Just found this cool free AI real estate tool and thought i'd share

Builder disclosure up front: this is my product.

One line of context: every GSE appraisal moves to the UAD 3.6 standard on Nov 2, review goes field-driven, and appraisers suddenly need real support behind every adjustment number.

What CompIQ does, one sentence: upload your MLS export, get regression-supported adjustments plus short per-field comments sized for the new URAR's comment boxes.

The part nobody documents — what the file needs to be:

• The standard closed-sales results-grid export from your MLS. CSV or Excel.
• One hard requirement: a sold/close price column. GLA, beds, baths, year built, lot size, garage, etc. all get used if present, skipped if not.
• Column names don't need cleanup — common header variants are recognized automatically, and anything missed is a two-click manual map.
• Real-world mess is handled: split full/half baths, "Street #" + "Street" split addresses, lot size in acres or SF, features buried in pipe-delimited columns.
• Hard floor is 5 closed sales; more sales, tighter numbers.
• Files parse in your browser. The raw export — agent names, owner fields, remarks — never leaves your machine; only the mapped analysis fields are used.

Free trial, no card: https://compiq.app

If you're an appraiser or build for them: what would this need to fit a real UAD 3.6 workflow?

I run a small company that scores residential parcels for visible physical distress using vision AI on street-level and aerial imagery. I recently finished a study across 27,142 homes in 8 rural counties in Tennessee and Georgia, and several results went against what I expected. I am sharing the ones I think are useful whether or not you ever touch a tool like mine.

First, the scope: This is 8 rural Southeastern counties, not a national sample. "Distress" here means visible physical distress (roof, structure, windows, yard), not financial distress like tax delinquency or foreclosure. A house can look rough with a perfectly content owner who will never sell. These are estimates with real limits. With that said, three findings stood out.

1. "Overgrown yard" is close to worthless as a signal. An overgrown or unkempt yard showed up on about 85% of the homes we scored. When a signal is present on five of every six houses, it does almost nothing to separate a real lead from a normal lived-in property. Seasonality, big rural lots, and plain rural aesthetics all inflate it. The signals that actually discriminate are the rare structural ones: visible structural damage on 10.3% of homes, broken windows on 3.3%, and fire damage on 0.1%. If you are building or buying a distress filter and it leans on yard condition, you are mostly buying noise. Weight the rare structural stuff instead.
2. The biggest finding was a blind spot, not a signal. 27.4% of residential parcels in the study had no usable street-level imagery at all. Either no camera car has driven that road, or not recently enough to matter. That should make anyone relying on street imagery nervous, because the missingness is not random. Across the 7 Georgia counties, street-view coverage correlated negatively with measured distress at r = -0.74. In plain terms, the areas we could see the least were the areas where what we could see was the worst. The rural edges with the thinnest imagery are exactly where distress concentrates. The practical takeaway: any distress rate built only from imagery is a floor, not a full count. We measured roughly 5.0% of scored homes at clear visible distress (3.5 or higher on a 0 to 5 scale), and I believe the true rate is higher, because the worst areas are underrepresented in what a camera has captured. If a vendor quotes you a clean distress percentage and never mentions imagery coverage, ask about coverage first.
3. Age and absentee ownership are real but weak on their own. Older housing predicts distress in a clean, monotonic way. A home built before 1940 was about 1.6 times as likely to show distress as one built since 2000. Absentee ownership moved the odds too: at the "some neglect" threshold, 56.6% of absentee-owned homes crossed it versus 44.9% of owner-occupied. Both are useful filters. Neither is strong enough to stand alone. A shift of about a quarter in the odds is a nudge, not a verdict, and if you treat absentee ownership as a distress proxy by itself you will chase a lot of well-kept rentals.

If there is one thing to take from this, it is that the popular easy signals (overgrown yards, absentee flags) are the weak ones, and the honest hard part is coverage: knowing where you cannot see, and not mistaking an absence of data for an absence of distress.

A few limits worth stating plainly, since I know this crowd will ask. This is 8 rural counties in two states, so do not read national numbers into it. Visible distress is a physical signal, not a motivation signal, so pair it with ownership, tax, or life-event data before you treat any address as a lead. And vision models over-call on ambiguous cases, which is another reason we lean on the rare structural signals rather than soft ones like yards.

