What is Gigged.AI?
Gigged.AI provides an enterprise-focused solution for technology hiring, leveraging artificial intelligence. The platform operates through two main components: an Internal Talent Marketplace and an Open Talent Marketplace. The Internal Talent Marketplace is designed to map the skills within a company's existing workforce, facilitating internal resourcing before seeking external candidates. This approach aims to optimize contractor spending and enhance employee retention by promoting internal mobility.
For situations requiring external expertise, the Open Talent Marketplace connects businesses with a global network of contingent tech professionals. It assists users in creating detailed Statements of Work (SoW), supporting both outcome-based and time-and-material project structures. The platform utilizes AI to match project requirements with talent based on specific skills and availability, thereby reducing hiring risks and accelerating project timelines.
Features
- Internal Talent Marketplace: Captures internal workforce skills for internal resourcing.
- Open Talent Marketplace: Provides access to a global pool of contingent tech talent.
- AI-Powered Skills Matching: Matches projects with talent based on skills and availability.
- AI-Powered SoW Creator: Assists in creating outcome-based or time & material Statements of Work.
- Instant Project Alerts: Notifies talent of relevant new projects based on their skills.
- Compliance Management: Helps ensure work arrangements meet compliance standards.
- Project Management Tools: Allows management of deliverables and updates within the platform.
Use Cases
- Finding and hiring tech talent for specific projects.
- Improving internal employee mobility and retention.
- Managing contingent workforce and optimizing contractor spend.
- Resourcing projects internally before seeking external hires.
- Creating detailed Statements of Work for tech projects.
- Reducing hiring costs and time-to-hire for tech roles.
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Gigged.AI Uptime Monitor
Average Uptime
100%
Average Response Time
1124.38 ms
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