Build, Orchestrate, and Optimize Insurance Operations in One Platform

Bernoly helps insurance companies and brokers, who struggle with inaccurate risk evaluation, manual underwriting processes, and unpredictable loss ratios, achieve precise, data driven risk decisions and sustainable profitability. Unlike legacy core systems or single purpose automation tools, we deliver an AI powered platform, real time risk analytics, and seamless human AI collaboration , enabling insurers to minimize financial loss, optimize pricing, and stay competitive in a fast changing market.

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Four Module Cards

Bernoly is built for the complexity of insurance. It combines four connected modules that let insurers design experiences, manage data, and apply analytics with transparency and control.

Experience Flow

The Experience Flow is the heart of our platform, allowing your teams—not developers—to design and deploy every customer touchpoint. From a simple quote request to a multi-step claim submission, you create the logic, define the steps, and launch the bespoke digital experience instantly. This flow is precisely what your customers see, ensuring a guided, compliant, and branded journey for policy purchase, renewals, FNOL, and service tasks.

Key Capabilities:

  • No-Code Builder: Visually define complex business logic and pathways.
  • Omnichannel Delivery: Deploy the same flow across web, mobile, and customer portals.
  • Dynamic Personalization: Adjust the experience based on customer data and product rules.

Analytics Flow

The Analytics Flow transforms raw transactional data into a powerful decision engine for your business. This dedicated environment gives your analysts the power to instantly measure the performance of every deployed Experience Flow. Gain deep visibility into conversion rates, abandonment points, and task efficiencies. Crucially, the Analytics Flow enables advanced capabilities like real-time anomaly detection, accurate performance prediction, and data-driven underwriting insights to proactively manage risk.

Key Capabilities:

  • Real-Time Performance Dashboards: Instantly track flow conversion and customer friction points.
  • Anomaly Detection: Automatically flag suspicious claims or unusual process deviations.
  • Predictive Modeling: Forecast product demand, lapse rates, and claims frequency.

Human - AI Collaboration

Our platform operates on a philosophy of Human-AI Collaboration, ensuring optimal efficiency without sacrificing quality or compliance. Tasks are managed by an Intelligent AI Agent trained on your specific prompts and rules, allowing it to automate routine inquiries and process steps. When the AI encounters complexity, ambiguity, or a defined high-risk scenario, the task is immediately and seamlessly escalated via Human-in-the-Loop intervention. This tight, real-time collaboration ensures maximum Straight-Through Processing (STP) while keeping a human expert ready for high-value judgment.

Key Capabilities:

  • Intelligent Escalation: Automatic handoff from AI to human agents when confidence thresholds are met.
  • AI-Assisted Agents: Human operators receive pre-summarized data and next-best-action guidance from the AI.
  • Continuous Learning: Every human intervention trains and refines the AI models.

Data Atlas

The Data Atlas provides a single, transparent, and logical view of all data assets within the platform. This is your command center for understanding where data lives, how it is structured, and how it is connected. By presenting a full data schema, including all tables, fields, and crucial relationships (e.g., 1:1, 1:many), it ensures that all teams are working from a consistent, governed, and accurate source of truth. The Data Atlas is the foundational component that enables sophisticated analytics and seamless integration across your enterprise.

Key Capabilities:

  • Visual Data Schema: Transparent overview of all data entities and their relational integrity.
  • Data Lineage & Governance: Maintain consistency and compliance with a clear understanding of data origins.
  • Database Overview: High-level summary of all stored data assets and their key metadata.

AI in Insurance: Case Studies and Insights

AI strategy for ChatGPT 12.0
To be published on 1 December 2025
How personalized experiences can drive loss ratios?
To be published on 15 November 2025
Why Tsetlin machines could be the future of insurance modeling?
To be published on 15 December 2025
WhatsApp in Insurance: how can it make an impact?
Policy support in your pocket.
Opportunity in conversational engagement for insurers
Turning chats into customer connections.