95% of GenAI pilots never reach production

From AI pilot → production
without a leap of faith

GenGuardX gives teams the clarity and control to test, approve, monitor,
and track GenAI before and after launch 

Trusted by Tier 1 global banks Leading US health systems Credit Unions SOC 2 Certified
The two blockers

Two teams have to say yes before AI goes live

Business teams need confidence in what the AI should do.
 Risk teams need evidence against what it should and will not do.
 Most pilots stall because neither has the right tools to get this confidence.

Business Team Objective
Does the AI do what it's supposed to?

While business teams own the experience, they are often sidelined during technical testing. GGX bridges this gap, allowing you to interact with the AI, verify its value in real-time, and build the evidence-based confidence needed to sign off with certainty.

Trust gapNo hands-on way to validate AI behaviour before it reaches customers.
Reputation riskLogic errors and hallucinations turn into public brand liabilities.
Unclear readinessNo objective proof that the AI is ready for production.
Risk Team Objective
Is the AI blocking policy violations?

Before GenAI goes live, risk and legal teams need more than a demo, they need evidence. GGX enables teams to stress-test models against unintended behaviors, track the closing of security gaps, and build a defensible audit trail that ensures compliance from day one

Novel risksCritical vulnerabilities like bias, data leaks, and jailbreak attempts.
No evidence trailSubjective testing is difficult to defend to legal, risk, and audit stakeholders.
No thresholdsLack of clear, measurable metrics for what constitutes safe.

Confidence comes not from seeing, but from trying.

BUSINESS · HOW GGX SOLVES IT

Empower Business Owners to Validate AI

GGX provides the safe environment your Subject Matter Experts (SMEs) need to stress-test scenarios, flag behavioural gaps, and verify fixes before your AI reaches a single customer.

Trust cycle: Try, Experience, React, Retest, Repeat - with TRUST at the center. Each cycle builds confidence. Every fix increases trust.

Interactive playground

Business users run realistic scenarios against the AI application before launch - no developer required.

Feedback portal

One-click flagging, ratings, and structured findings on every interaction.

Findings database

Every issue tracked from raised to resolved, no scattered feedback lost.

Progress tracking

Version-over-version proof that issues are being fixed.

THE BYPRODUCT

Every business reaction becomes ground truth

Every flag, rating, and annotation from a business user becomes reusable ground truth. GGX turns SME feedback into structured data that supports objective measurement, faster iteration, monitoring, and future evaluation sets. Capture it once. Reuse it throughout the AI lifecycle.

RISK · HOW GGX SOLVES IT

Give risk teams evidence they can approve

GGX turns GenAI risk review into a repeatable workflow: identify applicable risks, measure them with standardized evaluations, mitigate gaps, and monitor after launch.

01 · IDENTIFY

Map applicable risks

Select use-case-specific risk categories such as accuracy, bias, toxicity, privacy leakage, groundedness, prompt injection, and agent tool use.

02 · MEASURE

Run standardized evaluations

Use repeatable tests against curated datasets, expected outputs, policies, and thresholds - not one-off scripts.

03 · MITIGATE

Track fixes and retest

Apply guardrails, prompt changes, routing logic, or workflow controls, then prove the gap was closed.

04 · MONITOR

Watch for drift and regressions

Detect new failure modes, threshold breaches, and model behavior changes after deployment.

Stop guessing what your risk exposure is.

Risk library

Stability, accuracy, ethics, vulnerability, groundedness, prompt injection, jailbreaking, dark patterns, data leakage - and your custom categories.

Standardized reports

Choose from a library of use-case-specific reports and datasets, or create your own. Approved, versioned, reusable.

Controlled evaluation

Run evals in a controlled environment with reproducible outcomes, auditable records, and challenger comparisons.

PRODUCTION · THE GGX EXTENSION

Keep both teams confident after launch

Approval is not a one-time event. Inputs drift, LLMs update, and third-party agents shift.
GGX keeps business and risk teams aligned by turning observability traces into alerts, evidence, and ground truth.

BUSINESS TEAM · CONTINUED
"Did the AI do what it's supposed to do?"
→ Is it still doing what it's supposed to?
RISK TEAM · CONTINUED
"Is the AI blocking policy violations?"
→ Is it still blocking what it shouldn't?
High-volume production traces, narrowed to what truly needs review Live production traces Every customer interaction · errors · latency · cost Heuristic pre-processing Deduplication · noise filtering · diversity enforcement LLM-aided judgment Answer relevancy · toxic/jailbreak · groundedness Human review, only when needed

For the business team

See when AI behavior drifts from the version they approved. Surface quality decay, confusing responses, and customer-impacting failures before they become reputational issues.

For the risk team

Track threshold breaches, new failure modes, and control performance in production. Maintain audit trails that approved controls continue to work.

For both

Turn production findings into new ground truth, new test cases, and new approval evidence. Monitoring feeds the next cycle of refinement and validation.

GGX builds clarity around what truly counts.

Industries

Built for high-stakes, customer-facing AI

The blockers are universal: business confidence, risk approval, and production monitoring. The use cases vary by industry.

Financial services

Banking, credit unions, lending

Customer chatbots, fraud agents, credit-decisioning agents. Where stakes are high, internal approvals are slow, and production drift is closely watched. Deployed at a Tier 1 G-SIB.

Healthcare

Health systems and payers

Triage IVR, patient chatbots, clinical documentation agents. Where patient trust and clinical accuracy are non-negotiable. Live in production at a leading US health system.

Insurance

Carriers and brokers

Claims agents, underwriting assistants, policyholder chatbots. Where customer decisions affect lives - and any wrong answer can go viral fast.

AI-native

Built for Enterprise AI teams.

Customer support agents, internal copilots, multi-agent systems. Where AI velocity has to meet business reality before things ship - and stay safe after.

Responsible AI sandbox

Practice before you deploy

A guided cohort program with Google Cloud and Oliver Wyman, where enterprises run real use cases through the full AI lifecycle - with experts in the room.

12
Institutions
3
Month cohort
2
Cohorts run

"The sandbox is a safe and practical way to learn how to measure and manage risks from GenAI, so organizations can build the confidence to use this powerful technology."

- Toby Brown, Managing Director, Global Retail Banking Solutions, Google Cloud

Apply for the next cohort →
Ways to engage

Start where your AI program is today

Begin with targeted testing, expand to approval workflows, and scale into full lifecycle monitoring.

EXPLORE
Test an AI use case
Interactive agent testing
Ground Truth Dataset creation
Core bias and accuracy tests
Toxicity and tone tests
Common LLM connectors
Versioning and activity tracking
APPROVE - MOST COMMON
Build confidence and approval
Everything in Explore, plus:
Business-team feedback portal
Trace ingestion & LLM judges
Custom risk tests & reports
Findings database & tracking
Approval workflows
SCALE
Govern the full lifecycle
Everything in Approve, plus:
Production monitoring & alerts
Org AI Policy & Risk Framework
Custom agent integrations
SSO & access management
Dedicated advisory support
Ready to move past pilot ?

Get your AI to production - and keep it there

A shared environment that gives business teams confidence, risk teams evidence, and both of them visibility - for the full lifecycle.

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