PH Deck

Welders and related professionals struggle to find comprehensive and up-to-date salary data based on state, experience level, and specialty, relying on fragmented sources like job boards or anecdotal information which lack granularity and accuracy.

Users need to manually search and filter through H1B LCA filings for salary and employer trends data, leading to time-consuming research, outdated information, and limited insights.

Founders frequently ask, "What should I be paying myself?" but struggle to find solid data on salary ranges, averages, and distributions, making financial planning and competitiveness in the market challenging.

Users manually decide who pays in group settings, leading to arguments and inefficiency.

Users manage data products manually without a centralized system, leading to inconsistent data quality and fragmented access across organizations.

Users are at risk of data theft, leaks, and unauthorized access with the current solution.

Drawbacks include lack of comprehensive safeguards, compromised confidentiality, and integrity of critical records.

Restaurant and retail merchants face high processing fees and rely on outdated POS systems lacking modern integrations (e.g., pay-at-table, real-time insights), leading to operational inefficiencies and reduced profit margins.

Job seekers often apply to positions without clear salary information, leading to mismatched expectations and wasted time. No CV upload required streamlines the process but existing platforms lack upfront salary data, causing unmet salary expectations and inefficiency.

Data professionals manually decipher corporate data jargon and unclear terms during meetings and documentation, leading to a time-consuming and error-prone process that causes miscommunication and frustration.

Users need to manually generate random data like names and color palettes for design, testing, or prototyping, which is time-consuming and lacks diversity.