Applications per hire in early 2026, against about 100 in early 2021, per Ashby’s 2026 Talent Trends report.
Of recruitment firms say AI cut their screening time by half or more, per Bullhorn’s GRID 2026 report.
US staffing sales in 2025, per the American Staffing Association.
Where AI Pays Back in Recruiting
Artificial intelligence in recruiting pays back fastest in the hours recruiters spend searching, screening and writing. Application volumes keep climbing, past candidates sit unused in the ATS, and submittals and client updates get written by hand. Candidate and client data is personal and often confidential, so the AI that reads it runs inside the firm. We build custom AI for these workflows and deploy it privately, on your servers or in your own cloud account, connected to Bullhorn, Loxo, Recruit CRM or Greenhouse.
AI Recruiting Software on Your ATS
Search your own candidate database in plain language, match candidates with a model trained on your placements, and draft submittals, all on self-hosted models connected to your ATS.
AI Recruiting Agents
Agents rediscover past candidates, research longlists and run follow-ups and scheduling, with a recruiter approving the steps you choose.
AI Screening Calls
First-round phone screens on a self-hosted voice stack, with answers and a summary written to the ATS for the recruiter to review.
Executive Search AI
Market maps, longlists, candidate reports and assessment summaries on private models, with access walled by mandate.
Matching Models and Resume Parsing
Matching models trained on your placement history, plus parsing that turns CVs into clean ATS records, built by our machine learning team.
Private Search Across Your Documents
Chat over client agreements, rate cards, policies and past proposals, with every answer citing the source document.
Who We Build For
Staffing Agencies
- Rediscovery of past candidates for every new job order
- Matching against open jobs, trained on your placement history
- Follow-ups and scheduling at volume, logged to the ATS
Recruiting and RPO Firms
- Screening calls and summaries for high-volume roles
- Submittal and client update drafts in your format
- Client-ready pipeline reports drafted from ATS data
Executive Search Firms
- Market maps and target-company lists
- Longlists from years of past mandates
- Candidate reports in house style, on private models
Leadership Advisory and Assessment Practices
- Assessment interview and 360 feedback summaries
- Coaching notes kept in their own access group
- Succession planning research packs
Private by Design
Recruiting data is personal data: CVs, compensation, references, interview notes and, in executive search, confidential mandates. Every system we build runs where that data already lives. You choose one of three deployment options: on-premise servers, a self-hosted deployment in your own AWS, Azure or GCP account, or a dedicated tenant we provision in the region you choose.
The models run where the data does: open-weight LLMs served with vLLM, with self-hosted embeddings and a vector index beside them. Access follows your ATS roles and SSO groups, and every query, score and draft is logged with the user and the sources used.
Those logs support the rules that apply to hiring AI. NYC Local Law 144 requires an independent bias audit within one year before an automated employment decision tool is used, a published summary of the results and candidate notice at least 10 business days before use, per the NYC Department of Consumer and Worker Protection. Colorado’s SB 26-189 adds notice and explanation duties from January 1, 2027, and Quebec’s private-sector privacy act requires telling a person when a decision is based exclusively on automated processing. Your counsel sets the policy, and the system records what an audit needs.
Where We Focus
Our recruiting AI work sits beside your recruiters: tools that search, draft, summarise and schedule, with a person making every hiring decision. A recruiter reviews every shortlist, a consultant signs every candidate report, and candidates can always reach a person.
We build the private AI layer that connects to the ATS or search system you already run, and we hand over the models, the code and the documentation, so the capability belongs to your firm.
How an Engagement Runs
Three stages, each with a decision point, so you expand only what your recruiters already use. Book a strategy session to scope the first stage.
The three stages
- Data review: ATS fields, document types and access rules mapped before any build
- Pilot on one desk or one workflow, scored by your recruiters against past roles
- Rollout across desks, offices and clients, with monitoring and audit reporting
Frequently Asked Questions on AI for Recruiting
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Ready to scope AI for your recruiting desk?
Bring one desk or one workflow to a strategy session, and we will map the first AI build worth adding to your ATS.