Happy to answer questions or run the numbers a different way if people want cuts by county or by threshold. The full write-up with the charts and methodology is here if you want the detail: https://uglyhousefinder.com/distressed-property-research/ . It is not gated, no email required.

I’m curious what everyone’s workflow looks like for staying in touch with leads, past clients, and your sphere.

Specifically:

• What platform(s) are you using if at all?
• Are you sending market snapshots, listing alerts, newsletters, or something else?
• How do you decide who gets what and how often?
• Is it mostly automated, or do you manually create campaigns?
• If you use a CRM, are you sending emails directly through it or integrating with another email marketing platform?

I’m less interested in the content itself and more interested in how people have their email marketing system set up. I’d love to hear what has worked well (and what hasn’t).

A year ago I moved my site- NestingInNashville.com off WordPress after a decade of cycling through IDX plugins. I just pulled my 12-month Search Console: 64,800 clicks, 6.18M impressions on AgentLoft.com

I was at roughly 15 clicks a day before the switch — now it's closer to 150.

The part that surprised me most: a big share of my traffic is people googling specific addresses, and I regularly rank right behind Zillow — for listings that aren't mine. The platform auto-generates and cross-links property-type pages (pool homes in a ZIP, basement homes in a city) with zero setup.

I wrote up the full experience, including what I don't love and how much of the growth is the platform vs. my own weekly publishing. Not affiliated with them in any way — full disclosure on the referral mechanics is in the post. Screenshots included. Happy to answer questions in the comments.

Blog Review: https://nestinginnashville.com/blog/agentloft-review-real-estate-website

For those of you running FB / IG ads, what type of ad are you seeing bring in decent buyers/sellers?

Most real estate “matching” platforms are not really recommendation services.

They are referral businesses.

The basic model is usually:

1. A consumer asks for an agent.
2. The platform sends the lead to a participating agent.
3. The platform receives a referral fee or other compensation if the transaction closes.

There is nothing inherently wrong with that model. But it creates an obvious conflict: the platform is choosing from agents who participate in its commercial system—not necessarily from every agent who may be the best fit for that particular buyer, seller, property type, price range, and market.

A true recommendation service should work differently.

It should start with the customer’s specific job and analyze relevant evidence, such as:

• Transactions in the same micro-market
• Experience with the same property type and price range
• Buyer-side or seller-side activity
• Days on market and price reductions
• Sale-to-list performance compared with the local market
• Expired or withdrawn listings, where the data is available

The recommendation should come first. Any commercial relationship should be disclosed separately.

Do you know of a real estate platform that operates this way—a genuine recommendation engine rather than a compensated referral network?

I recorded a video exploring the difference and demonstrating how transaction data could be used to identify the best agent for a specific job. The link is in the first comment.

I’d genuinely appreciate feedback from people working in real estate technology: Is this distinction meaningful? What would a trustworthy recommendation product need to show?

I've been hearing more and more title abstracting services using AI to automate their searching processes, and some of them don't even have a human look over the final report. I was wondering what everyone's thought was on this, and if you trust the AI with it. I'm interested in doing this myself if people think it's reliable, because it seems like it would be a massive time save for me.

Hi, we are splitting off from a larger team and I am overwhelmed with how to choose a website and tech stack. We are with REAL Broker and will be staying with them.

1. We currently use FUB and would be happy to continue with this, but open to other options.

2. Have looked at Agent Image, it seems very expensive, but also worth it. Also spoke with Sierra, but unsure about moving forward with them bc you don't really own the website like you would with AgentImage.

3. I own the domain I need already but its not active anywhere.

4. Im not the best with tech but I am willing to learn.

5. TC uses A-Frame but not sure that is the best choice for a CRM.

6. Can any agents give me a short list of the tech stack you use?

Thank you in advance for helping me work through this!

If like me you work in commercial real estate acquisitions, site selection, or land development you've looked at hundreds, maybe thousands, of properties over your career. Not physically "looked at" - some are visited on site tours, some are in emailed flyers, some are listings or saved searches on CoStar, LoopNet, Crexi, or whatnot. The point is we "look at" lots of properties. Most of them are passed on, some of them you barely remember. But a few of them are either immediately of interest, or something you want to follow up on at some point in the future.

