Duck Creek has made its Agentic First Notice of Loss product available to early-access customers. The insurer-software provider says the service uses orchestrated AI agents to capture, validate, enrich and route claims across digital, voice-to-text and mobile channels.

First notice of loss is an attractive automation target because poor information at intake creates downstream cost, delay and customer frustration. Duck Creek says its system can verify coverage, identify potential issues and move a claim towards the appropriate next step. It also claims benefits including better data quality, shorter claims cycles and lower loss-adjustment expense; those outcomes have not yet been independently demonstrated in the announcement.

The governance burden is unusually high at this point in the process. A distressed policyholder may provide incomplete or ambiguous information, while a routing decision can influence fraud treatment, reserving and the speed of support. Insurers therefore need evidence of what the agent asked, what it inferred, which records it used and when a human intervened. Early-access status makes the launch editorially valuable precisely because the controls are still being tested. The decisive measure will not be conversational fluency, but whether the system produces reliable, contestable and auditable claims records.

Execution Level Governance- What audit-ready agent governance actually looks like
David Girvin, founder and CEO of Assury argues that model-in-the-loop review, AI governing AI, is fundamentally unreliable for regulated environments: even the best-performing models miss a meaningful share of violations, the reviewing model is typically provided by the same vendor being reviewed, and prompt injection or context poisoning can compromise both the acting agent and its supposed overseer simultaneously. He makes the case for deterministic, architecturally enforced controls instead, walking through Assury’s approach of autonomy zones, session risk accumulation, and credential starvation, which lets a compromised agent be cut off from its tools instantly rather than relying on time-boxed access. The conversation touches on why David is sceptical of just-in-time credentialing as a solution for agent security more broadly, since agent sessions don’t run on predictable human timescales, along with the current gap between how identity and security vendors are pitching agent protection and what he sees happening at the execution layer in practice. He also discusses the compliance and audit implications of probabilistic decision-making, arguing that regulated industries will increasingly need tamper-evident, hash-chained audit trails that can withstand scrutiny from auditors and regulators who are only beginning to understand agentic risk, and reflects on a named frontier lab’s own published framework as an example of the gap between research and practitioner reality. Elsewhere, David reflects candidly on building a bootstrapped security company in an increasingly crowded market, why he turned down aggressive VC funding to stay in control of the product, and what a credible third-party assessment of his own gateway would need to look like given that Assury sits directly in the execution path for every customer’s agents.
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