Manual consultant-to-project matching is a bottleneck that kills both recruiter productivity and deal velocity. A Nordic consulting firm was losing opportunities because evaluating candidate fit took days. They needed a way to screen, analyze, and rank consultants against incoming missions in minutes instead.
Problem
Consulting networks handle hundreds of inbound project requests monthly, but finding the right consultants for each mission was entirely manual. Recruiters spent days reviewing spreadsheets, cross-referencing consultant profiles, and manually scoring fit. The process was slow, inconsistent, and prone to error—and great consultants got missed while less-obvious matches were overlooked.
The firm needed to surface the best candidates instantly, with confidence scores and detailed analysis of why each consultant was or wasn't a good fit. They also needed the system to handle multi-tenant operations, email ingestion, and integration with their existing workflow.
Solution architecture
Multi-source data ingestion
The platform automates the mission intake pipeline. Outlook email inboxes are monitored continuously, missions are extracted from unstructured email text using LLM-powered parsing, and key details (scope, requirements, duration) are structured automatically. Each mission is converted to a vector embedding for semantic search.
Semantic matching with vector search
When a recruiter requests matching for a mission, the system runs a multi-stage ranking algorithm. Consultant profiles are embedded using the same vector model, then searched semantically against the mission. The top candidates are retrieved, scored on technical fit, availability, and requirement coverage (SKAL vs. BÖR), and ranked by composite score.
Real-time, reactive database
All data—consultants, missions, applications, matches—lives in a serverless real-time database. Changes propagate instantly to the frontend, enabling live match updates and background analysis without page refreshes.
Matching latency
<2 seconds
Candidate precision
92% fit accuracy
Manual screening reduction
85%
Time per match
30 seconds vs. 4 hours
AI-powered analysis
Each candidate is scored using a multi-dimensional scoring function: technical skill coverage, availability fit, seniority alignment, and bonus factors (past assignment success, manager rating). The AI agent analyzes each candidate's strengths and gaps, generating a brief written assessment of fit.
Insight
Requirement coverage tracking
The platform tracks SKAL (must-have) vs. BÖR (nice-to-have) requirement coverage per consultant, giving recruiters immediate visibility into coverage gaps and trade-offs.
Outcome
What previously took days of manual screening now happens in minutes. Recruiters can match a mission, review ranked candidates with analysis, and draft applications within 30 minutes. The platform has reduced no-match scenarios by 85% through proactive candidate suggestions, and improved application acceptance rates by surfacing more qualified consultants earlier in the cycle.
The firm now runs their entire consultant network through a unified system—reducing friction, improving match quality, and scaling their business without proportional headcount growth.
