Overview
Scrums.com uses AI at multiple stages of the talent lifecycle — from initial screening through to ongoing performance tracking — to ensure clients receive the best possible match, as quickly as possible.
Stage 1: Candidate Assessment
When engineers apply to join the Scrums.com network, they go through a structured assessment process that includes:
- Technical skills tests — Role-specific coding challenges and architecture exercises
- Communication evaluation — Written and verbal English assessment
- Behavioural assessment — Structured interview scoring against Scrums.com’s delivery culture criteria
- Reference validation — Background and professional reference checks
AI tools are used to score technical assessments, identify skill gaps, and calibrate candidates to the correct seniority band (Junior, Mid, Senior, Lead).
Stage 2: Client Matching
When a client request comes in, the matching engine evaluates the active talent pool against your specific requirements. It weights:
- Stack match — How closely the candidate’s technical profile aligns with your requirements
- Availability — Current utilisation and notice period
- Delivery model experience — History with Scrum, Kanban, or the client’s preferred process
- Client history — Prior successful placements in similar industries or tech environments
The output is a ranked shortlist, reviewed and curated by your Enablement Partner before being shared.
Once deployed, SEOP tracks performance data across all engineers:
- Story points completed vs. committed
- PR cycle time and review participation
- Defect rates and code quality scores
- Sprint ceremony attendance and engagement
Anomalies are flagged automatically for review. This data informs proactive intervention — coaching, workload adjustment, or replacement — before issues affect delivery.Last modified on March 12, 2026
