Riders faced 40-minute waits as agents juggled four chats. AI now resolves issues in seconds, freeing humans for sensitive cases.
A global mobility platform operating across six continents and thousands of cities, serving millions of riders and drivers with support needs ranging from fare adjustments to safety incidents.
Riders and drivers faced wait times of 30 to 40 minutes while agents juggled up to four simultaneous chats, resulting in severe burnout and robotic...
“We were in a really tough spot. Our customers were frustrated. We were pouring a lot of time and energy into creating new products, but they weren't moving the needle.”
On-demand ridesharing, bicycle-sharing, and motorized scooter platform.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Lyft's Customer support is part of this use case:
Related implementations across industries and use cases
Scripted bots lacked backend access, forcing manual GPS fixes. Now, an API-connected AI instantly closes rides and diagnoses root causes.
A legacy bot passed 50% of chats to staff. Now, AI agents connect 62 databases to resolve 87% of inquiries autonomously.
Every new support agent meant months of engineering handoffs. Now the people closest to customers build and ship their own.
A legacy bot passed 50% of chats to staff. Now, AI agents connect 62 databases to resolve 87% of inquiries autonomously.
A solo operator was firefighting volume. AI now resolves 50k monthly inquiries, freeing humans to handle complex enterprise cases.
Fragmented support caused frustrating handoffs. Live AI translation now lets a small English-speaking team handle 14 languages instantly.
Each new agent took 8 weeks to ship reliably. A factory framework cut that to days, freeing people for the relationship work AI can't do.
Data siloed across five products, no shared identity. A unified ID and AI trained on slang now complete cancellations inside the chat.
Agents summarized every call by hand and memorized talk scripts. Voice-to-text and real-time screen pops cut after-call work by 80%.
Riders faced 40-minute waits as agents juggled four chats. AI now resolves issues in seconds, freeing humans for sensitive cases.
A global mobility platform operating across six continents and thousands of cities, serving millions of riders and drivers with support needs ranging from fare adjustments to safety incidents.
Riders and drivers faced wait times of 30 to 40 minutes while agents juggled up to four simultaneous chats, resulting in severe burnout and robotic...
“We were in a really tough spot. Our customers were frustrated. We were pouring a lot of time and energy into creating new products, but they weren't moving the needle.”
On-demand ridesharing, bicycle-sharing, and motorized scooter platform.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Lyft's Customer support is part of this use case:
Related implementations across industries and use cases
Scripted bots lacked backend access, forcing manual GPS fixes. Now, an API-connected AI instantly closes rides and diagnoses root causes.
A legacy bot passed 50% of chats to staff. Now, AI agents connect 62 databases to resolve 87% of inquiries autonomously.
Every new support agent meant months of engineering handoffs. Now the people closest to customers build and ship their own.
A legacy bot passed 50% of chats to staff. Now, AI agents connect 62 databases to resolve 87% of inquiries autonomously.
A solo operator was firefighting volume. AI now resolves 50k monthly inquiries, freeing humans to handle complex enterprise cases.
Fragmented support caused frustrating handoffs. Live AI translation now lets a small English-speaking team handle 14 languages instantly.
Each new agent took 8 weeks to ship reliably. A factory framework cut that to days, freeing people for the relationship work AI can't do.
Data siloed across five products, no shared identity. A unified ID and AI trained on slang now complete cancellations inside the chat.
Agents summarized every call by hand and memorized talk scripts. Voice-to-text and real-time screen pops cut after-call work by 80%.