occupancy drops, NOI trends, tenant delinquencies, expiring leases, or unusual expense spikes.

Brewer:
It can also surface correlations between market dynamics and asset performance—for example, how a local economic shift might impact demand for space in a particular property.

Kidd:
That proactive flagging is critical. Instead of finding out about a problem months later, you’re getting alerts in real-time so you can take action before it impacts returns.

Kidd:
And you can run portfolio-wide scenario modeling. If interest rates change or market conditions shift, the system can simulate how that would affect your entire portfolio. That kind of stress testing used to take weeks, and now it happens instantly.

Brewer:
This is really about giving asset managers and surveillance teams the tools they need to manage risk continuously, not just during quarterly reviews. It’s continuous portfolio intelligence.

Kidd:
To wrap up, it’s worth repeating that Smart Capital is built exclusively for commercial real estate. Every feature—from underwriting automation to tenant monitoring to financial analysis—is tailored to the needs of CRE investors, lenders, and asset managers.

Kidd:
The system doesn’t replace human judgment; it enhances it. Analysts and managers keep full control, preserve their own methodologies, and maintain their “secret sauce” while offloading the repetitive manual work.

Brewer:
And everything is secure. The platform is SOC 2 Type 2 compliant, we work with regulated entities, and we give clients full control over how AI models are applied. Nothing leaves your environment or goes into public training data.

Key takeaways

The speakers summarize measurable results, client successes, and the unique advantages of CRE-specific AI co-pilots.

• AI co-pilots save analysts hours by automating data extraction and reconciliation.

• Tenant and market monitoring enables proactive risk management.

• Smarty provides on-demand answers and projections, enhancing decision-making in real-time.

• Clients like JLL and KeyBank have reported 30x faster financial processing and 40% less time to prepare models.

• All insights remain transparent, customizable, and exportable to Excel or Argus.

Connect for your personalized live underwriting demo

Brewer and Hiebert close the session with a recap of how Smart Capital Center empowers CRE professionals to move faster, manage risk proactively, and scale with confidence.

Brewer:
The future of underwriting is real-time deep research. AI in CRE isn’t a someday story—it’s here today. From ingestion to risk monitoring, Smart Capital Center empowers teams to act decisively and outperform at scale.

Hiebert:
Thank you all so much for joining us for this live underwriting demonstration. If you’d like to see how Smart Capital Center can support your firm specifically, please reach out to us for a personalized demo.