That is the nature of our business.

The challenge for me is a problem that nobody has solved well: How can I easily save those that I want to follow up on, and how can I quickly share the properties I am interested in with my team?

For me the specific frustrations were four things:

Storing: I needed a single place to save every property I looked at with enough detail to be useful later. Not just an address. Contacts, notes, files, URLs, zoning info, price, broker, owner, APN, coordinates. Everything attached to the property record in one place.

Categorizing: I work on multiple projects simultaneously, often with different tenants or different project types. A single property might be relevant to three different projects and I need a way to assign properties to specific projects or tenants without duplicating property details across multiple spreadsheets. Anyone who has managed acquisition pipelines knows exactly how complicated it becomes trying to coordinate updates across multiple spreadsheets.

Searching: This one matters more than people realize once they've been doing this for a few years. Often times I need to find a property I entered six months or two years ago based on whatever fragment I could remember - owner name, broker, city, zoning, a keyword from my notes, a price range, or any combination of those. The ability to search across hundreds of properties by who, what, when, where, and why is not a nice-to-have, it's the difference between valuable institutional knowledge and a folder full of forgotten spreadsheets.

Mapping: I want the ability to generate a map of all properties owned by a specific company, offered by a specific broker, or relevant to a specific project, depending on what I am searching for, and not have to export the data and import it into a Google map. Properties should display on the map as pins when zoomed out and parcel boundaries when zoomed in without having to create multiple map layers or duplicate data. Occasionally the only thing I can remember about a property is where it is located. Being able to zoom to specific location on the map to find the property is sometimes the only way I can track it down.

To solve these problems I looked at many tools: property ownership apps, project management tools, and CRMs. None of them did the trick. Ownership apps like LandVision or LandGlide are excellent for ownership research but have no easy way to save and share what you find. Project management tools like Asana or DealForce require so much data entry per record that tracking hundreds of properties becomes a part-time job. CRMs like Salesforce are contact-centric when acquisition work is fundamentally property-centric, and the real estate add-ons are expensive, complex, and still fall short on mapping and ease of use.

None of them did what I needed.

So, around 2022 I started building something that did, which became the precursor to Pics & Parcels.

It was built nights and weekends over about a year before it was functional, while I continued to acquire and develop properties during the day. The functionality is there, it works the way I want it to. I have been using it every day since it went ‘online’, updating it and adding features along the way. The UI still needs polish. But the core of the app - storing, categorizing, searching, and mapping properties at volume - works exactly as I need it to.

Just so you understand my background: before real estate I worked in enterprise software development - accounting systems, distribution systems, geographic and GIS-based market analysis applications. For P&P I wrote every line of HTML, CSS, JavaScript, PHP, and SQL in the platform. This is not a vibe-coded weekend project. I even had to update the entire mapping functionality when Microsoft replaced Bing Maps with Azure Maps, ugh. It is an application built by someone who understands both the technical requirements of the software and the daily workflow of the job.

I currently have over 3,000 properties in the app and have used it to source more than 100 development projects since I started using it. The mobile layer - GPS photo capture, automatic sign reading, field capture from your phone - is in development now and will complete the workflow from field to desk in one tool.

One important clarification: P&P is not meant to replace a full project management platform. Once a property moves into active development I use Smartsheet to handle the heavy lifting of contract timelines, due diligence, permits and approvals, engineering drawings, scheduling, and team coordination. That level of detail and workflow complexity is exactly what project management tools are built for. What I needed was the layer that comes before that - tracking and categorizing properties at volume during the site selection and acquisition phase, before a deal is even under contract. That gap is what P&P is meant to fill, and for me it has been doing exactly that.

Let me know if any of the frustrations I described sound familiar to you, Pics & Parcels was built for that.

If you want more information or want to sign up for pre-release early access, visit the link below.

Thanks.

https://picsandparcels.com

#LandAcquisition #SiteSelection #CommercialRealEstate #PropTech #RealEstateTechnology

Hi everyone,

My team and I have been working on a product, and I'd love to get some honest feedback from people in real estate, PropTech, and AI.

