Case study
REC Intelligence recruitment intelligence platform
A multi-tenant AI recruitment intelligence, sourcing, ATS and CRM platform that turns a staffing agency's live job data into sourcing, market and business development intelligence.
Category
AI Platform, ATS & CRM
Industry
Staffing & Recruitment
Solution
VMS & ATS Integration
The brief
Agencies publish everything a market intelligence engine needs, their live vacancies, yet none of it is read back to them. Recruiters worked across five or six disconnected tools: a job board, a CV database, a contact data tool, a spreadsheet for business development, an ATS and an email client. The result was slow sourcing, generic adverts, unqualified BD activity and no measurable link between spend and placements.
What we delivered
- AI recruiting assistant with natural language and voice input, inline candidate cards and anti-fabrication guardrails
- Candidate search, match, lists and persona research with bulk contact reveal and open-to-work detection
- Outreach intelligence generating five-touch email sequences, LinkedIn messages, SMS templates and phone scripts
- Job analysis scoring any advert out of 100 and rewriting it in one click, typically from 25 to 82
- Job intelligence builder with salary suggestions, resume-to-job matching and 40+ mapped job boards for media strategy
- Geo analysis heat maps, market supply and demand ratios, salary benchmarks and demand forecasting
- Business development lead discovery, client dossiers and deterministic opportunity scoring
- Native ATS with publish-to-website feeds, application intake API and AI resume parsing
- Native CRM with multi-job deals, weighted forecasting, lead trust scoring and email campaign builder
- Credit-based usage metering, analytics, RBAC, audit logging and a super-admin tenant console
- Integrations across Bullhorn, Recruiterflow, Apollo.io, ContactOut, Perplexity, Mapbox, SendGrid, Resend and Stripe
Engineering highlights
- 1
Feed-first architecture: the platform ingests XML, gzipped feeds, website exports, Bullhorn or Recruiterflow, or provides a native ATS, with AI detecting and mapping feed structure so onboarding takes minutes.
- 2
AI as an assistant, not an oracle: every output is grounded in the client's own data and live research, with deterministic scoring where consistency matters and a multi-model fallback chain so no single provider outage takes the product down.
- 3
Multi-tenancy and security from day one: organisation-level isolation at the database layer with row-level security, security-definer functions, per-endpoint rate limiting and strict token validation.
- 4
Sector-agnostic configuration: sector, keywords, job boards, geography and currency are configuration, so the same codebase serves construction staffing in the US, hospitality in South Africa and technology recruitment in the UK.
Technical stack
- Front end
- React, TypeScript, Vite, Tailwind CSS, shadcn/ui, Tiptap, Recharts
- Mapping
- Mapbox GL with custom heat map and drill-down layers
- Backend
- Serverless Postgres platform with 65+ tables and row-level security
- Serverless logic
- 80+ purpose-built functions for sourcing, enrichment, scoring, parsing, billing and cron workers
- AI
- Multi-model gateway with automatic fallback, plus live web research
- Scheduling
- Background workers for feed caching, alerting, campaign sending and health checks
- Billing
- Stripe subscriptions, seat management, invoices and webhook reconciliation
- SendGrid for campaigns, Resend for transactional and system mail
- Scale
- Async job queue with skip-locked workers and stale-while-revalidate caching
ROI model
Five measurable levers: sourcing cost per candidate, recruiter time recovered, advert performance, media spend efficiency and revenue generated from live hiring signals.
Two or three per-seat sourcing and contact data subscriptions consolidated into one credit pool
5 to 7 hours per recruiter per week returned to selling and placing, roughly 15% of billable capacity
Weak adverts scoring 20 to 40 rebuilt into benchmarked adverts scoring 80+, lifting applications per posting
10 to 20% of job board budget reallocated to channels that actually produce placements
Qualified pipeline of companies hiring right now, with named decision-makers and weighted revenue forecasting
Inside the platform






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