Hang Ten Raises $53M to Challenge Legacy IT Systems Integrators with Agentic Workflows

Enterprise artificial intelligence services startup Hang Ten Systems Inc. announced it has closed a $53 million second seed round, bringing its total raised to $85 million across two seed rounds closed only five weeks apart. The round was led by Temasek-backed Xora Innovation, with participation from Mayfield, Aramco Ventures, and prominent tech leaders including Lip-Bu Tan, Sanjay Mehrotra, and Jerry Yang. Hang Ten, founded by former Infosys CEO Vishal Sikka, delivers transformation and applied AI services tailored for global enterprises like Saudi Aramco and Siemens Gamesa. This funding round underscores the accelerating push to replace traditional IT consulting and legacy systems integrators (SIs) with agentic platforms. Rather than deploying hundreds of consultants over multi-year cycles to write boilerplate integrations, Hang Ten operates with a lean team of 20 to 25 staff utilizing autonomous agentic code generation layered over domain expertise and a modular 'skills library'. As large enterprises face backlogs in custom software deployment, finance analytics, and HR modernization, the economics of delivery are fundamentally changing when code generation marginal costs approach zero. The broader trend reflects the shift in enterprise AI from experimental conversational interfaces toward operational agentic engineering workflows. Enterprise leaders are realizing that raw model performance is insufficient without reliable implementation tooling and repeatable patterns. Startups that combine autonomous code execution with hardened enterprise skills libraries are successfully securing multimillion-dollar production contracts in mere weeks—a speed unimaginable under legacy outsourcing frameworks. For DevOps practitioners and enterprise architects, the rise of agent-driven systems integration changes the build-versus-buy calculus. Engineering teams should evaluate how autonomous agent frameworks and standardized skills registries can be integrated into internal platform engineering toolchains. However, the critical operational challenge will shift from code generation to code governance: establishing strict CI/CD guardrails, security auditing, and verification suites to ensure agent-generated enterprise code remains reliable, maintainable, and compliant across multi-cloud environments.