One thing we've noticed is that real estate professionals spend a surprising amount of time on operational work—not selling homes.

Managing documents.
Keeping track of deadlines.
Following up with multiple parties.
Organizing transaction data.
Making sure nothing falls through the cracks.

We're building YayTrack to help solve that.

Instead of trying to replace people, our goal is to use AI to handle repetitive operational tasks while keeping humans in control of the final decisions.

Some of the things we're focusing on include:

• AI-assisted transaction workflows
• Intelligent document management
• Deadline and follow-up tracking
• Real-time visibility into transaction progress
• Better collaboration across everyone involved

We're still early in the journey, and we're actively shaping the product.

I'd genuinely love to hear your thoughts:

• What's the biggest operational headache in your real estate workflow?
• If AI could eliminate one repetitive task for you, what would it be?
• What existing transaction management tools do you wish worked better?

We're here to learn as much as we are to build.

Thanks for reading, and I'm looking forward to hearing your perspectives.

Just had a call with them and it all sounds great but I am skeptical. Looking for anyone that has worked with them or still does, did you like it? Why did you leave? Why are you still with them? Did you see a good ROI?

I am working with a local, MA based real estate company. Here we take capital from investors and let the borrowers borrow it for a short period for their needs. We do all kinds of deals, even foreclosures. I need to find leads, people facing foreclosures or anyone looking to sell their homes fast for cash. I want leads specifically in New England (Massachusetts, Rhode Island, Connecticut and new Hampshire).

Can anyone guide me the right tool or strategy to find the leads? Would be a huge favor.

One thing we’ve noticed is that it’s surprisingly common to jump between multiple websites just to verify an address or pull out details like coordinates, postal code, or administrative areas.

We ended up building a simple Reverse Address Lookup tool that does all of that in one place. Paste an address, and within a few seconds you get coordinates, postal code, city, region, country, timezone, and other location details. You can also download the results or generate a map preview if you need to share the location.

The video attached shows how it works.

If anyone here works with property data, listings, or location information, maybe it’ll save you a few clicks too. It’s free to use - no account or credit card required.

Try it here

I'm both a licensed realtor and a software developer.

I built a platform to identify the best on-market flips/wholesale opportunities here in LA/OC/IE, but the data quality is becoming an issue now that I want to add AI features to see if it can help me source off-market deals.

I want to get a back-office data connection (free-ish for licensed brokers (I'll pay for it)). I would get it through my current broker, but the guy is so low tech that he doesn't understand why I want the data feed. Even when he brought me on board, it took about 2 months because he sent the paperwork via mail.

If there are any tech-forward brokers working in this space, shoot me a line. I'd love to get in touch.

How do you guys think the real estate market and technologies will change because of AI over the next few years? Are we looking at complete automation of listing marketing and lead nurture, or is it just overhyped?

Where It Began

In 2003 I was doing GIS consulting for Pathmark Supermarkets, helping them implement Anysite — a market analysis platform used to generate detailed demographic and trade area reports for potential new store sites.

Pathmark wasn't satisfied with the drive-time generators available at the time, so their analysts did it manually. They'd start at a subject property with a stopwatch and a Hagstrom paper map, drive north for two minutes, stop, mark the location, keep going — repeating the process in every direction until they had enough points to hand-draw 2, 4, 6, and 8-minute drive-time regions around each site.

If you've never heard of a Hagstrom map — think Google Maps, but paper, and you had to fold it yourself (usually unsuccessfully).

Pathmark recognized the obvious safety risk of asking analysts to monitor a stopwatch, mark a paper map, and navigate busy suburban traffic simultaneously. They asked me to automate it.

I built an app that connected a GPS unit to a laptop and polled for coordinates at timed intervals. The analyst simply drove the primary and secondary roads around each site, and the app tracked their location automatically every two minutes. The GPS data was then used to generate accurate drive-time regions that were imported directly into Anysite. Problem solved.

Then It Got Interesting

During that same period I was also working with a developer on retail site selection — touring markets and identifying potential locations for pharmacies, c-stores, banks, and supermarkets. This was well before smartphones, so we used digital cameras and — you guessed it — Hagstrom maps. We'd photograph properties and broker signs and hand-mark locations and notes directly on the map.

