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AI Readiness

Is your organization AI-ready?

Many enterprises want to leverage AI but lack the data quality, governance, or infrastructure to support it. AI readiness is about building a trusted foundation that allows machine learning and generative AI applications to deliver accurate, secure, and compliant outcomes. Passerelle’s AI Readiness services assess your current environment, highlight gaps, and provide a roadmap for safe and effective adoption.

AI Readiness

Is your organization prepared to adopt AI responsibly?

AI Readiness matters. AI projects often fail when built on incomplete, siloed, or unsecured data. Before implementing advanced tools, organizations must ensure they can trust their data, comply with regulatory requirements, and align leadership on governance and culture.

With Passerelle’s AI Readiness services, you will be prepared to:

  • Safeguard compliance with HIPAA, GDPR, and emerging AI regulations.
  • Reduce risk of bias, hallucinations, and governance failures.
  • Enable a data-driven culture that supports adoption.
  • Avoid wasted time and resources on failed pilots.

How It Works

Preparing for AI requires more than a quick checklist—it takes a structured evaluation of your systems, processes, and policies. Passerelle uses a proven framework to assess readiness and create a roadmap that balances risk management with innovation. This includes:

  • Readiness Assessment – Review data maturity, governance, and architecture.
  • Risk & Ethics Review – Evaluate transparency, oversight, and bias mitigation.
  • Use Case Alignment – Identify achievable opportunities tied to business goals.
  • Custom Roadmap – Deliver actionable next steps with time and cost estimates.

Customer Testimonials

“We have a small team. We like to punch above our weight, and we look at who we’re competing against. We need something to help us out, and that’s why a strong toolset that includes Generative AI will help us produce things faster and get some of the monotonous reporting out of our hands. It will help us along our path of efficiency.” Josh Nash, SVP and Director IT at Camden National Bank

Preparing for Enterprise AI

Architecture Review – Validate whether your data estate supports AI workloads

Gain an understanding of your current environment with an assessment of your existing infrastructure. The review confirms cloud readiness, integrations, and performance so your systems can support AI workloads at scale.

Data Quality & Security – Confirm access to clean, compliant, and governed data

Improve trust in your AI initiatives by validating the accuracy, completeness, and compliance of your data. Governance and security controls ensure that sensitive information is protected while remaining accessible to the right people.

Governance & Stewardship – Establish ownership, lineage, and monitoring practices

Build confidence in your data by establishing clear ownership, lineage tracking, and monitoring practices. These measures create accountability and transparency, ensuring that data is reliable and audit-ready.

Culture & Training – Equip teams with knowledge to adopt and manage AI responsibly

Accelerate adoption by giving your teams the knowledge and confidence to work with AI responsibly. Training programs build literacy across business and technical users, supporting long-term use and organizational alignment.

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Snowflake
Highline
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Data
Rocket
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Guide
to Modernization for Banks and Credit Unions

Frequently Asked Questions

Q: How long does the readiness process take?

A: Most readiness assessments take a few weeks, with recommendations delivered quickly.

Q: What if my data isn’t perfect?

A: That’s common. Readiness prioritizes improvements so you can move forward safely.

Q: Do we need AI expertise already in place?

A: No. Our goal is to help your existing team prepare for AI adoption.

Case Studies

We help businesses harness the power of their data.

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Camden
National Bank
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Washington
University in St. Louis
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Metro
Credit Union
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