# Risky Future Hosts AI Underwriting Demo Day > Source: > Published: 2026-07-07 05:00:17+00:00 # Risky Future Hosts AI Underwriting Demo Day Insurance Journal's **Risky Future** series is hosting a free "AI Tools for Underwriting" **Demo Day** on **Wednesday, July 8** at 1pm ET, according to Insurance Journal and Claims Journal. The event targets carriers, MGAs, specialty program leaders, underwriters and claims professionals, with six vendors, ABBYY, Nearmap, Cogitate, ZestyAI, Cotality and IntellectAI, each running 15-to-20-minute demos covering document AI, geospatial risk data, pricing guidance, submission triage and portfolio management. For practitioners evaluating underwriting AI tools, the session offers a fast, low-commitment way to compare vendor claims side by side, though a short scripted demo is a screening step, not a substitute for testing tools against real production data. The event is a useful gauge of where underwriting AI vendors are focusing effort this cycle: document extraction from messy submissions, geospatial property risk, and pricing and triage automation, rather than novel model architectures, reflecting where insurers still have the most manual friction to remove. ### What happened Insurance Journal's Risky Future series is hosting an "AI Tools for Underwriting" Demo Day on Wednesday, July 8, beginning at 1pm ET, free for insurance-organization attendees (Insurance Journal, Claims Journal). The session targets carriers, MGAs, specialty program leaders, underwriters and claims professionals. Six vendors are confirmed to present 15-to-20-minute sponsored demos: ABBYY (intelligent document processing and agentic automation), Nearmap (geospatial property intelligence and building-materials data), Cogitate (a cloud-native underwriting and policy platform with agentic orchestration), ZestyAI (property-level risk scoring for wildfire, storm and water peril plus regulatory-filing intelligence), Cotality (property-ecosystem data and workflow tools), and IntellectAI (embedded and generative AI for commercial and specialty underwriting). ### Industry context The lineup reflects where underwriting workflows still bottleneck: extracting structured risk data from unstructured submissions, layering geospatial and peril data onto property risk, and automating pricing and triage decisions. This is the latest in Risky Future's recurring Demo Day series, which runs roughly monthly across insurance niches including retail agents, MGAs, billing, cyber, and aerial/geospatial risk, per the event's own calendar. ### For practitioners Because presentations are sponsored and scripted, treat the demos as a fast way to shortlist vendors rather than as independent evaluation. Useful diligence questions to bring: what training data underlies each risk model and how often it updates, how uncertainty or confidence is reported, and whether the vendor offers a sandbox or API trial against your own submissions before committing to a pilot. ### What to watch Whether any of these six vendors show measurable adoption or case-study results at later Risky Future Demo Days this year, and whether insurers publish independent, non-vendor-reported performance data for document-AI or geospatial risk tools evaluated through this channel. ## Key Points - 1Risky Future's July 8 Demo Day features six vendors, ABBYY, Nearmap, Cogitate, ZestyAI, Cotality and IntellectAI, showing underwriting AI tools. - 2The vendor lineup targets document extraction, geospatial risk data, and pricing automation, the workflow steps insurers still handle manually. - 3Practitioners should treat sponsored demos as a vendor-shortlisting tool and still test finalists against their own production data. ## Scoring Rationale This is a routine vendor-sponsored trade-event announcement with genuine but narrow practitioner utility for insurance teams shortlisting underwriting AI tools. The score stays modest because the sourcing is mostly from the event organizer and trade publisher, and the event does not report a new model, benchmark, deployment result, or policy change. ## Sources Public references used for this report. Practice with real Ad Tech data 90 SQL & Python problems · 15 industry datasets [Active Search Campaigns by BudgetEasy](/problems/sql/active-search-campaigns-by-budget) [High CPC Clicks & Poor Landing PagesMedium](/problems/sql/high-cpc-clicks-poor-landing-page) [Campaign ROAS by Attribution ModelHard](/problems/sql/campaign-roas-by-attribution-model) 250 free problems · No credit card [See all Ad Tech problems](/problems/datasets/adtech)