ai.r Recruit
AI Search

AI Search for recruiting, built for relevance & scale

We instantly recommend candidates for a job or jobs for a candidate using proprietary match technology, not keywords, not agentic prompts. Get better recommendations, fast at scale, directly in your ATS or job board.

Semantic search
AI reasoning
Real-time
Explainable
  • No keyword hacks — semantic, structured & signal-aware
  • No naive agentic/LLM loops — deterministic, cost-predictable
  • Built for volume — sub-second retrieval over millions of profiles
  • Explained results — skills, titles, tenure, recency, constraints
Outcome → relevant shortlists, zero "keyword matches", fewer false positives
Relevance-first

Understands skills, seniority signals, tenure, recency & context — not just words.

Scale-ready

Indexes millions of profiles & jobs with low-latency retrieval and stable costs.

Explainable

Each hit includes reasons — e.g., skills overlap, title proximity, recency, location.

From raw text to relevant results

Simple 4-step process that delivers intelligent search results in real-time.

Step 1
Connect your platform

ATS/job board or API. We handle credentials & secure sync.

Step 2
Process your data

We parse & enrich your candidate database and jobs; optional anonymisation.

Step 3
Implement surfacing

We wire where results appear: job view, candidate view, search pages, webhooks.

Step 4
Get better search

Real-time recommendations appear directly in your product UI.

Need external sources? We support custom connectors for third-party databases, with dedupe & consent-aware blending.

Why this beats keywords & naive LLM search
  • Keywords miss synonyms, seniority and context; we model skill graphs & signals.
  • Agentic/LLM search loops are slow and costly at volume; our retrieval is deterministic & scalable.
  • We explain results — factors & reasons — so teams can trust recommendations.
Inside the engine
Structured features
Parsed & normalised signals: skills, titles, tenure, education, recency, location.
Semantic vectors
Domain-tuned embeddings for candidate–job similarity.
Hybrid ranking
Blend vectors + structured constraints for high precision.
Latency & scale
Distributed index; sub-second retrieval for millions of docs.
Integration & surfacing
ATS / Job board

Work with your APIs & webhooks; we never break your workflows.

Surfacing points

Job page → Recommended candidates. Candidate page → Recommended jobs.

Custom sources

Blend your DB with third-party sources. Dedupe, consent & policy-aware.

Typical rollout: connect → process database → wire surfacing → validate results with your team.

FAQs
Why not just use keyword search?

Keywords can't model skills, seniority, tenure, recency or adjacency. We combine semantic vectors with structured features for precision.

Do you use LLMs?

We use LLMs where they add value (e.g., summaries), but not for high-latency retrieval loops. Search itself is deterministic and cost-predictable.

How fast is it?

Designed for sub-second recommendations at multi-million document scale, depending on load and filters.

Where do results appear?

Inside your ATS/job board — typically on job and candidate pages, and in search results via components or notes.

Can you include third-party databases?

Yes. We offer custom connectors and dedupe across sources to keep only relevant, consent-compliant profiles.

Ready for relevance at scale?

Switch off keyword search. Ship AI Search that finds the right people — fast — inside your ATS or job board.

Semantic searchGDPR compliantEnterprise SLA