We’re inviting companies in batches to ensure a high-quality, white-glove experience.
Want early access? Drop your email below and we’ll be in touch!
The power behind Candidate Search AI comes from more than just natural language input — it’s a vertically integrated AI engine built specifically for recruiters. Each step is engineered for speed, relevance, and precision.
How it works
We start by deeply parsing resumes and profiles from your ATS. Our parser is designed for recruiting data — extracting structured insights on roles, skills, locations, seniority, responsibilities, and career trajectories, even from poorly formatted documents or image-based resumes.
Built in-house for control, accuracy, and speed
Handles messy, unstructured resumes at scale
Parses job descriptions to better align candidate-job fit
Once parsed, candidate content is mapped into a rich profile schema. We unify metadata across resumes and ATS records — including custom fields, tags, engagement history, and recruiter notes.
Normalizes job titles, skills, and seniority levels
Adds temporal sequencing and engagement signals
Standardizes diverse inputs into a consistent, searchable format
Candidate profiles and search queries are translated into vector embeddings using powerful LLM-based models trained on talent-specific data. This allows us to understand recruiter intent beyond keywords — identifying relevant candidates who may not have used the exact same terms.
Enables semantic understanding of skills, experience, and role fit
Supports fuzzy, multilingual, and intent-aware searches
Adds contextual depth to every query and match
After vectorization, we search across millions of profiles in seconds — combining semantic relevance with traditional text matching to produce the most meaningful results.
Hybrid ranking: combines deep vector search with text scoring for precision
Fast response times, even across massive datasets
Learns from every search and user action to improve over time
We continuously refine the engine based on real-world use — optimizing results for accuracy, recall, and recruiter satisfaction.
Role-specific tuning for high-volume job categories
Continuous A/B testing on anonymized data
Feedback loops personalize and improve ranking logic
Resume data is sensitive. Our system is built with trust and compliance at its core — ensuring enterprise-grade data integrity and explainability.
End-to-end encryption at rest and in transit
Role-based permissions and detailed audit logs
No customer data used to train third-party models
Clear explanations for every result build confidence and transparency
We'll do it for you! You’ll get a dedicated Slack channel with us and white glove onboarding for success.
AI-First
Security first
Easy migration
Unlimited Storage
Engineered for scale
24/7 free support
Their support fuels our innovation, growth, and mission to redefine how business teams communicate.
We’re inviting companies in batches to ensure a high-quality, white-glove experience.
Want early access? Drop your email below and we’ll be in touch!
FAQ
Everything you need to know about the platform and how it works.
Candidate Search AI uses natural language processing and semantic search to understand recruiter intent — not just match keywords. It captures context (e.g. seniority, tech stacks, location, industry experience) and returns results based on meaning, not just word overlap. That means you get relevant candidates, not just resumes that happen to contain the right words.
Yes. We integrate with 80+ ATS platforms. Onboarding is as simple as a 1-click sync — no lengthy migration, no downtime. Within minutes, your entire candidate database becomes searchable through our AI interface.
We never train external models on your data. All enrichment, learning, and optimization happens privately within your environment. Data is encrypted at rest and in transit, and candidates can even self-update profiles securely via our portal to ensure accuracy.
That’s exactly what Candidate Search AI is built for. Our engine includes resume parsing, data normalization, enrichment from public sources (like LinkedIn), and optional candidate self-updates via a candidate portal — so your data becomes structured, fresh, and searchable, even if it wasn’t before.
