Hexure Launches Automated Document Error Correction

Not In Good Order (NIGO) submissions are a significant operational drag, with some estimates suggesting an average of 60% of life insurance and annuity applications are initially flagged as NIGO. Common errors include missing signatures, incorrect forms, and payment mistakes, all of which halt processing and require manual agent intervention. This creates costly delays for carriers and a poor customer experience. The workflow is an example of an agentic AI system, which moves beyond simple task automation to orchestrate complex, multi-step processes. Unlike traditional rules-based automation, agentic AI is goal-driven and can adapt to variability, analyzing documents, making decisions, and executing tasks with minimal human input. This architecture is key to managing the inherent unpredictability in document submissions. Under the hood, such systems often utilize a multi-agent architecture where specialized AI agents collaborate to handle a complex workflow. A coordinator agent might decompose the high-level goal of "correct NIGO document" into sub-tasks, dispatching them to other agents with specific tools, like a data extraction agent or a compliance validation agent. This modular approach allows for more robust and maintainable systems. Frameworks like LangChain and LlamaIndex provide the orchestration layer for these agentic workflows, offering tools to load and parse diverse document types (PDFs, Word docs), split them into manageable chunks for LLMs, and chain together sequences of operations. For document-heavy tasks, open-source OCR engines like Tesseract or more advanced tools like Surya can be integrated to handle initial text extraction from scanned images. The shift towards straight-through processing (STP) is a major driver for this technology, as insurers aim to automate the entire lifecycle of a policy or claim without manual touchpoints. While personal lines have seen STP rates over 75%, fewer than 10% of claims are processed straight through on average, highlighting the opportunity for automation in more complex areas. APIs are the critical connective tissue, allowing these new AI systems to interface with legacy core systems for policy administration and claims management. For technical founders, the agentic AI trend represents a significant opportunity, as the market moves from experimentation to execution. Venture capital is increasingly focused on vertical AI—models trained on domain-specific data for industries like insurance—and the infrastructure layers needed to deploy these agents reliably in production environments. As of Q2 2025, global insurtech funding saw a 16.7% decline to $1.09B, indicating investors are becoming more selective and prioritizing startups with clear efficiency gains.