Every quote and every renewal, ready before the client starts wondering.

Brokers win and keep business on responsiveness. Waiting on an underwriter shouldn't be the reason a submission goes cold.

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What we consistently hear

The same handful of pain points, in every conversation with credit, fraud, compliance, and relationship management teams.

New business quotes wait on underwriter bandwidth

A client expects an answer the same day. Most quotes still take three, because they're queued behind an underwriter's other work.

Renewals turn into rework

An exposure change sitting in the file gets missed on the first pass, so the desk redoes work it should have caught the first time.

Claims advocacy starts with finding the status

Before an advocate can help a client, they have to go hunting for where the claim actually stands across insurer and client touchpoints.

How Zentis addresses it

Not a bolt-on feature for each pain point. One governed platform that removes the root cause of all of them.

Client and market data read as one picture

Needs and pricing profile get understood directly from the inquiry, not reconstructed from a back-and-forth.

Renewal history checked in full, every time

Opportunities and exposure changes get flagged before terms are proposed, not discovered after the client has already asked.

Status consolidated across every touchpoint

Claim status, documents, and communications pull together automatically, so an advocate starts from the answer, not the search.

Use cases in Insurance Brokerage

Specific workflows, worked through end to end.

Insurance Brokerage · Global

New business quoting for a commercial brokerage

3 days → 45 minutes

Client inquiry to bound quote

View use case →Insurance Brokerage · Global

Renewal review and servicing at scale

12 days → 1 day

Renewal review to confirmed terms

View use case →Insurance Brokerage · Global

Claims advocacy for a brokerage desk

5 days → 2 hours

Status change to client communication

View use case →

More workflows are being modelled

If yours isn't listed yet, that's a conversation worth having with Zara.

Built for how this industry is actually regulated

The same regulatory packs as the carriers you place business with, so nothing gets lost in translation between broker and insurer. Deployment runs as SaaS, private cloud, on-premise, or fully air-gapped, with model choice, OpenAI, Anthropic, Google, open-weight, or your own, set per agent at runtime. GDPR compliant, SOC 2 and ISO 42001 certified, regardless of which option you choose.

Why teams choose this over the alternatives

A brokerage serves many carriers, not one, so the platform underneath it has to stay neutral. Zentis doesn't favor a market or a line of business, it runs the same governed cycle regardless of which insurer the business ends up with.

Three answers, before you have to ask.

The economic buyer is assessing career risk, not capability. These are the three doubts, answered inline.

The full detail lives on the Trust page.

Determinism

What happens when the model is wrong

Deterministic rules run before any model does, and roughly 69% of narration-audit records settle on rules alone. Below the confidence threshold the workflow escalates to a human rather than guessing.

Deployment

Where the models run, where the data sits

Your choice per deployment: SaaS, private cloud in your own subscription, on-premise inside your data centre including the models, or fully air-gapped with no egress at all.

Regulatory

Can this be shown to a regulator

Every decision carries a defence file: source, rule applied, confidence, adversarial record, and the named approver. Regulatory overlays ship per geography, versioned alongside the workflow.

A bounded way to find out.

No quarter-long RFP. A working session on your documents, with the challenge step switched on. If the controls it extracts are wrong, you will see that immediately — which is the point.

DurationSix to eight weeks, on a process you name.

What we need from you

A named process, and the documents it touches
One working session with the team that owns it
The regulatory pack for the geography you run in

What you get at the end

A running agent team on your data
The defence file for a real decision, end to end
A written readout: what held, what did not, what production takes

The same cycle, whatever the domain.

Insurance Brokerage work goes through SPAR like everything else. The domain knowledge changes; the governance does not.

SaaSPrivate cloudOn-premise

Model choice is configuration, per agent, at runtime — including your own on-premise model.

SSourcePulled from the system of record, with provenance and hash captured at ingest.provenance · hash

PProcessDomain specialists run in parallel under a schema contract, so bad payloads fail loudly.schema contract

AAdversarialA separate agent, on a different model, tries to break the result.cross-model review

RReleaseNothing leaves without a named human approving it. Citations, confidence, all of it.named approver

See insurance brokerage on your own documents.

A working session, on your data, with the challenge step switched on. If the controls it extracts are wrong, you'll see that immediately — which is the point.

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