Skip to content
Agentic 10-K

NSCALE Ltd

AI agent disclosures in SEC filings

As of 2026-09-18, NSCALE Ltd disclosed AI-agent language in 1 SEC filing since 2026-09-18 (source: Agentic 10-K, from SEC EDGAR).

Market cap
—
First seen
2026-09-18
Latest filing
2026-09-18

Matching filings by quarter

012Q1 '25Q2Q3Q4Q1 '26Q21Q3Q4*
Filings* Quarter in progress

What the filings cover

Functions named

IT & security ops, Legal & compliance, Sales & marketing, Software development

Vendors and products named

None named

Source

1 filing since 2025-01-01. All EDGAR filings (opens in a new tab)

Stage and function are keyword-rule labels, not the company’s words.

In its own words

Sentences copied from the filings, whitespace normalised.

“to robotics enterprises, this full stack offering will help companies speed up image and document processing, fine-tune LLMs on their proprietary data, and deploy AI agents in-house using open-source models.”

S-1Filed 2026-09-18Source on sec.gov (opens in a new tab)Filing index (opens in a new tab)

“Usage continues to broaden from frontier labs to mainstream enterprises; a number of enterprises are actively adopting and implementing AI agents.”

S-1Filed 2026-09-18Source on sec.gov (opens in a new tab)Filing index (opens in a new tab)

All matching filings

S-1 filed 2026-09-18 Filing index (opens in a new tab)

S-1Filed 2026-09-18

NSCALE offers solutions to help companies deploy AI agents in-house.

“to robotics enterprises, this full stack offering will help companies speed up image and document processing, fine-tune LLMs on their proprietary data, and deploy AI agents in-house using open-source models.”

S-1Filed 2026-09-18

NSCALE notes enterprises are adopting AI agents and related compute risks.

“Developments in artificial intelligence have driven a pervasive shift across the globe as use cases, both commercial and noncommercial, continue to emerge and improve. Usage continues to broaden from frontier labs to mainstream enterprises; a number of enterprises are actively adopting and implementing AI agents. From foundational model training to inference at scale, both the development and usage of artificial intelligence require large quantities of high‑performance compute. We expect this to drive an expanding mix of sustained, large‑cluster requirements and event‑driven workloads. If AI adoption slows, or if demand shifts away from high-performance infrastructure toward lower-cost alternatives, our opportunity set could be smaller than anticipated.”

S-1Filed 2026-09-18

NSCALE discusses broadening AI compute demand including enterprise AI agent deployment.

“Broaden Customer Base and Enter New Markets: We are extending our reach into new industries, geographies, and verticals, serving regulated and sovereign customers worldwide, and replicating our proven hub-and-spoke model in Asia and other high-growth regions. AI compute demand is broadening from hyperscaler-led LLM training to enterprise inference, fine-tuning, and deployment, as well as physical AI and other use cases. While continuing to capitalize on our offerings that are optimized for AI training at scale, we are simultaneously positioning to serve evolving needs through enterprise-ready capacity, managed orchestration, and distributed clusters aligned to regulatory and performance constraints. We are in the process of supporting this growth with an elevated compliance profile, and are in the process of obtaining industry standard certifications and qualifications, including ISO 27001, SOC 2 and ISO 22237-aligned data center standards, and developing NIS2 readiness, and EU sovereign cloud compliance frameworks. We expect the Anyscale Acquisition to further expand our customer base across multiple customer archetypes. We believe our ability to win AI natives will be significantly strengthened with Anyscale offering the ability to build custom AI models for high demand AI applications with enhanced performance and an improved developer experience. Meanwhile, from healthcare to e-commerce to robotics enterprises, this full stack offering will help companies speed up image a”