i3 Verticals, Inc (IIIV) Fair Value & Analysis
Technology · US · Market cap $554M
Fair value as of: Jun 24, 2026
Analysis
i3 Verticals, Inc (IIIV) currently trades at $19.94, while our model-based Fair Value estimate is $14.53 — implying the stock looks roughly 27.1% overvalued today. We read business quality at 80/100 (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: medium).
About the company
i3 Verticals, Inc. provides enterprise software and services solutions to public sector entities in the United States and Canada. The company offers digital solutions for dynamic processes to plan, coordinate, evaluate, record, and provide up to date information within court systems; E-Filing and revenue cycle management solutions for courts; solutions for computer aided dispatch, records management, evidence management, jail management, mobile solutions, and livescan; and software solutions for vehicle title and registration, driver's license and permit management, and motor carrier compliance for departments of transportation. It also provides digital customer engagement platform, comprising web, mobile, chat, and voice options; billing and back-office management software solutions and services; solutions for school lunch programs, including meal account management, point of sale, menu planning, nutritional analysis, food inventory and free, and reduced meal applications, as well …
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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.