How Vectis Capital Runs Due Diligence 10× Faster With Research Swarms

Vectis Capital evaluates 200+ startups per quarter across Southeast Asia. Each due diligence cycle required 3 junior analysts spending 2–3 weeks gathering financial data, competitive landscapes, founder backgrounds, regulatory filings, and market sizing. The firm was bottlenecked: they could only deep-dive on 15 companies per quarter, missing time-sensitive deal flow. Annual analyst cost for research alone exceeded S$480K.

We deployed a multi-agent research swarm consisting of 6 specialized agents: (1) Company Profiler — pulls founding team backgrounds, funding history, cap tables from public and proprietary sources; (2) Market Sizer — gathers TAM/SAM/SOM estimates using industry reports and financial databases; (3) Competitive Intel — maps competitor landscape, pricing, positioning, and hiring signals; (4) Regulatory Scanner — checks compliance filings, patent records, and legal history; (5) Sentiment Analyzer — aggregates news, social media, Glassdoor, and customer reviews; (6) Report Synthesizer — compiles all findings into a branded 25-page investment memo with executive summary.

Week 1: Deep-dive into Vectis' existing DD checklist (147 data points across 8 categories). Week 2: Built and trained 6 specialist agents with domain-specific extraction rules and verification protocols. Week 3: Integrated with their Notion deal pipeline and Airtable tracking system. Week 4: Calibration — ran 10 parallel DD reports (AI vs. human) to validate accuracy. AI reports matched 94% of human findings and surfaced 12% more signals.