Learn how Qualcomm leveraged early SBIR funding to develop CDMA technology, transforming from a 7-person startup to a $180 billion telecommunications giant that powers billions of smartphones worldwide.

Discover how Genzyme parlayed a $62,000 SBIR grant into groundbreaking treatments for rare diseases, ultimately becoming a $20 billion acquisition and transforming medicine's approach to orphan diseases.

Learn how iRobot leveraged SBIR grants and defense contracts to evolve from building bomb disposal robots to creating the Roomba, pioneering the consumer robotics industry worth billions.

In 1996, two Stanford PhD students were working late into the night on a project that most people thought was a waste of time. The internet was growing exponentially, but finding anything useful on it was like searching for a needle in an ever-expanding haystack. Search engines of the day—AltaVista, Excite, Yahoo—returned results that were often irrelevant, spam-filled, or completely useless.Sergey Brin, a mathematics prodigy from Russia, and Larry Page, a computer engineering student from Michigan, had a radical idea: what if they could rank web pages not just by keywords, but by their importance—treating links as "votes" of credibility? This concept would become PageRank, the algorithm that powers Google. But without a crucial $4.5 million National Science Foundation (NSF) Digital Library Initiative grant, Google might never have existed.

Clean energy funding in 2025 presents both unprecedented opportunities and significant challenges. While the federal government cancelled $4 billion in clean energy grants in May 2025, $2.1 trillion in global energy transition investment reached record levels in 2024, creating a complex landscape where private foundations, state programs, and remaining federal opportunities offer billions in non-dilutive funding for clean energy companies.

The AI funding landscape has fundamentally shifted beyond venture capital, with over $2 billion in non-dilutive grant funding now available annually for machine learning startups. This represents a massive opportunity for founders to accelerate R&D without surrendering equity, particularly as traditional VC funding becomes more selective and AI development costs continue to rise. Government agencies, tech giants, and private foundations are investing unprecedented amounts in AI innovation, creating pathways for startups to secure substantial funding while retaining full ownership of their technology and vision.

Biotech startups face a unique challenge in early-stage development: long research timelines paired with high technical risk. These companies often work at the edge of what is scientifically possible, where traditional funding may be slow, limited, or unavailable. Government funding programs like SBIR exist to support this early, uncertain work. They allow small companies to test ideas, develop prototypes, and generate the data needed to move forward. This article explains how SBIR funding works within the biotech sector. It also outlines how this type of capital fits into the broader funding strategy for companies working on new therapeutics, diagnostics, and other life science innovations.

Many AI startups begin with a strong technical foundation and a clear vision, but funding that vision without giving up ownership can be difficult. Venture capital is one path, but it often requires founders to give away equity early—sometimes before the product is ready or the market is clear. Non-dilutive funding is an alternative. It provides capital without requiring founders to give up shares in the company. This is especially valuable for AI startups working on long-term research or regulatory-heavy applications, where early revenue may not be immediate. As non-dilutive funding sources—including federal grants, R&D tax credits, and innovation challenges—continue to expand in 2025, understanding this type of capital has become more important for AI companies looking to scale without altering ownership.

Each year, thousands of federal grant applications are submitted across industries ranging from healthcare to energy technology. Many are rejected—not because the projects lack merit, but because the applications contain preventable errors. Some of the most common mistakes are technical, such as missing a deadline or uploading the wrong attachment. Others are strategic, like proposing a project that doesn't align with the agency's priorities. This article outlines seven critical pitfalls that often prevent otherwise strong proposals from being competitive. Each section focuses on one specific issue and offers a clear explanation of how it can affect your application.

Deep tech companies often face long development timelines, high research costs, and significant technical risk. These challenges can make it difficult to rely on a single source of funding. Unlike consumer tech startups that may raise venture capital early and often, deep tech founders frequently turn to non-dilutive funding—capital that does not require giving up equity. Federal and state grants, for example, can support early-stage R&D or help validate a novel technology. However, most grants are limited in scope, duration, or budget. Relying on a single grant may leave critical gaps in funding, especially during transitions between research phases.This is where a multi-grant strategy becomes relevant.