FreightTech Startup
AI Profiles for Logistics Professionals
My boldest attempt to redefine trust in logistics. We built a system that created AI-generated performance profiles for every logistics professional worldwide – over 62 million – based on public records and private email data.
Year :
2025
Niche :
B2C Software on B2B Market
Company :
Tiliport - 5th Version
Duration :
2 weeks
Problem :
In logistics, your reputation travels faster than your freight ever will. Yet today, professionals rely on word-of-mouth, anonymous reviews, or no signal at all to choose partners – a huge risk in an industry where trust determines margin. Worse, performance data is often buried in emails or never captured at all.
Solution :
I flipped the model. We pre-built AI profiles by scanning public freight records and leaked email threads where logistics professionals were quoted, booked, or ghosted.
We built:
– Public metrics: lane activity, partnerships, bill of lading volume
– Private signals: quote speed, booking friction, delay handling
– Red flag alerts: missed ETAs, ghosting, unread messages
Then we told the user:
Your AI Profile is already public. Check it before someone else does.
It turned fear of exposure into a trigger for action.
Challenge :
Tiliport relied on a hybrid dataset: public freight records and privately verified email threads. While public data provided a baseline for logistics activity and credibility, the most valuable insights – like quote response speed, booking behavior, and issue resolution – required users to upload email threads and have them verified by all involved parties.
The core challenge was data acquisition:
– Users were reluctant to upload threads involving customers or partners.
– Without broad participation, private performance signals remained limited.
– The product’s value varied depending on how much data had been linked to a profile, leading to inconsistent utility across the network.
Summary :
Tiliport was an AI-driven profiling engine that aggregates public logistics data and email-derived behavioral signals to build performance profiles for freight professionals and companies.
Each profile exists passively in the system and can be claimed, enriched, corrected, or hidden by the person it represents. The product positions profile visibility as both a reputational risk and competitive advantage – encouraging proactive engagement.
More Projects
FreightTech Startup
AI Profiles for Logistics Professionals
My boldest attempt to redefine trust in logistics. We built a system that created AI-generated performance profiles for every logistics professional worldwide – over 62 million – based on public records and private email data.
Year :
2025
Niche :
B2C Software on B2B Market
Company :
Tiliport - 5th Version
Duration :
2 weeks
Problem :
In logistics, your reputation travels faster than your freight ever will. Yet today, professionals rely on word-of-mouth, anonymous reviews, or no signal at all to choose partners – a huge risk in an industry where trust determines margin. Worse, performance data is often buried in emails or never captured at all.
Solution :
I flipped the model. We pre-built AI profiles by scanning public freight records and leaked email threads where logistics professionals were quoted, booked, or ghosted.
We built:
– Public metrics: lane activity, partnerships, bill of lading volume
– Private signals: quote speed, booking friction, delay handling
– Red flag alerts: missed ETAs, ghosting, unread messages
Then we told the user:
Your AI Profile is already public. Check it before someone else does.
It turned fear of exposure into a trigger for action.
Challenge :
Tiliport relied on a hybrid dataset: public freight records and privately verified email threads. While public data provided a baseline for logistics activity and credibility, the most valuable insights – like quote response speed, booking behavior, and issue resolution – required users to upload email threads and have them verified by all involved parties.
The core challenge was data acquisition:
– Users were reluctant to upload threads involving customers or partners.
– Without broad participation, private performance signals remained limited.
– The product’s value varied depending on how much data had been linked to a profile, leading to inconsistent utility across the network.
Summary :
Tiliport was an AI-driven profiling engine that aggregates public logistics data and email-derived behavioral signals to build performance profiles for freight professionals and companies.
Each profile exists passively in the system and can be claimed, enriched, corrected, or hidden by the person it represents. The product positions profile visibility as both a reputational risk and competitive advantage – encouraging proactive engagement.
More Projects
FreightTech Startup
AI Profiles for Logistics Professionals
My boldest attempt to redefine trust in logistics. We built a system that created AI-generated performance profiles for every logistics professional worldwide – over 62 million – based on public records and private email data.
Year :
2025
Niche :
B2C Software on B2B Market
Company :
Tiliport - 5th Version
Duration :
2 weeks
Problem :
In logistics, your reputation travels faster than your freight ever will. Yet today, professionals rely on word-of-mouth, anonymous reviews, or no signal at all to choose partners – a huge risk in an industry where trust determines margin. Worse, performance data is often buried in emails or never captured at all.
Solution :
I flipped the model. We pre-built AI profiles by scanning public freight records and leaked email threads where logistics professionals were quoted, booked, or ghosted.
We built:
– Public metrics: lane activity, partnerships, bill of lading volume
– Private signals: quote speed, booking friction, delay handling
– Red flag alerts: missed ETAs, ghosting, unread messages
Then we told the user:
Your AI Profile is already public. Check it before someone else does.
It turned fear of exposure into a trigger for action.
Challenge :
Tiliport relied on a hybrid dataset: public freight records and privately verified email threads. While public data provided a baseline for logistics activity and credibility, the most valuable insights – like quote response speed, booking behavior, and issue resolution – required users to upload email threads and have them verified by all involved parties.
The core challenge was data acquisition:
– Users were reluctant to upload threads involving customers or partners.
– Without broad participation, private performance signals remained limited.
– The product’s value varied depending on how much data had been linked to a profile, leading to inconsistent utility across the network.
Summary :
Tiliport was an AI-driven profiling engine that aggregates public logistics data and email-derived behavioral signals to build performance profiles for freight professionals and companies.
Each profile exists passively in the system and can be claimed, enriched, corrected, or hidden by the person it represents. The product positions profile visibility as both a reputational risk and competitive advantage – encouraging proactive engagement.