DeepSearch

Company profile:

Startup name: DeepSearch

Tagline: Find possible people matches by name

Elevator Pitch: DeepSearch helps people start a people search with a name and review possible profile matches. Limited candidate-list previews are available without login; full reports require payment.

Namesakes and incomplete records can lead to mistakes, so users should verify important details against original sources. This pitch is submitted by the product team.

Target Market: Individuals researching possible people matches

How will you make money?: Limited candidate previews are free; full reports are paid.

How much capital have you raised?: null

Website: https://deepsearch.tools/

City/Country: null

AI-assisted summary:

DeepSearch is a subscription service that lets users begin with a person’s name, optionally add a city or company, and review matching profiles plus available public-facing background, location, social, and contact information in a single report. (Source: https://deepsearch.tools/)

The product matters because it is positioned as a simpler front end for a familiar but sensitive data-broker category: people-search services that compile information from multiple sources into paid reports. (Source: https://deepsearch.tools/about) (Source: https://consumer.ftc.gov/articles/what-know-about-people-search-sites-sell-your-information)

Problem and target users

DeepSearch targets individuals who have limited starting information and want to identify a person, reconnect with an old friend or colleague, locate a public social profile, or inspect the information associated with their own name. (Source: https://deepsearch.tools/) (Source: https://deepsearch.tools/about)

The underlying challenge is entity matching: a name alone often maps to several people, while fragmented online profiles, locations, usernames, and work histories make it difficult to determine which records refer to the same individual. (Source: https://deepsearch.tools/about)

DeepSearch explicitly positions the service for lawful personal research and verification, and its terms prohibit using reports for employment, housing, credit, insurance, or other regulated eligibility decisions. (Source: https://deepsearch.tools/terms)

That boundary is important: the Federal Trade Commission notes that people-search sites are a type of data broker, while information compiled for employment, housing, credit, insurance, or similar eligibility decisions can trigger Fair Credit Reporting Act obligations. (Source: https://consumer.ftc.gov/articles/what-know-about-people-search-sites-sell-your-information) (Source: https://www.ftc.gov/business-guidance/resources/what-employment-background-screening-companies-need-know-about-fair-credit-reporting-act)

Product and solution

The workflow is straightforward: users submit a name, add a city or employer when helpful, select the likely person from candidate matches, and open a report containing whatever fields are available. (Source: https://deepsearch.tools/about)

According to DeepSearch, reports can include names, locations, social profiles and usernames, work and education, and available phone numbers or email addresses; availability varies by person, platform, and country. (Source: https://deepsearch.tools/about)

The company says it does not access private social accounts, private messages, or live locations, and warns that a matching name does not establish identity. (Source: https://deepsearch.tools/about)

DeepSearch says it relies on third-party profile and enrichment services, identifying Harvest for profile discovery, People Data Labs for enrichment, and EnrichLayer for additional contact information when needed. (Source: https://deepsearch.tools/privacy)

Its own disclosures also acknowledge a core product limitation: results can be incomplete, outdated, incorrectly matched, or unavailable, so the service is best understood as a research aid rather than authoritative identity verification. (Source: https://deepsearch.tools/about) (Source: https://deepsearch.tools/terms)

Business model, pricing signals, and traction

DeepSearch uses a recurring subscription model with weekly, monthly, quarterly, and annual plans priced at $6.99, $18.99, $38.99, and $49.99 respectively. (Source: https://deepsearch.tools/terms)

The published plan catalogue assigns separate allowances for searches and report unlocks, ranging from 45 searches and nine reports on the weekly plan to 385 searches and 77 reports on the annual plan. (Source: https://deepsearch.tools/terms)

Subscriptions renew automatically unless cancelled, while full reports require a plan after users review available search access and pricing. (Source: https://deepsearch.tools/) (Source: https://deepsearch.tools/terms)

The publicly available materials reviewed for this overview describe the product and pricing but do not provide verifiable customer, revenue, funding, or growth figures. (Source: https://deepsearch.tools/) (Source: https://deepsearch.tools/about)

Expert take

DeepSearch’s positioning is clear: reduce the friction of piecing together scattered public-person data for everyday consumer use. Its strongest product decision is also its biggest operating challenge—presenting useful, affordable results while making uncertainty, privacy controls, data provenance, and prohibited use cases impossible to overlook.

For founders and investors, the key unknowns are data quality, acquisition economics, retention after an initial search need, and whether correction-and-removal processes can scale credibly in a category where mistaken matches and privacy expectations are central risks.

Note: Information based on publicly available sources at the time of writing, and summarized by AI.