Nova Recruiter

What is Nova Recruiter?

Nova Recruiter is an agentic talent sourcing platform designed to help recruiting teams find and reach out to candidates more efficiently. It searches across 800M+ public profiles, ranks results using Nova’s merit-based intelligence, and supports automated outreach across multiple channels.

The core purpose is to reduce the time spent on sourcing and follow-up while improving outreach effectiveness—shifting recruiter effort toward conversations that move hiring forward.

Key Features

• Search across 800M+ public profiles: Use natural-language search to find relevant candidates without manually scrolling through large lists.
• Merit-based ranking (not keyword ranking): Candidates are surfaced using Nova’s proprietary merit-based intelligence, aiming to prioritize talent fit beyond keyword matches.
• Automated multi-channel outreach: Run automated campaigns across Nova, Email, InMail, and LinkedIn with automated follow-ups and AI personalization.
• AI agents that handle the workflow: Agents automate sourcing steps including filtering, shortlisting, messaging, and replying so the process runs without constant manual intervention.
• Credit-based usage model tied to candidates contacted: Nova Recruiter uses a credit system based on the number of candidates you contact, with unlimited search and shortlists in paid plans (as stated on the page).
• Model Context Protocol (MCP) connectivity: Nova Recruiter can connect to an AI assistant via MCP so users can run searches and build shortlists from within their assistant workflow.

How to Use Nova Recruiter

1. Get started by trying Nova Recruiter (the page states “Try for free”) or booking a demo.
2. Search for candidates using natural language; Nova surfaces candidates from 800M+ public profiles and ranks them by merit-based intelligence.
3. Build shortlists from the results and use the platform to prepare outreach.
4. Launch automated campaigns with multi-channel outreach (LinkedIn, Email, InMail, and Nova), including automated follow-ups and AI personalization.
5. Optionally use MCP to run searches and shortlist-building from an AI assistant that supports Model Context Protocol.

Use Cases

• Filling a role while minimizing sourcing time: Recruiters can rely on AI agents to search, shortlist, message, and manage replies, reducing the hands-on effort per vacancy.
• Increasing candidate engagement from multi-channel outreach: Teams can set up campaigns across LinkedIn, Email, InMail, and Nova, with automated follow-ups and AI personalization to improve response rates.
• Early-stage hiring with A-player standards: Founders recruiting for high-caliber candidates can automate the sourcing and outreach steps and spend their time on interviews.
• Reducing manual follow-up and pipeline tracking: Hiring teams that previously tracked candidates in spreadsheets can shift outreach execution and reply handling to automated workflows.
• Running sourcing tasks inside an AI assistant: Users who prefer working through an AI assistant can use Nova Recruiter via MCP to perform searches and build shortlists without switching tools.

FAQ

• What data source does Nova Recruiter search? Nova Recruiter searches across 800M+ public profiles, as stated on the page.

• How does Nova Recruiter decide which candidates are most relevant? The platform ranks candidates using Nova’s merit-based intelligence rather than keyword-only matching.

• Which channels does Nova Recruiter support for outreach? The page lists automated multi-channel outreach across Nova, Email, InMail, and LinkedIn.

• How are credits/usage handled? Nova Recruiter uses a credit-based system tied to the number of candidates you contact through the platform. The page also states that search and shortlists are unlimited in all paid plans.

• Can Nova Recruiter be used with an AI assistant? Yes. The page states Nova Recruiter connects natively to an AI assistant via Model Context Protocol (MCP).

Alternatives

• Recruiting inbox + manual sourcing workflow: Traditional recruiting systems can manage messaging and tracking, but they typically require more manual searching, filtering, and follow-ups compared with agent-driven sourcing.
• Keyword-first sourcing tools: Tools focused on keyword or boolean searches may be faster to set up for narrow queries, but they may not provide the same merit-based ranking approach described for Nova Recruiter.
• General outreach automation platforms: Sales-style sequence tools can automate email and follow-ups, but they may not be purpose-built for recruiting workflows or candidate discovery across large profile databases.
• AI assistant-based research workflows (without dedicated recruiting features): Using a general AI assistant to research and draft outreach can reduce drafting time, but dedicated recruiting tools generally handle candidate search, shortlisting, and recruiting-focused outreach flows more directly.