KiHire.
Agentic sourcing for small companies — jobs, candidates, matches.
Step 01 · of3
Enter job description
Sourcing for small companies is broken.
Mid-sized companies open three to five roles a year and have no in-house recruiter. LinkedIn Recruiter costs 9,000 € a year per seat — a volume that doesn’t justify the spend. External headhunters take 25 % of annual salary. Neither option matches the reality.
The result: roles stay open for weeks, applications fall through the cracks, hires happen through personal networks — with all the bias and bottlenecks that come with that.
Agents that search, read, decide — not just filter a list.
KiHire takes a job spec, lets a Claude agent extract the context (skills, seniority, industry), launches a sourcing agent that finds candidates, and scores each one with a match rationale. Outreach mails are personalised based on candidate experience.
Beta with first pilot customers. Per-match pricing, no seat model. Next phase: multi-user workspaces for recruiting teams, plus the Notion-to-Supabase migration onto a dedicated backend.
/ tech-decisions
Three decisions that mattered.
Agent Loop
Claude sub-agents per sourcing step
Instead of one long prompt chain: specialised agents for job analysis, profile search, match scoring, outreach drafting. Each agent has its own context window — better results on long job specs.
Data Layer
Notion → Supabase migration planned
Beta runs on Notion API as job and candidate database. Migration to Supabase is the pilot for replacing Notion across the SSV apps too (summer 2026).
Pricing
Per match, not per seat
Classical ATS tools bill per recruiter — punishes small companies with irregular hiring needs. KiHire bills per qualified match. Fair model for 1–10 hires per year.
/ other apps