I kept thinking: what if I could capture my GPS location at the exact moment I took a picture? I could geo-reference every image taken during a market tour, and have a complete digital record of every site of interest that could be viewed on a map and shared with the whole team.

The solution came in the form of the Ricoh Caplio Pro G3 — a GPS camera that wrote latitude and longitude directly into each image's data. I'd take pics of the properties, download the images to my laptop, and map every location in my app. Click a point on the map, see the photo. Click the photo, see the point on the map. It worked exactly as I'd imagined.

Fast Forward

When smartphones arrived with built-in cameras and GPS, everything I needed was in one device. Apps like GPS Essentials and Conota Camera added precise location data to images, which I could display in whatever mapping tool I was using. It worked well, but was still a cobbled-together workflow. There was no real-time sharing of data and the images were either on my phone or laptop.

The next evolution of this is what we're now building with Pics & Parcels — currently in pre-release. Tour a market, photograph any property of interest, add notes, and everything is instantly available to your entire team for review and follow-up.

For those of you doing site selection and market tours today — what tools or workflows are you using in the field?

#SiteSelection #CommercialRealEstate #PropTech #LandAcquisition #RealEstateTechnology

Has anyone built a viable real estate CRM? I am an agent and I own a RE proptech company.

I think I've tried 5 of them in the last 18 months and am not sold on any of them. Most of them have too many features I don't need, or it's impossible to figure out how to setup things.

If I really tried I could probably build my own but I do not have the time or energy to attempt that. I am looking for a CRM to use personally, and potentially one that we can bundle into our platform to create a more vertical operation.

If you've built something, let's chat!

Looking at switching from Follow Up Boss to consolidate some of my tech stack. Brivity seems to have everything I'm looking for but I'm hoping to get some feedback from folks using the platform before making the switch

Hey-

I built a free Chrome extension that captures real estate leads while you browse. One click to add to your pipeline.

FB/LI groups, Nextdoor etc. can be a goldmine for leads. Manually collecting, sorting and organizing the data is painful and time consuming.

this eliminates that and does it for you

How it works:

• Browse Facebook, LinkedIn, or Nextdoor etc. - leads get flagged as you scroll (buyer, seller, renter, referral)
• On Zillow, Redfin, or Realtor.com: Click any listing to capture it - address, price, and details auto-pull
• All leads get sorted by intent so you know who to contact first
• export to CSV if youd like

browse normally, it spots leads

If you want to try it out comment and I'll send you a DM.

Hey everybody! About a year and a half ago I posted here looking for beta testers for a side project called Ugly House Finder (a tool for finding off-market distressed properties). Around 55 of you signed up, a few even paid for a few months, and a bunch of the feedback I got in that thread genuinely shaped where it went. Figured I owed the sub an update, and a way to actually try it instead of just reading about it.

Back then it basically read street-level photos for signs of neglect (boarded windows, overgrown yards), pulled some public data and Census info, and spit out a single score. It's come a long way since:

• Coverage went from a handful of areas to most of the country, thousands of counties.
• It doesn't just read street-level photos anymore. It also reads aerial/overhead imagery, so it catches more and still works in places Google Street View never drove
• Instead of one number, it tiers everything Hot / Warm / Cold, and it now weighs the owner's situation, not just how rough the house looks. So it's better at surfacing people who might actually sell, and not skipping a great potential lead that just happens to sit behind some overgrown trees.
• It can run a whole county or region at once now, not just one neighborhood at a time

This whole project got started when a wholesaler friend of mine told me he'd pay $1000 for any lead that he could turn into a deal. After learning about driving-for-dollars, I figured I needed a way to do it at scale.

Rather than just talk about it, drop your county or ZIP in the comments and I'll reply with what it finds there. Roughly how many distressed candidates, the Hot/Warm/Cold breakdown, and one example Hot property with the address blurred. A lot of areas I can turn around pretty much on the spot. I'd genuinely rather show you than tell you.

And if it nails your area, tell me. If it's way off, definitely tell me, because that's the stuff I actually want to hear. Thanks for reading!

Curious if any of you realtors have used them in the past, did you close seller leads from them?