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AIFF

Firefly Neuroscience, Inc.

AIFF

Firefly Neuroscience, Inc. NASDAQ
$1.73 2.98% (+0.05)

Market Cap $23.31 M
52w High $17.20
52w Low $1.45
Dividend Yield 0%
P/E -0.77
Volume 56.81K
Outstanding Shares 13.47M

Income Statement

Period Revenue Operating Expense Net Income Net Profit Margin Earnings Per Share EBITDA
Q3-2025 $388K $2.802M $-2.639M -680.155% $-0.2 $-2.403M
Q2-2025 $299K $1.908M $-1.833M -613.043% $-0.14 $-1.771M
Q1-2025 $43K $2.108M $-12.93M -30.07K% $-1.74 $-12.783M
Q4-2024 $53K $3.489M $-3.785M -7.142K% $-0.45 $-2.558M
Q3-2024 $33K $2.829M $-4.289M -12.997K% $-0.61 $-4.261M

Balance Statement

Period Cash & Short-term Total Assets Total Liabilities Total Equity
Q3-2025 $4.325M $12.407M $2.75M $9.657M
Q2-2025 $5.918M $14.938M $2.838M $12.1M
Q1-2025 $9.545M $12.363M $7.178M $5.185M
Q4-2024 $1.81M $4.601M $4.976M $-375K
Q3-2024 $1.23M $5.311M $2.535M $2.776M

Cash Flow Statement

Period Net Income Cash From Operations Cash From Investing Cash From Financing Net Change Free Cash Flow
Q3-2025 $-2.639M $-1.488M $-86K $-19K $-1.593M $-1.574M
Q2-2025 $-1.833M $-2.39M $-2.372M $1.135M $-3.627M $-2.402M
Q1-2025 $-12.93M $-2.511M $-7K $10.253M $7.735M $-2.518M
Q4-2024 $-3.785M $-1.218M $-76K $1.874M $580K $-1.298M
Q3-2024 $-4.289M $-2.519M $-89K $3.48M $872K $-2.683M

Five-Year Company Overview

Income Statement

Income Statement Firefly Neuroscience looks like a very early-stage, pre-commercial business from a financial perspective. Reported revenue is essentially non‑existent over the past several years, and the company is running at a loss, as you’d expect for a firm still building and validating its technology rather than selling at scale. The income statement suggests spending is going mainly into operating activities such as research, development, and overhead, with no meaningful gross profit yet. The widening loss per share in the most recent year points to heavier investment or higher costs as the company ramps up its platform and partnerships. Overall, this is a story of building future potential rather than current earnings. Financial performance today is weak by design, with the hope that commercialization of the technology eventually changes that picture.


Balance Sheet

Balance Sheet The balance sheet data provided is extremely limited and largely blank, which makes it hard to judge the company’s true financial strength, liquidity, or leverage. We do not see clear information on cash, total assets, or debt levels in the summary. Conceptually, a company at this stage often has a relatively light asset base, with value concentrated in intangible assets such as software, datasets, and intellectual property rather than factories or equipment. Funding typically comes from equity issuance or private capital rather than heavy borrowing. Given the lack of detail, any view on balance sheet health carries high uncertainty. The key unknowns are how much cash runway the company has and how dependent it may be on future capital raises to sustain operations and growth plans.


Cash Flow

Cash Flow The cash flow picture echoes the income statement: there is essentially no cash coming in from customers yet, and cash use is driven by operating expenses. Operating cash flow appears modestly negative, reflecting the cost of developing and supporting the BNA platform and broader organization. Capital spending looks very light in the data, which fits a software- and data-driven business that doesn’t need large physical investments. That said, low capital spending does not remove the need for cash; ongoing development, clinical work, and commercialization all require funding. In practical terms, the company is currently a cash consumer, not a cash generator. The central cash-flow question is how it will bridge the gap between today’s negative operating cash flow and any future stage where customer and partner payments could cover costs.


Competitive Edge

Competitive Edge Firefly’s competitive strength is almost entirely strategic and technological at this point, not financial. Its main asset is the BNA platform: an AI-powered system that interprets brain activity from EEG data to support diagnosis, treatment decisions, and drug development. The company’s proprietary brain-data repository is a major differentiator. This large, standardized EEG database is difficult for rivals to replicate quickly and becomes more valuable as it grows, giving Firefly a data advantage and a natural network effect: more users generate more data, which improves the models and makes the platform more attractive. Regulatory clearance for the platform and partnerships with well-known pharmaceutical and technology companies further strengthen its position. These relationships signal external validation and can help accelerate adoption. However, the neurotechnology and digital health space is competitive and rapidly evolving, so sustaining this lead will require continued execution and innovation.


Innovation and R&D

Innovation and R&D Innovation sits at the core of Firefly’s story. The BNA platform applies AI to both resting and task-based EEG data, aiming to turn complex brain signals into clear, actionable insights for clinicians and drug developers. This is a step beyond traditional, more subjective EEG interpretation. The company is pushing several notable initiatives: improved signal-cleaning technology (CLEAR), novel biomarkers such as “brain age” to detect early cognitive decline risk, and the long-term ambition of a foundation model for the human brain. Each of these, if validated and adopted, could broaden use cases and deepen the platform’s value. Firefly’s R&D is also leveraged by partnerships: collaborations with pharmaceutical firms, hardware makers, and AI infrastructure providers give it access to data, domain expertise, and computing power. The key uncertainty is how fast these innovations move from research and pilot programs into routine clinical and commercial use.


Summary

Firefly Neuroscience today is best described as a high-innovation, pre-revenue neurotechnology company. Its financials show almost no commercial activity and ongoing losses, consistent with a firm still in the build-and-validate phase rather than the scale-and-profit phase. On the positive side, the company appears to have meaningful intangible strengths: a unique and growing dataset, a differentiated AI platform with regulatory clearance, and partnerships with recognized players in pharma and technology. These elements together form a credible competitive moat in a specialized, data-hungry field. On the risk side, limited financial disclosure and a lack of operating revenue make the business heavily dependent on continued access to capital and successful commercialization. Execution risk is high: management must turn scientific and technical advantages into sustainable, repeatable revenue while navigating regulatory, clinical, and competitive challenges. Overall, AIFF looks like a classic early-stage, research-driven story in a promising but demanding niche. The company’s future will hinge less on current financial metrics and more on how effectively it can convert its innovation pipeline and partnerships into real-world adoption and, eventually, durable cash generation.