An Army of AI Agents vs. 1.69 Million Broken Records
How AI agents that reason through data chaos turned an unsolvable problem into a competitive advantage
Offers are going to the wrong people. Real owners missed entirely. Competitors reaching them first. Everyone knew the data was broken, but fixing it would take 50 analysts months of work. Not worth it.
An army of AI agents that reason through data chaos, understanding that “Miller, John” and “John Miller” are the same person without being told. 10 agents doing in hours what used to be a full-time job.
Problems that were previously unsolvable are now solvable. Better targeting. Faster deals. A capability their competitors lack and cannot easily imitate.
1.69M
Records Processed
1.25M
Unique Owners
125x
Cost Savings
10x
Time to Market
A Capability Their Competitors Don't Have
Achieve better targeting, close deals faster, and track ownership more effectively than competitors. Because they're still relying on flawed data.
More Accurate Offers
Clearly identify ownership details before reaching out to avoid sending offers to the wrong person or overlooking key owners.
62%
94%
Faster to Deals
Skip manual research; data is available on day one. Begin outreach right away instead of spending weeks cleaning it.
Track Ownership Changes
Identify when properties change ownership before competitors to gain the first-mover advantage on new deals.
The Competitive Advantage
Everyone handling public tax data faces these issues. Fixing them was previously not financially practical until AI agents enabled it. This client achieved that, while their competitors have not.
“Previously, we sent four mailers to the same person and overlooked the actual property owners. Now, we know exactly who owns what before we make contact.”
Public Data, Private Headaches
The data originates from public tax rolls and county records. As anyone familiar with government data knows, quality can vary greatly. Some counties assign the same ID to hundreds of different individuals, while others split a single person across dozens of IDs. All organizations that rely on this data must contend with these issues.
670 Different People. One ID.
Owner ID 817132 was linked to 670 completely unrelated people. Different names, different states, nothing in common.
Excluding one person would mean excluding all 670.
Each person can be managed individually.
44,421
Collision Groups
670
Worst Case
51,609
New IDs Created
Not Financially Feasible Before Agentic AI
Rules-based systems cannot manage the endless variations in how names and addresses are listed across county records.
How many rules would you need to match these?
From ID Chaos to Clean Profiles
Observe how AI-validated confidence scores transform fragmented, conflicting records into unified owner profiles.
Owner Records Export
1.69M records with broken IDs
John Miller
123 Oak St, Denver CO
Paula Richardson
456 Pine Ave, Boulder CO
Miller, J
123 Oak Street
JOHN MILLER
Oak St 123, Denver
Click the toggle above to see the transformation
10 AI Agents Working in Parallel
A detailed look at how the agents reasoned through 1.69 million records.
Entity Resolution Pipeline
Raw Records
Fix Collisions
Consolidate
Cross-Reference
Match Records
Clean Data
Inconsistent Public Records
Owner ID 817132 was associated with 670 distinct individuals. Miller Paula was listed under four different IDs. Anyone working with government data at the county level knows this pain.
1.69M
Total Records
44,421
Collision Groups
99,581
Unstable Groups
What an Army of AI Agents Accomplished
We deployed 10 agents for this project, though we could have deployed hundreds, as the reasoning scales infinitely. That was the key change.
44,421 collision groups fixed. 99,581 unstable IDs consolidated.
cost savings
10x
Faster to Market
1
Record per Owner
100%
Decisions Documented
Works for Your Industry
The Same Approach, Tailored to Your Data
No matter how messy your data is, we can help clean it up.
Ownership of mineral rights
Monitor changes in ownership across millions of records. Contact the right person on the first attempt.
First-mover advantage
Property and owner records
The same property may have different records over time. Keep track of ownership accurately.
10x faster research
Unify Customer Data
A single customer may have multiple products and different names. Establish a unified customer view.
Single source of truth
Patient Record Matching
Ensuring the same patient is correctly identified across different visits and systems to unify records across various facilities.
90%+ duplicate reduction
Supplier Consolidation
Use the same vendor with different names after M&A to streamline your supplier base.
30%+ duplicate suppliers found
Custom Data Challenges
Handling messy data that requires matching, deduplication, or consolidation.
Let's discuss your use case
Your data could be your competitive advantage
If your industry has messy data that everyone struggles with, we can help you fix it. Talk to us about your specific challenges.
From this project
1.69M
Records Processed
125x
Cost Savings
10x
Faster to Market