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CI&T Inc (CINT) Fair Value & Analysis

Technology · US · Market cap $490M

Price$3.50
Fair Value$5.81
Upside+66.0%
Quality95/100
Evidence: High Range $4.35 – $7.26

Analysis

CI&T Inc (CINT) currently trades at $3.50, while our model-based Fair Value estimate is $5.81 — implying the stock looks roughly 66.0% 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: high) — always confirm before acting.

About the company

CI&T Inc., together with its subsidiaries, provides strategy, design, and software engineering services in North America, Europe, Latin America, Asia Pacific, and worldwide. It is also involved in the development of customizable software through the implementation of software solutions, including machine learning, artificial intelligence, data analytics, cloud migration, and mobility technologies. The company offers business and digital strategy, working closely with clients to understand strategic objectives, organizational constraints, and market dynamics; customer-centered experience and design, analyze customer and user journeys to design digital products, services, and platforms that improve efficiency, engagement, and satisfaction; and software engineering and platform delivery solutions, that designs, builds, modernizes, and operates digital platforms using agile, Lean, and DevOps practices. CI&T Inc. was founded in 1995 and is headquartered in Campinas, Brazil.

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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.