omni:us

"No-Touch Claim Automation, Agentic Co-Pilot & Leakage Reduction" — AI that thinks, acts, and delivers like your best claims specialist, driving automation, better decisions, and measurable ROI from day one.

Where it wins

• 70% no-touch automation for P&C claims at a DACH Top 5 Insurer, eliminating backlogs during high-volume events like storms [1].
• 54% no-touch automation in global marine claims, outperforming human adjusters with 0% decision accuracy loss [1].
• 50% faster handling of complex claims via the Agentic Co-Pilot, allowing human adjusters to focus on high-value decisions [1].
• AI-Act-compliant, auditable, and bias-free models trained on 3M+ annotated claims and 80M+ insurance documents [1].

Credibility: Claims performance metrics (70%, 54%, 50%) and model training data (3M+ claims, 80M+ documents) are sourced directly from omnius.com, with specific customer testimonials from Allianz AT and unnamed DACH/EU top insurers [1].

• Insurance-Native AI: Sells pre-trained AI models on 3M+ claims and 80M+ documents, reducing time-to-value for insurers [1].
• Agentic Automation: Moves insurers from simple automation to "Agentic" workflows where AI acts autonomously on claims [1].
• Scalable Delivery: 21 reference processes for major P&C lines allow rapid deployment without heavy custom engineering [1].
• Profitability Focus: Revenue tied to measurable ROI: leakage reduction, efficiency gains, and combined ratio improvements [1].

• Legacy InsurTechs: Competitors offering basic automation, but lacking omni:us's agentic AI and 3M+ claim training data [1].
• General AI Providers: LLM vendors without insurance-specific models, lacking the 21 reference processes and domain expertise [1].
• In-House AI Teams: Insurers building internal AI, but facing longer deployment times and higher R&D costs compared to omni:us's weeks-to-value [1].
• Differentiators: omni:us wins on insurance-native AI, agentic automation, and proven ROI (70% no-touch, 54% marine) [1].
• Threats: New entrants with large general AI models may attempt to replicate insurance-specific workflows [1].

• Manual Claims Backlogs: Insurers struggle with processing delays during high-volume events like storms, causing customer dissatisfaction [1].
• Leakage and Subrogation Losses: Billions lost annually due to inefficiencies in subrogation and claims leakage [1].
• Slow Decision-Making: Human adjusters are bottlenecked by complex claims, delaying settlements and increasing costs [1].
• Regulatory Compliance: Pressure to ensure AI decisions are auditable, bias-free, and compliant with AI-Act [1].
• High Operational Costs: Traditional claims processing is expensive, eroding combined ratios and profitability [1].

omni:us's acquisition by adesso is a strategic wedge to embed AI directly into insurance core systems, bypassing legacy integrations. The main risk is over-reliance on a single acquirer's sales motion; if adesso's integration slows, omni:us's standalone growth may stall. The opportunity lies in expanding the Agentic Co-Pilot to other insurance lines beyond P&C and marine, leveraging the 21 reference processes. The next signal to watch is the deployment speed of custom models for EU Top 10 insurers; if they can consistently deploy in weeks, it validates the scalability of the agentic model.

omni:us should develop a self-service portal for mid-market insurers, lowering the barrier to entry beyond top-tier DACH/EU clients. Expand the Agentic Co-Pilot to include real-time customer communication, enhancing the end-to-end experience beyond internal adjuster efficiency. Publish more detailed case studies on leakage reduction ROI to attract CFOs and risk officers, not just CIOs. Leverage the Horizon2020 recognition to lead industry standards on AI-Act compliance, positioning omni:us as the trusted, auditable AI provider.