https://open-gpt.app/ VS Sortinghat

Sortinghat's answer:

Sorting Hat is an ATS and CRM built exclusively for staffing, search and RPO firms, not a general hiring tool adapted for agencies. Three things set it apart. First, AI is native to the workflow rather than added on: AI voice screening calls, AI video interviews, natural language search across the firm's own database, and notes that write themselves onto the record. Second, migration off Bullhorn, Ceipal, Recruit CRM or Recruiterflow is handled with no data loss, including comments and attachments. Third, implementation, customisation and hands-on adoption support are included, because buying AI is easy and getting recruiters to actually use it is the part most firms fail at.

Sortinghat's answer:

Legacy platforms were built as systems of record. Recruiters still do the sourcing, chasing and screening by hand, and spend 60 to 70 percent of the week on admin. Sorting Hat absorbs that work, so the same headcount carries roughly twice the roles. It also sources from the firm's own database before spending on job portals, which cuts portal spend by around 40 percent. Front and back office sit in one system, including pay and bill, timesheets and invoicing, so contract desks do not need a second tool. Data is hosted in the client's own country, with SOC 2 and ISO 27001 in progress. Migration and training are part of the deal, not a paid add-on.

Sortinghat's answer:

Scalene Works Peoplefy Scrabble Codersbrain Jigsaw Interned Atlass Partners

Sortinghat's answer:

Staffing, recruitment, executive search, RPO and GCC management firms, from teams of ten recruiters to firms of 400+ employees. It fits both niche search desks and high volume hiring desks, and works for firms running contingency, retained or contract models. Typical buyers are founders, delivery heads and operations leaders who are either running a legacy ATS they have outgrown, or have bought AI tools their recruiters never adopted

Sortinghat's answer:

Apoorv Tamrakar started a talent search firm at 18 and scaled it to a 15 member team. Running that desk made the problem obvious: recruiters spent most of their week on chasing, screening and data entry, none of which is the part clients pay for, and every tool on the market was built to store records rather than do the work. Sorting Hat was built from that experience, as the platform he wanted while running an agency. The team now works with staffing firms globally, and one early finding shaped the product: after auditing 3M candidate records at a single firm, around 10 percent were duplicates and 10 percent unusable, meaning firms keep paying job portals for profiles they already own.

Sortinghat's answer:

I don't know your actual stack, so fill this one in yourself rather than let me guess. It usually wants front end, back end, database, hosting and AI layer. Send me the list and I will write it up to match the tone of the rest.