# Beyond the Backlog: AI for submissions, claims and onboarding backlogs

> Kognitos + Indium webinar: how neurosymbolic AI fixes the three backlog hotspots in insurance — submissions/underwriting, claims registration, and agent onboarding — without black-box risk.

**Page**: https://www.kognitos.com/videos/beyond-the-backlog-how-ai-is-finally-fixing-submissions-claims-and-onboarding/
**Watch on YouTube**: https://www.youtube.com/watch?v=5oY1x4hUWv0
**Length**: 47m 05s

## About this webinar

A joint Kognitos and Indium webinar focused on three of the most persistent backlog hotspots in the insurance industry — submission triage and underwriting, claims registration, and agent/broker onboarding. Presented for carriers, MGAs, brokers, agents, and BPO / shared-service organisations.

## The three workflows tackled

- **Streamlining underwriting submission triage**: parse a flood of broker submissions (each with its own format), extract risk factors, route to the right underwriter, and clear the backlog.
- **Transforming claim registration**: get from FNOL (First Notice of Loss) to a registered, structured claim faster — without losing fidelity on the documents.
- **Reducing agent onboarding cycle time**: collect, verify, and approve the licensing and appointment paperwork that gates a new agent's ability to write business.

## Why incumbent tools haven't solved these

- **Brittle bots**: legacy RPA breaks on document variation — every broker submission and every claim form looks different.
- **Black-box LLMs**: rolling out an opaque generative model in a regulated environment is not viable. Insurance teams need to know *why* a decision was made.
- **Tribal-knowledge gaps**: most of the resolution logic lives in the heads of experienced operators — the “always check this field before approving” kind of knowledge.

## How Kognitos and Indium fit together

- **Kognitos**: neurosymbolic AI automation — LLM-driven extraction wrapped in a deterministic English-as-code runtime that promises “never hallucinate, never misrepresent.” Designed for highly regulated environments where transparency is non-negotiable.
- **Indium**: global system integrator with 5,000+ associates spanning GenAI, digital engineering, QA, data and analytics, and gaming. Deep delivery footprint to operationalise the Kognitos platform inside insurance carriers and MGAs.
- **Joint promise**: AI that's safe and scalable inside carriers, brokers, MGAs, and agents — not another point tool that addresses only one slice of the workflow.

## Roadmap highlights

- Capturing tribal knowledge from operators as reusable English rules.
- Deeper data search across Kognitos data *and* data outside Kognitos for decision-making.
- More decision-capture primitives so the AI helps decide, not just extract.

## FAQs

**Q: Which insurance workflows does this webinar focus on?**

Three: underwriting submission triage, claims registration, and the agent/broker onboarding process. The session is aimed at carriers, MGAs, brokers, agents, and the BPO / shared-service organisations that handle outsourced work for them.


**Q: Who are the Kognitos and Indium speakers?**

From Kognitos: Joe O'Neal (host) and Chitu (global partnerships). From Indium: Romesh and Jagan. Indium is a global system integrator with 5,000+ associates whose core capabilities span generative AI, digital engineering, quality assurance, gaming, and data & analytics.


**Q: Why does Kognitos position itself as “neurosymbolic” for insurance specifically?**

Insurance is highly regulated — carriers can't afford to ship a black-box LLM that occasionally hallucinates. Kognitos pairs LLM-driven extraction with a deterministic symbolic runtime so every decision is transparent and reproducible, which is the bar regulated carriers actually need.


**Q: What's on the Kognitos roadmap for insurance based on this webinar?**

Capturing tribal knowledge from operators as reusable English rules, deeper data search across both Kognitos data and external data, and more decision-capture capabilities so the platform helps make decisions in addition to extracting and routing.