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NSF Artificial Intelligence Topic (SBIR) is sponsored by National Science Foundation (NSF). NSF Artificial Intelligence Topic (SBIR) is sponsored by National Science Foundation (NSF). Directly targets AI innovations including federated learning approaches for distributed data in civic tech and infrastructure applications.
Official opportunity description and requirements excerpt:
Artificial Intelligence Grant – Apply Today | NSF SBIR An official website of the United States government. Check recent critical alerts! (Last updated 12/22/2025) NSF has temporarily paused the submission of new Project Pitches to the SBIR/STTR programs due to the lapse in congressional authorization. Program Directors will continue to process Project Pitches that were previously received. Please direct any questions to sbir@nsf.gov . Proposal Review & Decision Artificial Intelligence (AI) bioMASON Inc interior and exterior façade tile made with biocement, which is less costly and more sustainable than its traditional counterpart Artificial Intelligence (AI) The Artificial Intelligence topic focuses on cutting-edge technologies in the field of deep learning-based AI systems and AI-based hardware. The recent successes in computer vision, machine translation, natural-language processing and speech recognition have led to widespread use of learning-based systems in production and an unprecedented growth in AI systems that interact frequently with and/or on behalf of humans in highly personalized contexts. This topic especially emphasizes next-generation AI technologies that are not only safe and reliable but also fair, robust against sophisticated adversaries, privacy preserving, and efficient in terms of computational resources, energy, training data size, etc. It also includes cutting-edge hardware technologies needed for sustainable AI (i.e., novel devices and architectures to support the tremendous processing power needed by AI technologies), edge devices (i.e., intelligent systems on a chip for applications such as voice assistants) and AI technologies that lead to better hardware systems. These subtopics are only meant to serve as examples. All proposals that are focused on developing a new high-risk technical innovation and that have significant potential commercial and societal impact are welcome to apply, regardless of subtopic. AI1. Cognitive Science-based Technologies AI2. Computer Vision Based AI Technologies AI3. Conversational AI Technologies AI4. Language-Based AI Technologies AI5. Novel AI Hardware Technologies (e.g. Neuromorphic Computing, High-performance Technologies for AI, Smart and Secure Edge Devices, etc.) AI6. Sustainable AI Technologies for Low Resource Environments AI7. Technologies for Trustworthy AI (safe, fair, transparent, privacy-preserving, explainable, and/or secure) AI8. Other Novel Technologies Application process for Artificial Intelligence (AI) funding Eligibility for Artificial Intelligence (AI) funding + Your company must be a small business (fewer than 500 employees) located in the United States. At least 50% of your company’s equity must be owned by U.S. citizens or permanent residents. NSF does not fund companies that are majority-owned by multiple venture capital firms, private equity firms, or hedge funds, to participate in SBIR and STTR. All funded work, including work done by consultants and contractors, needs to
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Artificial Intelligence Grant – Apply Today | NSF SBIR An official website of the United States government. Check recent critical alerts! (Last updated 12/22/2025) NSF has temporarily paused the submission of new Project Pitches to the SBIR/STTR programs due to the lapse in congressional authorization.
Program Directors will continue to process Project Pitches that were previously received. Please direct any questions to sbir@nsf. gov .
Proposal Review & Decision Artificial Intelligence (AI) bioMASON Inc interior and exterior façade tile made with biocement, which is less costly and more sustainable than its traditional counterpart Artificial Intelligence (AI) The Artificial Intelligence topic focuses on cutting-edge technologies in the field of deep learning-based AI systems and AI-based hardware.
The recent successes in computer vision, machine translation, natural-language processing and speech recognition have led to widespread use of learning-based systems in production and an unprecedented growth in AI systems that interact frequently with and/or on behalf of humans in highly personalized contexts.
This topic especially emphasizes next-generation AI technologies that are not only safe and reliable but also fair, robust against sophisticated adversaries, privacy preserving, and efficient in terms of computational resources, energy, training data size, etc. It also includes cutting-edge hardware technologies needed for sustainable AI (i. e.
, novel devices and architectures to support the tremendous processing power needed by AI technologies), edge devices (i. e. , intelligent systems on a chip for applications such as voice assistants) and AI technologies that lead to better hardware systems.
These subtopics are only meant to serve as examples. All proposals that are focused on developing a new high-risk technical innovation and that have significant potential commercial and societal impact are welcome to apply, regardless of subtopic. AI1.
Cognitive Science-based Technologies AI2. Computer Vision Based AI Technologies AI3. Conversational AI Technologies AI4.
Based on current listing details, eligibility includes: For-profit small businesses (<500 employees) Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $275,000 (Phase I) Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Application snapshot: target deadline rolling deadlines or periodic funding windows; published funding information $275,000 (Phase I); eligibility guidance For-profit small businesses (<500 employees)
Use the official notice and source links for final requirements, attachment checklists, allowable costs, and submission instructions before applying.
Language-Based AI Technologies AI5. Novel AI Hardware Technologies (e. g.
Neuromorphic Computing, High-performance Technologies for AI, Smart and Secure Edge Devices, etc.) AI6. Sustainable AI Technologies for Low Resource Environments AI7.
Technologies for Trustworthy AI (safe, fair, transparent, privacy-preserving, explainable, and/or secure) AI8. Other Novel Technologies Application process for Artificial Intelligence (AI) funding Eligibility for Artificial Intelligence (AI) funding + Your company must be a small business (fewer than 500 employees) located in the United States. At least 50% of your company’s equity must be owned by U.
S. citizens or permanent residents. NSF does not fund companies that are majority-owned by multiple venture capital firms, private equity firms, or hedge funds, to participate in SBIR and STTR.
All funded work, including work done by consultants and contractors, needs to take place in the United States. The project’s principal investigator (tech lead) must be legally employed at least 20 hours a week by the company seeking funding. The principal investigator doesn’t need any advanced degrees.
The principal investigator needs to commit to at least one month (173 hours) of work on a funded project per six months of project duration. Evaluation Criteria: What We Look for When Evaluating Artificial Intelligence (AI) proposals + Read more about our criteria Take our project assessment to see if your work might be a good fit for NSF funding.
Voice biomarkers identify mental health challenges Kintsugi Mindful Wellness is using artificial intelligence to develop voice biomarker software to measure, predict, and scale access to mental healthcare. To learn more visit: https://www. kintsugihealth.
com AI helps medical professionals interpret, perform ultrasounds Caption Health (formerly known as Bay Labs) uses artificial intelligence to help medical professionals perform and interpret ultrasounds. To learn more visit: https://captionhealth. com/ Improving surgical outcomes with machine learning KelaHealth combines a patient’s data and machine learning to reduce surgical risks.
Its platform reduces surgical complications by using patient data and predictive algorithms to create “tailored risk profiles” for patients before surgery. To learn more visit: https://www. kelahealth.
com/ Kintsugi Mindful Wellness, Inc. We invest up to $2 million in seed funding and take zero equity. We’re looking for companies that are transformative, high-risk, have a market pull, and are scaleable.
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