AI recruiting agents that source and screen — without the slop.
Custom AI agents for recruiting and talent ops — sourcing, screening, outreach, scheduling, candidate updates. Wired into your ATS, calendar, and email.
Generic AI recruiting tools optimize for volume, not quality.
The generic version: scrape LinkedIn, generic outreach, hope something sticks. Candidates feel spammed, response rates fall, your employer brand erodes.
The off-the-shelf vendors (Findem, hireEZ + AI, Paradox) are useful but rigid — locked into their data model, their messaging templates, and their ATS integrations. If you have non-standard roles or a specific candidate experience you want to protect, the limits show up fast.
Recruiting agents that read like a senior recruiter.
We build recruiting agents that source against the specific signals that predict fit for your roles (relevant projects, tech stack, scale of impact, location, comp band), draft personalized outreach grounded in the candidate's actual work, screen via async questions, and schedule first interviews — while feeding everything cleanly into your ATS.
Your recruiters stop drowning in sourcing and screening. They spend their time on the interviews and the candidate experience.
The shape of capabilities we build into agents for this use case. Yours may need a subset; we scope in discovery.
Role-fit sourcing
Search LinkedIn, GitHub, Behance, AngelList against role-specific signals (not just keywords). Score candidates on real fit.
Profile enrichment
Pull project history, technical signals, content (GitHub repos, blog posts, talks), career trajectory. Synthesize into a recruiter-ready profile.
Personalized outreach
Outreach grounded in the candidate's actual work, not generic. Sent from your recruiters' inboxes, reviewed before send (or auto-sent above a confidence bar).
Async screening
Initial screen via async questions (text or video). AI summarizes responses, flags answers worth a human follow-up.
Interview scheduling
Time-zone-aware calendar negotiation with candidates. Reschedules handled gracefully. Reminders sent.
Candidate updates
Status updates to candidates after each stage. Honest, prompt, and consistent — protecting your employer brand.
ATS sync
Greenhouse, Lever, Ashby, Workday, custom ATS. Candidates, statuses, and notes flow in cleanly.
DEI signal protection
Configure what the agent considers and ignores. Audit logs to support EEOC compliance reviews.
Pipeline analytics
Sourced → contacted → engaged → screen → onsite → offer. Real conversion data per role and per recruiter.
How the agent ships.
Same structure for every agent build. Predictable timelines, fixed scope.
- 01
Discover
1 week. Real workflow, real data, what 'good' looks like. We pick what the agent owns and what humans keep.
- 02
Architect
1 week. Tool inventory, model choice, memory strategy, escalation rules, eval criteria — written and reviewed.
- 03
Build MVP
2–3 weeks. Working agent handles the happy path against real data. Observability and human-review UI from day one.
- 04
Harden
2–4 weeks. Edge cases, evals, monitoring, training, gradual rollout. Production-ready.
- 05
Run
Optional retainer. Model upgrades, prompt tuning, new tools, scope expansions.
The architecture you'd be getting.
It's the opposite when done well. Generic templates and slow follow-ups feel impersonal. An agent that mentions a candidate's actual project, responds promptly, and updates them honestly at each stage feels more personal than most human recruiters can manage at scale.
Greenhouse, Lever, Ashby, Workday, Recruitee, Polymer, custom ATSs. Via APIs or MCP servers. Candidates, statuses, attachments, notes — all synced.
Configurable. You decide what the agent considers in fit scoring and what it ignores (e.g., names, photos, schools). Audit logs of every scoring decision support EEOC reviews. Some clients use the agent to actively counter human bias by anonymizing reviews.
Yes — the architecture is the same. Sourcing signals differ per role (LinkedIn projects for product, content + cases for marketing, deal history for sales). We tune signals per role family in setup.
We design with data minimization: only fetch what's needed for screening, configurable retention windows, delete-on-request workflows. GDPR-ready when configured for it.
Want a recruiting agent for your team?
Tell us the workflow, the volume, and the systems involved. We'll come back with what we'd build, how it would handle the edge cases, and a fixed quote.