Client-brief translation
Turn calls, job descriptions, and hiring-manager tradeoffs into an actionable search strategy with must-have and flexible requirements.
Jellyfish
Jellyfish is AI recruiting software for staffing agencies. Its AI talent sourcer, Amy, turns client requirements into evidence-based searches, candidate outreach, reply management, and recruiter or hiring-manager updates.
AI talent sourcing for staffing agencies
Jellyfish is AI recruiting software for staffing agencies. Its AI talent sourcer, Amy, handles the operational workflow between a client brief and a qualified candidate conversation: translating requirements into a search, researching talent, explaining matches, conducting outreach, managing replies, and coordinating updates.
The product is designed for searches where job titles and conventional profile databases do not fully describe the required experience. Amy can look for evidence in technical work, research, open-source contributions, communities, portfolios, talks, patents, and other public career signals, then connect that evidence back to the client’s requirements. Recruiters can use a more autonomous workflow or retain approval over candidates, messages, and updates.
Core features
Evidence-based talent discovery
Research technical work and experience across GitHub, Google Scholar, open-source projects, technical communities, and the open web.
Candidate qualification
Assess candidates against the actual brief and explain matches with role-specific evidence, such as technical depth, scale, leadership, or current intent.
Personalized outreach
Create personalized engagement sequences, including email, LinkedIn connection and follow-up steps, and InMail, with review points where needed.
Inbox and reply management
Read candidate replies, answer routine questions, summarize responses, route strong candidates to the right recruiter, and keep next steps visible.
Recruiter and client coordination
Keep client context attached to candidate decisions and provide progress, evidence, and hiring-manager updates as the search develops.
Practical use cases
Launching a new agency search
Convert a hiring-manager conversation or job description into explicit must-haves, flexible criteria, and a search plan that retains the original client context.
Sourcing beyond job titles
Find technically qualified people whose relevant work is hidden behind broad titles such as Software Engineer or Product Engineer, using evidence of integrations, deployments, customer work, or other concrete outcomes.
Managing candidate outreach at scale
Run a repeatable engagement sequence, answer routine candidate questions, and surface interested or qualified replies so recruiters can focus on conversations requiring judgment.
Maintaining client and team alignment
Keep match evidence, candidate decisions, follow-ups, and progress updates connected when several recruiters or hiring stakeholders are involved in a search.
Combining automation with review
Use approval checkpoints for candidates, messages, or updates when a team wants AI to perform the routine work while recruiters retain control over consequential decisions.
Pros and Cons
Pros
- Connects client requirements to search criteria, candidate evidence, outreach, and follow-up in one workflow.
- Looks beyond job titles and conventional databases across technical and research sources.
- Provides explanations for candidate matches instead of presenting fit scores without context.
- Supports human review as well as more autonomous sourcing, engagement, and coordination.
- Handles routine inbox work and keeps recruiters and hiring managers aligned on progress.
Cons
- The available product material does not document pricing, integrations, onboarding requirements, or platform limitations.
- The described sourcing approach emphasizes technical and public-web evidence; coverage and accuracy may vary by role and by the amount of public information available.
- The product is positioned for staffing agencies, so its fit for internal recruiting teams or non-technical searches is not established by the available material.
FAQ
What is Jellyfish?
Jellyfish is AI recruiting software for staffing agencies. Its AI talent sourcer, Amy, converts client requirements into a search plan, researches candidates, evaluates evidence, runs outreach, manages replies, and keeps hiring teams updated.
How does Amy find candidates?
Amy searches beyond conventional profile databases, including GitHub, Google Scholar, open-source projects, technical communities, and the open web. It looks for evidence of relevant work rather than relying only on job titles or keywords.
Can recruiters review or approve Amy’s work?
The workflow can run with different levels of human involvement. Teams can let Amy source, engage, follow up, and coordinate, or require approval for candidates, messages, and client updates. The brief, rules, and autonomy level can be changed as the work progresses.
What does Amy produce?
Amy produces candidate matches with role-specific supporting evidence, personalized outreach, handled or summarized replies, qualified-candidate handoffs, and progress updates for recruiters or hiring managers.
Quick Facts
- Category
- AI recruiting and talent sourcing software
- Primary users
- Staffing agencies and recruiters
- AI agent
- Amy, an AI talent sourcer
- Workflow
- Client brief to qualified candidate reply
- Research sources
- GitHub, Google Scholar, open-source projects, communities, and the open web
- Pricing
- Not available on the reviewed pricing page
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