Real Estate Professionals: What Tools Do You Wish Existed?

Question

Hi, how are you? My name is Pedro.

I’m currently building an AI platform for the real estate market called Calder.

The goal is not just another tool, but an intelligence layer for real estate professionals — combining property data, market signals, financial analysis, and contract workflows into one system to help investors, agents, and operators make faster and more confident decisions.

We’re specifically exploring things like:

• identifying high-probability deals before they become obvious
• structuring and analyzing deals from a financial perspective
• simplifying contract review and decision-making
• reducing the amount of manual analysis and fragmented tools people rely on today

Right now, I’m still refining the product direction and trying to deeply understand where the biggest inefficiencies actually are in the real workflow.

Since you work in real estate, your perspective would be extremely valuable.

From your experience, where do you currently spend the most time analyzing, organizing, or validating information before making a decision on a deal?

I’d really appreciate any insights — it would help a lot in shaping what we’re building.

Thank you!

Ryan Stomel · Answer

Coming at this from the commercial side — NNN and modified gross leases, retail and industrial in Southern California — and the inefficiency I spend the most time on is CAM reconciliation and operating expense tracking. Every tool I looked at was built for residential or for large institutional operators. Nothing in the middle handled the mechanics of pro-rata allocations, CAM caps, base year calculations, or gross-up provisions without a ton of manual spreadsheet work on top.

For your platform, the biggest pain points I see for commercial operators specifically are: (1) tracking which expenses are recoverable under each lease and at what cap, (2) reconciling estimated monthly payments against actual annual expenses across multiple tenants who all have slightly different lease language, and (3) tying all of it cleanly to QuickBooks so the accounting actually matches what went out the door. That last piece is where most tools fall apart completely.

I ended up building something to solve exactly this problem (pigjet.com) after nothing off the shelf handled NNN properly. Happy to share what the real friction points looked like if it's useful for your product direction.