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Zentis AI
Industries
Banking & creditSOUL co-pilot, retail credit, onboarding.InsuranceFNOL, claims triage, underwriting.Finance, risk & voiceForecasting, reserving, voice agents.Insurance BrokerageEvery quote and every renewal, ready before the client starts wondering.
Products
Zentis AnalyticsForecasting, reserving, and regulatory reportingAuditOSBank, e-commerce, Shariah, and claims audit.FAMIend-to-end motor insurance automationZentis BinderDefence file assembly, live as the case runs.
Resources
NewsProduct news and conference write-ups.ArticlesLonger pieces on AI in regulated industry.Events & webinarsWhere to find us in person.UsecasesA library of reusable, editable templates.
Company
AboutWho we are and why the harness is the product.PartnersTechnology, consulting, and reseller partners.ContactTalk to the team, or book a working session.CareersJoin us
Platform
ZaraZara is where a workflow starts, Zara builds the team.Zen StudioZen Studiois where engineering opens it upZen PilotZen Pilot is where it actually runs
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Zentis AI

An enterprise-grade agentic platform for banking, insurance, and audit. Incubated by Techvantage.ai.

Platform

ZaraSPARZen StudioZen Pilot

Solutions

Audit & complianceInsuranceBanking & creditFinance, risk & voice

Trust

The defence fileSecurityAssuranceRegulatory packs

Resources

NewsArticlesEvents & webinarsClassic

Company

AboutPartnersContactCareers
© 2026 Zentis AI. All rights reserved.info@zentis.aiLondon, England
Anthropic Partner NetworkNVIDIA InceptionTechvantage.ai, Deloitte Technology Fast 50

Every credit decision, defended from the day it's made and the years after.

Banking runs on judgment calls that have to survive a regulator's questions months later, not just a committee's approval today.
Request a demoSee use cases

What we consistently hear

The same handful of pain points, in every conversation with teams in this industry.

Consistency depends on who picked up the file

Two analysts can look at the same application and reach different calls, and there's rarely a clean way to show why one call was right and the other wasn't.

Coverage is a percentage, not a guarantee

KYC and AML screening often runs on a sample, because reviewing every new account the way policy requires would take longer than the business can wait.

Investigations wait behind evidence gathering

Fraud and audit teams spend most of a case's cycle assembling the file, not deciding what's in it, and the backlog grows while they do.

Relationship managers spend the meeting building the meeting

Portfolio review prep eats the hours that should go to the client sitting across the table, not the system behind them.

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.

01

One governed team, every file

Zara builds the same six-role team for every application. It doesn't have a good day or a bad day, and it doesn't disagree with itself between reviewers.

02

Full population, not a sample

Deterministic rules run first and extend coverage to every account, not just the ones that happened to get pulled for review.

03

Evidence assembles itself, live

The defence file builds as the case moves through Zen Pilot, not after someone finally asks a regulator to reconstruct it.

04

A second opinion before anything's signed

A SPAR adversarial pass checks the first conclusion against how a similar case was handled, before a named officer signs off on either.

Platform in context

What this could mean

Illustrative, drawn from the shape of workflows modelled for this industry. The real number depends on the case, the team, and how it's configured.

Decision cycle time

Days down to hours

across credit, fraud, and onboarding workflows modelled for banking teams.

Screening coverage

Sample to full population

without adding headcount to the compliance function.

Senior escalation rate

Fewer cases reaching a senior analyst

when the first pass already carries a documented, checked rationale.

Meeting prep time

Hours down to minutes

so relationship manager time goes to the client, not the file.

Use cases

Use cases in Banking & Credit

Specific workflows, worked through end to end.

A bank building, beside figures on global reach — 170+ countries represented and $444B+ USD of global economic activity
Banking - Middle East

Full population audit testing for a retail bank

70%Reduction in audit cycle time
View use case →
Banking - Global

SME and retail credit underwriting

8 days → 5 hoursApplication to credit decision
View use case →
Banking - Global

KYC, AML and customer due diligence

4 days → 20 minutesScreening to risk rating decision
View use case →
Banking - Global

Fraud investigation for a retail bank

10 days → 1 dayCase flag to closure recommendation
View use case →
Banking - Global

A copilot for relationship managers

3 hours → 5 minutesPortfolio review prep per client meeting
View use case →
Banking - Global

Digital customer onboarding automation

3 days → 15 minutesApplication to onboarding decision
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

RBI, CBUAE, FCA, and the data residency requirements that come with each. 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

Most banks evaluating this work compare an internal build team against a horizontal, no-code platform. Neither ships with banking-native agents, jurisdiction-aware regulatory packs, or an adversarial check built into the cycle. Zentis starts with all three already in place.

Bring one workflow. See what it looks like running under Zentis.

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.

Banking & Credit work goes through SPAR like everything else. The domain knowledge changes; the governance does not.

SaaSPrivate cloudOn-premiseAir-gapped

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 banking & credit 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.

Book a demo