Notion
Autonomous workflow agents
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
- Internal AI adoption across all teams
Off-the-shelf AI wrote flat pitches. Now, models trained by top screenwriters draft tailored proposals that win work.
One of the world’s largest work marketplaces connects businesses with independent talent globally, managing millions of interactions across diverse job categories.
Proposal writing requires precision and significant time, creating friction for freelancers trying to stand out in a competitive hiring environment....
“Uma is the brain behind key parts of Upwork’s hiring and matching process. Uma’s ability to create tailored proposal drafts helps reduce friction for freelancers by helping them accurately communicate their services and offerings, positioning their unique skill sets and expertise to clients to stand out and win more work.”
Online marketplace connecting businesses with independent talent and freelance professionals.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Upwork's Job proposal writing is part of this use case:
Related implementations across industries and use cases
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Static modules lacked depth for 500M roles. AI now drives custom, multilingual voice interviews with sub-180ms latency.
Teams spent hours manually prepping for meetings. Now, custom agents generate instant briefings, speeding up client decisions by days.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Compiling research took sales reps a week. AI now synthesizes CRM data into bespoke proposals and SWOT reports in 10 minutes.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Off-the-shelf AI wrote flat pitches. Now, models trained by top screenwriters draft tailored proposals that win work.
One of the world’s largest work marketplaces connects businesses with independent talent globally, managing millions of interactions across diverse job categories.
Proposal writing requires precision and significant time, creating friction for freelancers trying to stand out in a competitive hiring environment....
“Uma is the brain behind key parts of Upwork’s hiring and matching process. Uma’s ability to create tailored proposal drafts helps reduce friction for freelancers by helping them accurately communicate their services and offerings, positioning their unique skill sets and expertise to clients to stand out and win more work.”
Online marketplace connecting businesses with independent talent and freelance professionals.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Upwork's Job proposal writing is part of this use case:
Related implementations across industries and use cases
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Static modules lacked depth for 500M roles. AI now drives custom, multilingual voice interviews with sub-180ms latency.
Teams spent hours manually prepping for meetings. Now, custom agents generate instant briefings, speeding up client decisions by days.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Compiling research took sales reps a week. AI now synthesizes CRM data into bespoke proposals and SWOT reports in 10 minutes.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.