Editorial portrait of Jesse Zhang
Photo: Decagon (photographer not stated) · Publisher-directed editorial use of an official or press portrait; underlying copyright retained by the credited source and no open reuse licence stated

FigureAsia 35 Under 35 · Business

Jesse Zhang

Age 28 · Enterprise software and business services · United States / Chinese diaspora

Turned autonomous support agents into contracted enterprise operations

Approximate age at the edition boundary
28
Field
Business
Country or region
United States / Chinese diaspora
FigureAsia U35 Assessment
92.0 / 100

Career and operating record

Remove valuation, fame and financing from view, and Jesse Zhang still has a measurable 2025–2026 record. By late 2025 Decagon’s AI agents were in use at more than 100 companies for returns, cancellations, account changes and other customer-service work.

Decagon made autonomous agents an operating-budget decision for established enterprises, shifting the discussion from demonstrations to service accountability. The limitations are equally clear: Vendor-reported revenue and customer outcomes need continued client-side verification, and automation quality remains an active operational risk.

Jesse Zhang is a founder and operating executive and serves as co-founder and chief executive at Decagon. In enterprise software and business services, the work addresses automating complex customer-service actions while preserving brand voice, escalation controls and access to underlying business systems.

Annual recurring revenue exceeded US$30 million and more than tripled year on year as the company moved beyond pilot deployments. Zhang built a roughly 200-person organisation and signed customers including large travel, education and consumer-service companies.

As co-founder and chief executive, Zhang led commercial contracting, customer deployment and organisational scale; technical model work is appropriately shared with his co-founder and team.

Why Jesse Zhang is on the list

For Jesse Zhang, this was a boundary decision grounded in what changed during 2025–2026, not in what may happen next.

By late 2025 Decagon’s AI agents were in use at more than 100 companies for returns, cancellations, account changes and other customer-service work. As co-founder and chief executive, Zhang led commercial contracting, customer deployment and organisational scale; technical model work is appropriately shared with his co-founder and team.

Annual recurring revenue exceeded US$30 million and more than tripled year on year as the company moved beyond pilot deployments. Zhang built a roughly 200-person organisation and signed customers including large travel, education and consumer-service companies.

Zhang’s paying enterprise base and repeated deployments were stronger than agent-software founders whose evidence stopped at demos or financing.

The 2025–26 business record

Operating result

By late 2025 Decagon’s AI agents were in use at more than 100 companies for returns, cancellations, account changes and other customer-service work. As co-founder and chief executive, Zhang led commercial contracting, customer deployment and organisational scale; technical model work is appropriately shared with his co-founder and team.

Market consequence

Annual recurring revenue exceeded US$30 million and more than tripled year on year as the company moved beyond pilot deployments. The result was completed within Zhang’s verified responsibilities as co-founder and chief executive at Decagon, while delivery remains credited to the relevant team and partners.

Strategic execution

Zhang built a roughly 200-person organisation and signed customers including large travel, education and consumer-service companies. The evidence connects Zhang to strategy and accountable execution; organisational output is not assigned to the individual wholesale.

The work in its market

Jesse Zhang is assessed against founders and operators in enterprise software and business services. Company performance establishes scale; individual credit follows only where the public record ties decisions and execution to the person’s role.

Assessment breakdown

92.0out of 100

01

Operating execution

27.6 / 30

By late 2025 Decagon’s AI agents were in use at more than 100 companies for returns, cancellations, account changes and other customer-service work. As co-founder and chief executive, Zhang led commercial contracting, customer deployment and organisational scale; technical model work is appropriately shared with his co-founder and team. The result is completed and operational rather than announced.

02

Commercial consequence

23.0 / 25

The record produced measurable consequence in enterprise software and business services, with company-wide outcomes kept distinct from personal credit.

03

Individual agency

18.4 / 20

As Co-founder and chief executive, Jesse Zhang held an identifiable decision-making and execution remit.

04

Industry influence

13.8 / 15

Turned autonomous support agents into contracted enterprise operations. The work established a reference point beyond one financing or publicity cycle.

05

Asian and global relevance

9.2 / 10

Chinese-American entrepreneur The work also carries consequence beyond one immediate market.

Evidence and attribution

Material claims on this page are supported by the edition’s evidence record. FigureAsia tests age, identity, role, result and individual attribution before publication. Public profiles present the reported record; supporting documentation is retained for accuracy review and corrections.

Achievement records
3
Assessment window
2025–26
Editorial status
Included in the 2026 FigureAsia 35 Under 35 edition

Rights and credit

The portrait is published under the rights basis recorded for this edition. Third-party ownership and reuse restrictions remain in force.

Publication status
Published under a documented rights basis
Credit
Decagon (photographer not stated)
Licence
Publisher-directed editorial use of an official or press portrait; underlying copyright retained by the credited source and no open reuse licence stated
Portrait source and credit