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Ouster, Inc (OUST) Fair Value & Analysis

Technology · US · Market cap $3.0B

Price$45.16
Fair Value$12.33
Upside-72.7%
Quality95/100
Evidence: Low Range $9.25 – $15.41

Analysis

Ouster, Inc (OUST) currently trades at $45.16, while our model-based Fair Value estimate is $12.33 — implying the stock looks roughly 72.7% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).

About the company

Ouster, Inc. engages in the production and sale of lidar sensor kits for the automotive, industrial, robotics, and smart infrastructure industries in the Americas, the Asia-Pacific, Europe, the Middle East, and Africa. The company offers the Outer Sensor (OS) product line, including OSDome that provides a hemispheric field of view; OS0 for wide view; OS1, for mid-range view; and OS2 for long-range view. It also provides the DF series, a suite of short, mid, and long-range solid-state digital lidar sensors for advanced driver assistance systems (ADAS) and autonomous driving systems; Velodyne that offers surround-view lidar sensors comprising VLP-16, VLP-16 Lite, VLP-16 Hi-Res, VLP-32, and VLS-128; Ouster Gemini, a perception platform designed for smart infrastructure deployments; and BlueCity, a Gemini-powered solution for traffic operations, planning, and safety. In addition, the company offers ZED, a high-performance camera that provides 2D and 3D color data, as well as AI Compute.…

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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.