Weave Communications, Inc (WEAV) Fair Value & Analysis
Healthcare · US · Market cap $440M
Fair value as of: Jun 25, 2026
Analysis
Weave Communications, Inc (WEAV) currently trades at $5.43, while our model-based Fair Value estimate is $3.11 — implying the stock looks roughly 42.7% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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: medium).
About the company
Weave Communications, Inc. operates an AI-powered patient communications, engagement, and payments platform for small and medium-sized healthcare businesses. It offers AI-receptionist; Unified Phone Number; Customized Phone System, a smarter phone system to identify whether incoming calls are from new or current patients, provide information at every call, and manage heavy call times; Softphones to make and receive calls from anywhere with an internet connection; Text Messaging and SMS response assistant; Missed Call Text that allows practices to respond when a call is missed; Missed Text Auto-Reply that replies to patient text messages by automatically responding to messages received outside of a practice's normal operating hours; Team Chat, a group messaging solution; and Weave Mobile App. It also provides Weave Reviews and Respond Assistant to request, collect, monitor, and respond to reviews; Weave Email Marketing and Email Assistant to create professional emails; Text Connect t…
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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.