Adlib's agentic intake accelerates claims intake and assessment by converting messy, multi-source claim packs into standardized, audit-ready documentation and structured data. Insurers reduce cost per claim, cut processing time, and improve accuracy across complex claims ecosystems.
Every step in Adlibʼs workflow is designed to deliver accuracy, compliance, and enterprise-ready data—ensuring your most critical documents become precise,auditable, and AI-ready.
Adlib centralizes claims documents from every channel into a single governed intake layer. All supporting content for a claim (forms, attachments, photos, reports) is captured, deduplicated, and associated to the right claim file, so adjusters aren’t chasing paperwork before they can even start the investigation.
Every step in Adlibʼs workflow is designed to deliver accuracy, compliance, and enterprise-ready data—ensuring your most critical documents become precise,auditable, and AI-ready.
Mixed formats are converted into consistent, searchable documents of record. Adlib normalizes PDFs, scans, images, office files, and multi-attachment email threads into unified, high-fidelity claim packs, making it easier for adjusters and examiners to review, compare, and share information, and eliminating formatting errors that can slow down processing or cause rework.
Every step in Adlibʼs workflow is designed to deliver accuracy, compliance, and enterprise-ready data—ensuring your most critical documents become precise,auditable, and AI-ready.
Adlib automatically pulls key data from claims documents; policy and claim numbers, parties, dates, loss details, amounts, and key indicators for fraud and coverage. This structured data flows into your claims and policy admin systems, supporting faster triage, straight-through or partial-through processing, and better fraud detection with less manual keying and fewer errors.
Every step in Adlibʼs workflow is designed to deliver accuracy, compliance, and enterprise-ready data—ensuring your most critical documents become precise,auditable, and AI-ready.
All claim-related documents are automatically assembled into complete, ordered claim files - FNOL, correspondence, evidentiary documents, expert reports, and payment approvals. Adlib keeps everything organized and easy to navigate, so claims teams and auditors can see the full story at a glance, reducing time spent hunting for the “right” document and speeding time to resolution.
Every step in Adlibʼs workflow is designed to deliver accuracy, compliance, and enterprise-ready data—ensuring your most critical documents become precise,auditable, and AI-ready.
Adlib validates that claims documentation and extracted data are complete, consistent, and aligned with regulatory and policy rules before they flow downstream. Accuracy and confidence signals flag missing or conflicting details, potential anomalies, and documentation gaps so only true exceptions are routed to specialists, reducing rework, supporting fraud detection, and helping you meet NAIC, ISO, and internal compliance standards.
Every step in Adlibʼs workflow is designed to deliver accuracy, compliance, and enterprise-ready data—ensuring your most critical documents become precise,auditable, and AI-ready.
Validated, organized claims files and structured data are delivered into your existing claims, policy admin, BI, and archive systems (Guidewire, Duck Creek, and beyond) using your current ecosystem as the system of record. Adlib helps move claims from intake to payout faster, with lower cost per claim, fewer errors, and fully audit-ready documentation that strengthens customer trust and regulatory outcomes.
Adlib connects to every system where unstructured data originates, including ECM/DMS, email, shared drives, line-of-business applications, and legacy repositories. It reads and standardizes content from any source, in any format, then scores and validates each document against your business rules with Adlib's Trust Score before handing it off. That validated, defensible output is what feeds the AI-enabled workflow orchestrators and automation systems running downstream, and it's why straight-through-processing rates go up: the systems doing the automating are finally working from data they don't have to double-check.
Whatever system the data comes from, and whatever system acts on it, Adlib sits in between. The Accuracy & Trust layer every workflow can rely on.
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How insurers can turn messy claim documents into trusted, AI-ready data, so automation actually works.
Turn unstructured insurance content into AI-ready, audit-ready pipelines that boost accuracy, STP, and compliance confidence.
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An executive guide to the architectural shift that determines whether your AI program reaches production, or quietly stalls between the demo and the audit.
Not directly. Adlib doesn't run fraud models itself. What it does is make sure your fraud and risk systems are working from clean, validated, structured data instead of messy source documents, which is usually where fraud-detection accuracy actually breaks down.
Adlib's intake runs continuously rather than on a batch schedule. Dcuments are classified, validated, and routed as they arrive, so a claim pack doesn't sit in a queue waiting for the next processing window.
Adlib's claims intake is built around the shared inboxes and multi-source document channels where claim packs actually arrive, including email attachments, scanned uploads, and portal submissions in whatever mix of formats a claim comes in.
The validated claim package is delivered into your claims management system, such as Guidewire, Duck Creek, OneShield, or Majesco, as structured, audit-ready data your adjusters or AI models can act on immediately, with no separate export or re-entry step.
It doesn't get silently pushed through. Documents that fail a business rule or come back with a low-confidence read are routed for human review rather than auto-approved, so exceptions get caught before they reach an adjuster or a downstream system.
OCR turns an image into text. Adlib's claims intake and validation goes further. It classifies what type of document arrived (FNOL, police report, repair estimate, adjuster note), extracts the relevant data, and checks that data against your business rules before anything moves forward. The output isn't just readable text, it's a validated, audit-ready record.
