Inseego Corp (INSG) Fair Value & Analysis
Technology · US · Market cap $168M
Fair value as of: Jun 24, 2026
Analysis
Inseego Corp (INSG) currently trades at $10.25, while our model-based Fair Value estimate is $2.10 — implying the stock looks roughly 79.5% 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: high).
About the company
Inseego Corp. engages in the design and development of cloud-managed wireless wide area network (WAN) and intelligent edge solutions for businesses, consumers, and governments in the United Stated, Europe, and internationally. The company offers 5G and 4G mobile broadband solutions, such as mobile hotspots under the MiFi brand. It also provides fixed wireless access solutions, including indoor, outdoor, and industrial routers and gateways. In addition, the company provides cloud management solutions, as well as wireless subscriber lifecycle management solutions. Further, the company offers Inseego Subscribe, a wireless subscriber management solution for carrier's servicing of their government and complex enterprise customer. It serves transportation companies, industrial companies, governmental agencies, manufacturers, mobile operators, system integrators, distributors, and enterprises. Inseego Corp. was founded in 1996 and is based in San Diego, California.
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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.