Self-hosted agent infrastructure slowed engineering focus. Now a managed foundation lets Omnichat build AI features twice as fast.
An AI-powered omnichannel conversational commerce platform founded in 2017, used by more than 5,000 brands worldwide for sales, marketing, and customer service.
As customer expectations shifted toward AI, the company needed a faster way to bring agentic capabilities to market without adding infrastructure...
“Amazon Bedrock AgentCore changes where we invest our engineering effort. Instead of building agent infrastructure, we can focus on the AI experiences that differentiate Omnichat.”
AI-powered omnichannel CRM unifying WhatsApp, Instagram, LINE and live chat for sales and support.
Cloud computing platform and on-demand infrastructure services.
Omnichat's Marketing and customer service agents is part of this use case:
Related implementations across industries and use cases
Every GPU was on a live call. New model benchmarks waited months. AWS gave them a separate lane—research and production run in parallel.
Building custom speech infrastructure risked draining engineering. An API-first voice layer refocused developers on core orchestration.
Manual checks across 160 games bottlenecked support. GenAI now references player data to resolve 90% of inquiries in minutes.
Every GPU was on a live call. New model benchmarks waited months. AWS gave them a separate lane—research and production run in parallel.
Building custom speech infrastructure risked draining engineering. An API-first voice layer refocused developers on core orchestration.
Thousands of tables tracking the same metrics differently. No one knew which to trust — not humans, not AI. One governed layer changed that.
SThree people, three different AI answers. Grounded data sources fixed that — finance now has years of vendor spend at its fingertips.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Self-hosted agent infrastructure slowed engineering focus. Now a managed foundation lets Omnichat build AI features twice as fast.
An AI-powered omnichannel conversational commerce platform founded in 2017, used by more than 5,000 brands worldwide for sales, marketing, and customer service.
As customer expectations shifted toward AI, the company needed a faster way to bring agentic capabilities to market without adding infrastructure...
“Amazon Bedrock AgentCore changes where we invest our engineering effort. Instead of building agent infrastructure, we can focus on the AI experiences that differentiate Omnichat.”
AI-powered omnichannel CRM unifying WhatsApp, Instagram, LINE and live chat for sales and support.
Cloud computing platform and on-demand infrastructure services.
Omnichat's Marketing and customer service agents is part of this use case:
Related implementations across industries and use cases
Every GPU was on a live call. New model benchmarks waited months. AWS gave them a separate lane—research and production run in parallel.
Building custom speech infrastructure risked draining engineering. An API-first voice layer refocused developers on core orchestration.
Manual checks across 160 games bottlenecked support. GenAI now references player data to resolve 90% of inquiries in minutes.
Every GPU was on a live call. New model benchmarks waited months. AWS gave them a separate lane—research and production run in parallel.
Building custom speech infrastructure risked draining engineering. An API-first voice layer refocused developers on core orchestration.
Thousands of tables tracking the same metrics differently. No one knew which to trust — not humans, not AI. One governed layer changed that.
SThree people, three different AI answers. Grounded data sources fixed that — finance now has years of vendor spend at its fingertips.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.