Convr AI Introduces Agentic AI Workflows for Autonomous Underwriting

Jan 16, 2026
Convr AI has introduced Agentic AI workflows within its underwriting workbench, enabling automated decision-making and reducing manual steps in commercial insurance underwriting.

Convr has introduced Agentic AI workflows to enhance automation in commercial insurance underwriting, announced in a press release. The new capabilities are integrated into its AI-powered underwriting workbench and include referral, financial analyst, and underwriting authority workflow agents.

These pre-built workflow templates allow underwriting teams to automate decision-making processes, such as generating referral summaries based on exposures, losses, and limits. The system can determine whether a submission fits within underwriting appetite or requires referral, and users can adjust the agents' level of autonomy to make or recommend decisions.

The platform’s template library includes starter prompts that can be customized without prompt engineering experience, requiring only basic underwriting knowledge. According to Convr, the Agentic AI workflows proactively collect data, flag risks, fill forms, and recommend actions, functioning as digital team members within the underwriting process.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Finance AI Weekly or Daily AI Brief.

Also, consider following us on social media:

AI in Finance AI Brief AI Brief (X)
Free newsletter

Finance AI Weekly

Weekly newsletter about AI in finance. Covers AI-driven trading, fintech innovations, and data analytics transforming markets

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.