In insurance, documents are the foundation—ACORD forms, inspection reports, loss runs, and policy PDFs flood systems daily. But manual handling slows everything down. Errors creep in. Time is wasted on data entry instead of decision-making, causing delays in policy issuance, claims processing, and overall service delivery.
InsurDocIQ, our AI-powered solution built on HTC MAiGE, changes that. It captures, understands, and transforms unstructured inputs into structured, validated data ready for core ingestion. Seamlessly integrating with systems like Guidewire and Duck Creek, InsurDocIQ automates document intake across the policy lifecycle—from new business and underwriting to servicing and claims. The result? Greater speed, accuracy, and clarity across every touchpoint—from policy to payout.
Simplify and standardize document intake from every channel and format.
Design and deploy the necessary infrastructure and modern data solutions to apply product thinking to datasets that can be served to various users within and outside of your enterprise. At the same time, ensure discoverability, security, explorability, understandability, and trustworthiness.
Unlock reliable, accurate data extraction backed by deep learning and insurance-aware schema validation.
Automate the end-to-end flow from document capture to policy and claims ingestion with plug-and-play integrations.
Built for scalability, visibility, and compliance across all Lines of Business.
Deliver operational excellence with intuitive interfaces, real-time insights, enterprise-grade service orchestration.
Complementing InsurDocIQ—and available as a modular offering within it—HTC’s AI-enabled iFNOL platform simplifies the first notice of loss (FNOL) process for auto insurers.
Acting both as a standalone, cloud-ready solution and as an integrated extension of InsurDocIQ, iFNOL is designed to reduce costs and elevate customer satisfaction. It captures FNOLs from any format—emails, images, voice inputs, or chatbots—and auto-fills them in real time, even with minimal input.
Rapidly deployable and fully integration-ready, it also leverages telematics to enable services such as roadside assistance and towing. For fast, intelligent handling of routine claims, iFNOL sets a new benchmark in FNOL automation.
Digital transformation is a monument built atop strong, modern data management. In the era of expanding the ‘datasphere’ and overwhelming amounts of dark data, stitching together the right pieces of information in real-time is the competitive edge.
Podcasts
AI integration presents a range of challenges for businesses, from compatibility with legacy systems to ensuring ethical practices and overcoming scalability issues.
AI has permeated every part of our lives, evolving from recognizing patterns to achieving human efficiency. Treading deeper into the AI landscape, generative AI (GenAI) has become the new normal, reshaping every industry.
All industry use cases and market predictions point in the direction of AI-driven contact centers — as the next strategic step for boosting agent productivity, supercharging customer experience, and increasing operational efficiency.
Generative AI (GenAI) has expanded the horizons of innovation and challenged us to rethink the potential of workflows, efficiency, and intelligence.
In the past year, Generative AI (GenAI) has emerged as one of the most remarkable breakthroughs, triggering a transformative wave across the global economic and IT landscape.
In this age and probably in the next century, artificial intelligence (AI) will be the cornerstone for futuristic enterprises seeking to make an impact.
In the dynamic landscape of artificial intelligence, Large Language Models (LLMs) stand as formidable entities, capable of processing vast amounts of information and making decisions that impact users.
The pressure is on. Every enterprise needs to be an AI-first organization. Yet, building formidable AI capabilities presents its own unique set of challenges.
Enterprises are no strangers to disruptions, with uncertainty lurking around every corner. In this dynamic environment, adaptability and resilience aren’t just admirable qualities but essential for business survival.
The advent of Generative AI models had a significant impact across industries – but most importantly, it accelerated the mainstream adoption of automation, thus enhancing speed and productivity.
Case Studies
We prevented more than 80% of wrong supplier codes in its first iteration, enabling a global automobile company to optimize its production with AI and ML-led solutions.
Case Studies
We helped a large public research university in California build AI/ML-driven solutions for managing technical data.
Case Studies
We enabled a multinational mass media and entertainment conglomerate enhance its interactive training modules with a VR-based 360° solution.
Case Studies
We enabled a 70% reduction in the turnaround time for auto claims, helping the insurer reimagine claims intake with an AI-based FNOL solution.
AI has been envisioned as a business multiplier for decades, but its adoption has only recently gained pace.
The retail industry is rapidly adopting Machine Learning, Computer Vision AI, and smarter AI-led solutions to enhance customer experiences, drive supply chain optimization, smarter in-store operations, and more. Generative AI, however, can help them achieve more.
Generative AI models and similar architectures are known for their impressive and versatile features. These models have revolutionized natural language understanding and generation.
AI-powered solutions are helping businesses gain deeper insights to make data-driven decisions with enhanced precision.
Talk to our domain experts to understand the best Enterprise AI use cases for your business.
Talk to our domain experts to understand the best use cases of Enterprise AI for your business.
© Copyright 2025 HTC Global Services. All Right Reserved
© Copyright 2023 HTC Global Services. All rights reserved
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