60 Seconds. That's How Long Device Insurance Underwriting Just Took. Customer uploads invoice. AI extracts data. Risk assessed. Premium calculated. Policy generated. What normally takes hours happened in under a minute. Here's the workflow (see video below for details): Upload proof of purchase → AI validates documents → Assigns risk tier → Calculates pricing → Generates policy summary → Flags for human review if needed Why senior insurance leaders should care: Traditional underwriting drowns teams in manual data entry. This eliminates it. Your underwriters stop copying invoice numbers into spreadsheets. They start reviewing edge cases and building customer relationships. The deployment reality: Works in your local cloud (UAE compliant) Lives in your data center if needed Uses YOUR underwriting guidelines Maintains human oversight gates What changes: Faster processing time + Zero manual data extraction errors Same quality standards + Better customer experience What stays the same: Your risk appetite. Your pricing strategy. Your underwriter's final call on complex cases. The catch: This isn't future tech. It's deployable today. Most insurers just haven't asked the right questions yet. For insuring phones and laptops now. SME commercial lines and travel insurance next. Seen similar AI workflows transform your underwriting? What's holding your team back from testing these?
Most investment memos don’t fail because the thinking is wrong... ...they fail because every deal reaches IC with a different level of rigor, structure, and context. Some are deeply researched. Others are rushed. The result is time spent debating the memo instead of the investment. This Agentic AI workflow was built to fix that. It starts with three inputs only: the company name, available financials, and any pre-diligence material already in hand. From there, it automatically pulls external market context, reviews how the company presents itself publicly... ...and searches internal IC notes, prior memos, and comparable deals to anchor the analysis in institutional memory. The memo is written sequentially by four AI agents. 1) Business overview first. 2) Competitive positioning next. 3) Financial analysis after. 4) Executive summary last. The output is a familiar IC-ready memo, but with consistent structure and depth across every deal, making comparison easier and discussion more focused. Judgment stays human (we still want a review before it goes to print). Preparation of the memo becomes reliable. If IC conversations are drifting toward reconciling memos instead of debating decisions, this Agentic AI workflow helps reset the baseline.
