For one of the largest U.S. wealth management firms, GenAI wasn’t a buzzword. It was already in motion spanning marketing, product development, data science, and advisory tools.
But velocity had led to sprawl. Dozens of experiments were running in parallel without shared standards for evaluation, compliance, or risk. According to BCG, while over 90% of financial institutions expect GenAI to reshape operations within three years, fewer than 20% have moved beyond pilots (source). This firm didn’t want to remain in pilot purgatory.
The Goal: Structured Innovation, Not Bureaucratic Delay
The goal wasn’t to slow innovation but to scale it responsibly. It wanted to scale it responsibly. That meant designing an architecture that could:
- Inventory and monitor GenAI initiatives across all teams
- Standardize how models are selected, tested, and approved
- Introduce risk and compliance controls from day one
- Reuse successful pipelines across business units
- Create alignment between GenAI efforts and enterprise AI strategy
Persistent Systems was brought in to deliver that governance layer, fast.
The Solution: The GenAI Governance Hub
In just 12 weeks, Persistent delivered a full-stack GenAI Governance Hub, built entirely on Google Cloud. The key capabilities included:
- A central registry of LLMs, experiments, and tools
- Authentication controls aligned to enterprise security policies
- Evaluation workflows using real-world prompts and scoring rubrics
- Scorecards for hallucination rate, compliance, bias, and more
- Approval chains to govern production readiness
It provided a single view of all GenAI activity, enabling innovation without sacrificing safety.
Illustration cue: Dashboard view – Registry → Evaluation Pipelines → Scorecards → Risk & Approval Gates
The Hub wasn’t a brake. It was a fast lane with guardrails.
Why It Worked: Governance That Accelerates
Many governance programs fail because they slow teams down. This one didn’t. Here’s what made the difference:
- One governance architecture applied across all business functions
- Guardrails that flexed based on project sensitivity (e.g., internal vs. client-facing)
- Reusable pipelines, scoring templates, and prompts
- Shared collaboration layer for performance data
- Out-of-the-box integration with OpenAI, Vertex AI, and Anthropic APIs
The result? It worked for developers, risk officers, and the C-suite alike.
Within 90 days of launch, the Governance Hub had transformed operations:
- 50+ GenAI projects registered and tracked
- Model evaluation cycles shortened by 70%
- Legal and compliance gained real-time oversight
- Reuse of evaluation assets across 12+ teams
- Enterprise-level visibility into all GenAI efforts
Illustration cue: Before/After table – manual reviews vs. centralized scoring + tracked approvals
The shift was clear: from oversight gaps to enterprise-wide confidence.
Strategic Impact: Future-Proofing AI at Scale
The Governance Hub is now a launchpad for sustainable growth. It supports:
- Cross-team model evaluation on shared baselines
- Versioning and audit-friendly data retention
- A future GenAI Center of Excellence built on standardized KPIs
- Accelerated rollout of new initiatives via standardized infrastructure
McKinsey estimates that scaling GenAI with proper governance and reuse can cut deployment costs by up to 40%.
This wasn’t just an audit win. It was a new operating system for AI.
The Takeaway: From Pilot Paralysis to Platform Power
Many firms experiment with GenAI. Few govern it at scale. By partnering with Persistent, this wealth leader created an enterprise-wide capability transforming GenAI from scattered tests into a managed, measurable, and strategic asset. From disconnected pilots to an execution platform. From friction to fluency. This is GenAI, done right.
