Building agents took weeks on pricey models. Switching to Gemini cut costs 10x, letting clients deploy them in hours.
A low-code enterprise workflow automation platform built on traditional cloud infrastructure, serving banking and finance customers with strict regional security and compliance requirements.
Customer demand shifted toward intelligent, autonomous workflows, but the existing infrastructure could not support the microservices architecture...
“On a performance and cost basis, using the Gemini models rather than those of a prominent competitor is a no-brainer.”
Low-code platform for building autonomous enterprise workflows and AI agents.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Autonom8's Workflow automation is part of this use case:
Related implementations across industries and use cases
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Novices were too embarrassed to ask basics publicly. Private AI agents now answer instantly, cutting response times from 10s to near-zero.
Overwhelmed by admin, onsite teams missed leasing leads. AI took over routine calls and resident messaging, freeing staff to close leases.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Building agents took weeks on pricey models. Switching to Gemini cut costs 10x, letting clients deploy them in hours.
A low-code enterprise workflow automation platform built on traditional cloud infrastructure, serving banking and finance customers with strict regional security and compliance requirements.
Customer demand shifted toward intelligent, autonomous workflows, but the existing infrastructure could not support the microservices architecture...
“On a performance and cost basis, using the Gemini models rather than those of a prominent competitor is a no-brainer.”
Low-code platform for building autonomous enterprise workflows and AI agents.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Autonom8's Workflow automation is part of this use case:
Related implementations across industries and use cases
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Novices were too embarrassed to ask basics publicly. Private AI agents now answer instantly, cutting response times from 10s to near-zero.
Overwhelmed by admin, onsite teams missed leasing leads. AI took over routine calls and resident messaging, freeing staff to close leases.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.