FreightTech Startup
Personal ChatGPT for Logistics
We reframed Tiliport as a private, logistics-specific ChatGPT – but based on each user’s particular logistics data.
Year :
2025
Niche :
B2C Software on B2B Market
Company :
Tiliport - 4th Version
Duration :
1 month



Problem :
ChatGPT can’t help with your real logistics. It doesn’t know your customers, providers, shipments, or deadlines. Freight professionals need answers and reminders grounded in their own data – not general knowledge.



Solution :
Tiliport worked like a teammate. It read your logistics emails (when CC’ed), then answered questions like:
– What’s arriving next week?
– Who didn’t send docs?
– Which quotes weren’t answered?
Plus, it emailed you daily reminders based on what matters to you.



Challenge :
Despite all benefits, users still didn’t CC emails. We realized that users didn’t have this pain - they simply don’t have anything to ask logistics AI in chat. We also realized that only c-level executives can approve tools that access internal data. Employees couldn’t adopt it on their own. Corporate ownership of data and fear of being “watched” overrode the utility.
Summary :
– Built a private, freight-specific ChatGPT with real-time email context
– Learned that personal adoption isn’t possible in an enterprise data environment
– Pivoted to a value proposition teams could adopt without resistance






More Projects
FreightTech Startup
Personal ChatGPT for Logistics
We reframed Tiliport as a private, logistics-specific ChatGPT – but based on each user’s particular logistics data.
Year :
2025
Niche :
B2C Software on B2B Market
Company :
Tiliport - 4th Version
Duration :
1 month



Problem :
ChatGPT can’t help with your real logistics. It doesn’t know your customers, providers, shipments, or deadlines. Freight professionals need answers and reminders grounded in their own data – not general knowledge.



Solution :
Tiliport worked like a teammate. It read your logistics emails (when CC’ed), then answered questions like:
– What’s arriving next week?
– Who didn’t send docs?
– Which quotes weren’t answered?
Plus, it emailed you daily reminders based on what matters to you.



Challenge :
Despite all benefits, users still didn’t CC emails. We realized that users didn’t have this pain - they simply don’t have anything to ask logistics AI in chat. We also realized that only c-level executives can approve tools that access internal data. Employees couldn’t adopt it on their own. Corporate ownership of data and fear of being “watched” overrode the utility.
Summary :
– Built a private, freight-specific ChatGPT with real-time email context
– Learned that personal adoption isn’t possible in an enterprise data environment
– Pivoted to a value proposition teams could adopt without resistance






More Projects
FreightTech Startup
Personal ChatGPT for Logistics
We reframed Tiliport as a private, logistics-specific ChatGPT – but based on each user’s particular logistics data.
Year :
2025
Niche :
B2C Software on B2B Market
Company :
Tiliport - 4th Version
Duration :
1 month



Problem :
ChatGPT can’t help with your real logistics. It doesn’t know your customers, providers, shipments, or deadlines. Freight professionals need answers and reminders grounded in their own data – not general knowledge.



Solution :
Tiliport worked like a teammate. It read your logistics emails (when CC’ed), then answered questions like:
– What’s arriving next week?
– Who didn’t send docs?
– Which quotes weren’t answered?
Plus, it emailed you daily reminders based on what matters to you.



Challenge :
Despite all benefits, users still didn’t CC emails. We realized that users didn’t have this pain - they simply don’t have anything to ask logistics AI in chat. We also realized that only c-level executives can approve tools that access internal data. Employees couldn’t adopt it on their own. Corporate ownership of data and fear of being “watched” overrode the utility.
Summary :
– Built a private, freight-specific ChatGPT with real-time email context
– Learned that personal adoption isn’t possible in an enterprise data environment
– Pivoted to a value proposition teams could adopt without resistance





