About Amy by Jellyfish
Amy is an AI sourcing employee built by Jellyfish, a team co-founded by Symion John. The tool ingests a client brief and searches across LinkedIn, GitHub, Google Scholar, and the broader web for potential candidates. It writes and sends personalized outreach messages, handles follow-ups and routine replies, then passes interested, qualified candidates to a human recruiter.
Review
Amy positions itself as an AI sourcer that works the way a human recruiter does-interpreting requirements, finding people who don't necessarily match a checklist, and explaining why they fit. The system runs on ChatGPT by OpenAI and uses Trigger.dev for workflow orchestration. It's a narrow, task-specific agent built for recruiting agencies that want to automate the top-of-funnel sourcing work without removing human judgment from the final decision.
Key Features
- Ingests client briefs and learns what a recruiter looks for, using that recruiter's own judgment signals rather than static keyword matching.
- Searches across LinkedIn, GitHub, Google Scholar, and other web sources to surface candidates who may not tick standard criteria boxes.
- Generates explanations for why each surfaced candidate fits the role, based on the brief and the recruiter's past patterns.
- Sends personalized outreach messages, follows up automatically, and processes routine candidate replies.
- Hands off only candidates who are interested and qualified, leaving the recruiter to handle relationship-building and closing.
Pricing and Value
Amy launched with a "Free" tag on its Product Hunt listing. The reference content does not specify a pricing model, tiers, or timeline for paid plans. As of this writing, the exact pricing structure is not yet defined publicly. Interested teams should contact Jellyfish directly for current access terms and any future pricing details.
Pros
- Operates across multiple platforms (LinkedIn, GitHub, Google Scholar) in one workflow, which reduces the need for manual cross-platform searches.
- Handles the full outreach cycle-initial message, follow-ups, and reply handling-without requiring a recruiter to monitor inboxes.
- Uses the individual recruiter's past decisions as training signals, so the tool adapts to what a specific agency values in candidates.
- Frees recruiters from repetitive sourcing tasks, letting them spend more time on client relationships and closing candidates.
Cons
- Cannot assess culture fit or make the intuitive leaps a human recruiter makes when taking a chance on an unconventional candidate-those decisions remain entirely with the human.
- The team acknowledges the system won't catch every hidden talent, and some strong candidates who don't match learned patterns may still be overlooked.
- Not well suited for teams that prefer full manual control over sourcing and outreach or that distrust AI-mediated candidate communication.
Amy fits recruiting agencies that already have a defined sourcing process and want to offload the repetitive parts-searching, initial outreach, and reply triage-to an AI agent. It's less appropriate for boutique firms where every candidate interaction is highly bespoke or for recruiters who believe sourcing decisions shouldn't involve a language model at any stage. The tool's effectiveness will depend heavily on how well it learns from an individual recruiter's judgment over time.
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