AI-Augmented Tendering & Recruitment Operations
A specialist recruitment consultancy partnered with ELab to break their dependency on one senior person for tender writing. In a focused 4-day sprint, we delivered a functional AI tendering solution and successfully submitted a live tender. The engagement set a target of enabling 80% of tender completion by non-expert staff, with subsequent recruitment automation proposals projecting $41,000-$55,000 NZD in Year 1 returns.
Industry: Recruitment / Executive Search | Duration: 4+ months | Region: New Zealand
The consultancy had built a strong reputation through high-quality tender submissions, but the entire tendering process depended on one senior person. This created a capacity ceiling on how many opportunities the business could pursue, and a critical business continuity risk.
On the recruitment operations side, the team faced a database of 150,000 candidate profiles with fewer than 5% tagged with relevant skills, making searches inefficient. And 30-40% of job applications were from offshore candidates not eligible for NZ-based positions, creating a manual processing burden.
What We Did
AI Tendering Sprint
We delivered a functional AI tendering MVP in a focused 4-day sprint, combining solution development with hands-on knowledge transfer. The approach uses a two-stage prompting methodology: first for response structure, then for content refinement. A live tender was successfully drafted and submitted during the sprint.
Knowledge Base & Process Design
We identified that AI tendering quality depends fundamentally on the quality of the underlying knowledge base. The follow-on work focused on building a structured repository of model answers and methodologies, categorised by government and private sector.
Recruitment Automation (Proposed)
We scoped AI-powered solutions for offshore candidate identification (automated screening based on phone number analysis) and skills tagging (AI-driven CV parsing against the client's taxonomy for 75,000+ onshore candidates).
Results
| Metric | Result |
|---|---|
| Tendering MVP delivery | 4 days from concept to submitted tender |
| Live tenders submitted using AI | 1 during sprint |
| Non-expert tender completion target | 80% of tender by non-expert staff |
| Projected Year 1 return (recruitment automation) | $41,000-$55,000 NZD |
The sprint-based delivery model proved the value of focused AI investment with rapid returns. The roadmap includes integrating the tendering AI with CRM for pipeline tracking, AI-assisted candidate matching using enriched skills data, and automated market intelligence reporting.
