NetApp has selected five deep-tech startups for the 15th cohort of its Excellerator programme, bringing together companies working on software development automation, artificial intelligence security, business workflow management and enterprise data intelligence.
Announced on October 16, 2026, the new cohort includes LightSprint AI, Wald.ai, Lasso Security, Cogover and QUIPU AI. The startups operate across India, the United States and Israel, according to programme coverage.
Editorial Insight
Key Highlights
Important points readers should notice.
Issue/Event: NetApp announced the 15th cohort of its Excellerator startup accelerator.
Location: Programme associated with NetApp's technology ecosystem in India, with participating startups from India, the United States and Israel.
Authority/Organisation: NetApp and the five selected deep-tech startups.
Action Taken: The company selected LightSprint AI, Wald.ai, Lasso Security, Cogover and QUIPU AI for a six-month programme offering mentorship, technical expertise and potential proof-of-concept opportunities.
Impact: The cohort provides selected startups with opportunities to test enterprise use cases and refine technology products in software engineering, AI security, workflow automation and data intelligence.
The six-month accelerator is designed to connect early-stage technology companies with technical expertise, mentorship and opportunities to explore potential proof-of-concept projects. Such projects allow businesses to test whether a technology can solve a practical problem before committing to a wider deployment.
Each selected startup will have opportunities to engage with NetApp teams and explore potential applications of its technology. Programme coverage also reports a grant of US$15,000 to support a potential proof-of-concept exploration. Participation does not, by itself, mean that a startup has secured a commercial contract or that its technology has been adopted by customers.
Five Startups and Their Technology Focus
Editorial Analysis
Why This Matters
The next stage of enterprise AI adoption depends on more than developing powerful models. Businesses also need secure software integrations, dependable data access, efficient workflows and safeguards that help prevent sensitive information from being mishandled. The five startups are targeting different parts of this challenge. Their technologies illustrate how the commercial AI ecosystem includes not only AI models themselves but also the software engineering, cybersecurity and data-management systems needed to use them. For India's technology sector, accelerator programmes can provide early-stage companies with opportunities to engage with larger businesses and understand enterprise requirements. However, the ultimate significance of this cohort will depend on whether the startups turn the programme's technical access and potential pilot projects into tested products, paying customers and sustainable businesses.
LightSprint AI is developing an AI-native software engineering platform designed to automate parts of the software development process using collaborative AI agents. Such systems aim to help development teams carry out tasks across coding and related engineering workflows, although the degree of automation and reliability depends on the product and use case.
Wald.ai focuses on data loss prevention for enterprise AI communications. Its approach uses contextual analysis to identify potentially sensitive information, addressing concerns about confidential business data being exposed through AI-powered tools.
Lasso Security develops cybersecurity solutions for generative AI applications, AI agents and large language models. As businesses introduce AI into their operations, security teams must consider risks such as inappropriate data access, unsafe integrations and weaknesses in the way AI applications interact with other systems.
Cogover is building a no-code and low-code workflow automation platform. These tools are designed to help organisations connect applications, information and business processes without requiring every workflow to be developed through conventional programming.
QUIPU AI focuses on enterprise knowledge intelligence, converting business information into contextual data that AI applications can use. The broader challenge in this field is enabling AI systems to retrieve relevant organisational information while maintaining appropriate access controls and data governance.
Although the five companies address different problems, their inclusion in the same cohort reflects a shared objective: helping organisations move beyond experimental AI demonstrations towards technologies that can be evaluated in real business settings.
Why Enterprise Testing Matters
A technology that performs well in a controlled demonstration may face different challenges when used inside a company. Enterprise systems must work with existing software, varying data formats, security policies and established business processes.
For AI products, the challenges can include inconsistent outputs, incorrect retrieval of information, exposure of sensitive data and difficulty integrating with older systems. Software engineering and workflow automation tools must also be evaluated for reliability, oversight requirements and the consequences of errors.
An accelerator programme can provide startups with access to technical feedback and opportunities to examine these practical issues. However, a proof of concept is generally an early validation step rather than evidence that a product is ready for large-scale commercial use.
For participating companies, the opportunity to work with an established technology provider may help clarify product requirements and identify possible enterprise applications. The commercial value will ultimately depend on technical performance, customer demand, security and the ability to deliver reliable solutions.
Women-Led Startups Also Included
Two companies in the new cohort, Cogover and QUIPU AI, are also part of ExcellerateHER, an initiative within the accelerator that supports women-founded and women-led technology ventures.
The initiative provides access to mentorship, technical expertise and enterprise opportunities. It forms part of a broader effort to expand participation in deep-tech entrepreneurship, where companies often need specialised technical support and substantial time to validate their products.
NetApp's programme history also provides context for the latest selection. The company reports that Excellerator, launched in 2017, has supported 90 startups across its earlier cohorts. Participating companies have collectively raised more than US$600 million, while the programme has facilitated proof-of-concept engagements and resulted in commercial contracts within NetApp.
These historical figures describe the programme's overall record and should not be interpreted as funding or guaranteed commercial outcomes for the five newly selected startups.
