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Jake HellerJan 6, 2026

AI Deal Sourcing for Brokers (Manus)

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AI Deal Sourcing for Brokers (Manus)

Jake Heller

Discover how to leverage AI with Manus to efficiently find apartment building acquisition opportunities in Los Angeles. This autonomous agent scans various platforms and public records to identify potential deals matching specific investment criteria, delivering a prioritized list and detailed reports.

Transcript

00:00
We are going to use Manus to find deals as a broker.
00:04
That's what we care about, right?
00:06
We want to find deals.
00:08
So let's use AI to do so.
00:10
I already created a prompt, in Claudia which we will utilize.
00:15
I'm going to copy and paste it.
00:16
I'm not going to waste your time.
00:18
but it's essentially research and identify potential apartment building acquisition opportunities in LA that match my investment criteria area as a commercial real estate broker.
00:28
All right, so we want to exhaust everything to find deal flow and Manus allows us to get creative and do so.
00:37
It's going to scan distress signals, it's going to scan public resources like Crexi, LoopNet.
00:44
It's going to scan everything across the market to help us find deals.
00:50
All right, so let's go ahead and hit, we'll hit agent there.
00:56
let's hit send.
00:57
So it's going to get to work.
00:58
It's first just going to review our prompt.
01:00
It's going to do some thinking and then it's going to go wide.
01:03
Manus is an autonomous agent.
01:05
It could execute any sort of task, it could exit or it could access any sort of database.
01:12
If there's, you know, password protected databases, you can give it that information so it can go ahead and do, Looks like it's going to create a top 10 priority list for the most promising opportunities for us as well.
01:24
So watch it go to work.
01:26
It's going to create its to do list here.
01:27
Search research, public property data sources and commercial listing platforms.
01:32
So let's watch it go to work here.
01:34
As you can see on the right side, you'll see what it's doing.
01:39
it acts, it shows us its computer here, which is pretty nice.
01:42
And it looks like it's going to start with LoopNet.
01:45
I'm not sure if it could actually access LoopNet or if LoopNet's bot protection software is robust enough to prevent it.
01:54
But let's see it.
01:55
We're going to watch in real time here.
01:58
We gave it some pretty specific criteria.
02:01
Obviously the market deal size, price points, cap rates, etc.
02:05
data sources identified.
02:07
Cool.
02:08
So look at that.
02:09
Look.
02:09
It's already done a lot of research here how quickly it moves.
02:13
Potential distressed auction properties, market statistics.
02:17
Look at that.
02:17
It's going to go in and it's going to filter by submarkets in all of our criteria.
02:22
It's, it's actually quite brilliant that it could do this and do it so quickly.
02:26
Wonder if it'll have trouble.
02:28
So it's already got Los Angeles in there.
02:30
Great.
02:31
It selected multifamily.
02:32
Great.
02:33
Let's see.
02:33
it's going to fill in the cap right there.
02:35
Look at that.
02:36
Beautiful.
02:36
So we asked it in our prompt.
02:38
We didn't have to do this, but, and then it did 5 to 50 units, which is exactly what we wanted.
02:43
So let's see if it could actually execute that query.
02:45
2 million to 15 million.
02:46
It added in there as well for pricing.
02:48
So cool.
02:49
Let's hit search.
02:50
Looks like it did it.
02:51
Boom.
02:51
There's all of our properties that meet that criteria.
02:54
There's quite a few of them.
02:55
So I'm not sure if it's going to pull all of them.
02:57
336.
02:58
I hope it doesn't spend the time to actually pull all of them there.
03:00
That would be a lot of credits.
03:03
First deal, it's going into there.
03:05
Six units.
03:06
It's grabbing pictures, it's grabbing all the information.
03:10
Gonna create a file.
03:12
Now what's so beautiful about this is we don't need to be sitting here and watching this.
03:17
we could be doing so many other things.
03:19
So fully autonomous.
03:21
Give it direction, watch it go to work and come back with results.
03:25
so now it's going to go into crexi.
03:27
Let's see if it could access crexi.
03:28
Verifying it might have the bot protection which we cannot access.
03:33
Let's see.
03:35
I'm not sure it's able to access Crexy It's going to go through public records.
03:40
It's going to exhaust as many resources as possible to help us find deals, which is cool.
03:46
And you can see all that, happening in real So it looks like we're just about done here.
04:35
It's putting the final touches on it.
04:37
Our top 10 properties ranked, we will see in just a moment.
04:41
And we'll also understand how they ranked it as far as the criteria.
04:46
So that was, pretty fast.
04:49
Again, you don't need to be sitting and watching this.
04:51
It all happens autonomously, which is pretty great.
04:56
I mean, being able to just keep your finger on the pulse as far as deals that are out there.
05:01
Obviously critical as a broker.
05:03
Looks like we're getting a full executive summary with market conditions.
05:07
It's identified the top opportunities.
05:10
Five tier one priority properties were identified.
05:13
These properties combine strong cap rates, attractive pricing per unit and optimal size for management and locations in target neighborhoods.
05:20
Okay, so there's our criteria.
05:22
And so we asked it to create an Excel file As well.
05:26
Our research is complete.
05:28
Wonderful.
05:29
It gave us a top opportunity.
05:31
So before the Excel file, let's just take a look at the other stuff.
05:34
So here's the LA apartment building investment research.
05:37
Here's the top 10 priority properties and why.
05:41
This property scores highly due to its excellent price per unit, optimal size for management efficiency and location and target neighborhood.
05:48
The cap rate is solid, offering a good balance of immediate return value add potential.
05:52
Cool little description there.
05:53
And then we have our summary report and here is our Excel file with the opportunities, how clean that is.
06:02
And it's broken out by tier one, tier two and tier three.
06:08
So if you're a broker focusing on the higher probability sites, bringing your buyer into the mix, I would think maybe most of these are, are listed.
06:18
That's, that's my guess.
06:19
which, that's okay.
06:21
but tier one priority, so Taft Avenue score of 83.
06:25
It's 20 units, good price per unit, decent cap rate, great area.
06:30
Crenshaw, 17 units.
06:32
Also good price per unit, very high cap rate.
06:34
It's part of a 41 unit portfolio.
06:36
Highest cap rate.
06:38
Interesting.
06:39
we obviously don't have the all the details on that but pretty cool way of, you know, finding interesting deals.
06:46
Higher probability deals perhaps.
06:48
Manus again you get out what you put in.
06:51
We gave it a good prompt, we gave it some good instruction, we got a good result.
06:55
So and it was done quickly.
06:58
So overall happy.
06:59
the suggested follow ups are also pretty spot on, as well.
07:03
So if you want to keep going with this, you certainly can.
07:06
And also integrates and connects with a lot of your tools.
07:10
So Gmail, Google Calendar, there's other connectors as well.
07:14
So if you know, you've seen me previously, you know that Manus, is one of my favorite platforms out there.
07:20
So thanks for listening in.
07:22
in.
AI Deal Sourcing for Brokers (Manus) — Tella