Beamr Imaging Ltd (BMR) Fair Value & Analysis
Technology · US · Market cap $25.8M
Fair value as of: Jun 25, 2026
Analysis
Beamr Imaging Ltd (BMR) currently trades at $1.41, while our model-based Fair Value estimate is $1.61 — implying the stock looks roughly 14.2% undervalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Beamr Imaging Ltd. engages in the content-adaptive video compression business in the United States, Israel, and internationally. The company offers a suite of video compression software encoder solutions, including Beamr 4 H.264, Beamr 4X H.264 content adaptive, Beamr 5 HEVC, and Beamr 5X HEVC content adaptive encoders; Beamr JPEGmini photo optimization software solutions for reducing joint photographic experts group file sizes; and Beamr Cloud, a cloud-based Beamr HW-accelerated content adaptive encoding SaaS solution. It also provides NVENC-CABR in the form of SDK integration, FFMPEG plugin, and Gstreamr plugin on the cloud service. The company serves tier one over-the-top content distributors, video streaming platforms, and Hollywood studios. The company was formerly known as I.C.V.T Ltd. and changed its name to Beamr Imaging Ltd. in January 2015. Beamr Imaging Ltd. was incorporated in 2009 and is headquartered in Herzliya, Israel.
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.