Fairvalue-Calculator Fairvalue-Calculator
EN DE

Talkspace, Inc (TALK) Fair Value & Analysis

Healthcare · US · Market cap $871M

Price$5.20
Fair Value$0.7900
Upside-84.8%
Quality95/100
Evidence: Medium Range $0.6000 – $0.9900

Analysis

Talkspace, Inc (TALK) currently trades at $5.20, while our model-based Fair Value estimate is $0.7900 — implying the stock looks roughly 84.8% 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

Talkspace, Inc., together with its subsidiaries, operates as a virtual behavioral healthcare company that connects patients with licensed mental health providers in the United States. The company provides psychotherapy and psychiatry services to treat various mental health conditions, such as depression, anxiety, trauma, and other fields of human challenges by operating an online platform for one-on-one therapy delivered through messaging, audio, and video channels. It serves health insurance plans and employee assistance programs, direct-to-enterprise customers, and individual subscribers. The company was formerly known as Groop Internet Platform Inc. and changed its name to Talkspace, Inc. in June 2021. The company was founded in 2012 and is headquartered in New York, New York.

Open the full interactive analysis →

Similar stocks

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.