North Star Identity
AI Services
Project Engagement

Responsible AI & Secure Prototype

You have a promising AI use case, but building it without security, identity, and governance controls in place from day one just creates a bigger problem to retrofit later.

A working, secure AI prototype — with identity, access, and governance controls built in — ready to evaluate for production investment.

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Who it’s for

  • Teams ready to move a prioritized AI use case from idea to a working, evaluable prototype
  • Organizations that want security and governance built in from the start, not bolted on after a pilot succeeds
  • Risk and compliance teams who need to see controls in action before approving production investment

What we deliver

  • A scoped, working prototype for your priority use case — for example a governed knowledge assistant or document workflow
  • Identity and access controls for the AI system and any AI agents involved, treated as governed non-human identities
  • Responsible-AI guardrails — human oversight points, output filtering, and audit-trail logging
  • An evaluation framework so stakeholders can assess quality, safety, and business value objectively
  • A clear recommendation and roadmap for production investment

How the engagement works

Typical duration: 6–10 weeks

01

Scope

Define the specific use case, success criteria, and evaluation method up front.

02

Build

Develop the prototype with identity, access, and guardrail controls built in from the first line of code.

03

Evaluate

Test against defined criteria with real stakeholders and representative data.

04

Recommend

Present findings and a production-readiness roadmap, including gaps to close before scaling.

Technology ecosystem

Platforms we commonly work with — not an implied partnership or certification.

Retrieval-augmented generation (RAG) architecturesMicrosoft Copilot, Salesforce Agentforce, watsonx Orchestrate, and similar platformsEnterprise identity platforms for AI-agent governance

FAQ

Will this use our real data?

We use representative or de-identified data wherever possible, and apply the same data-protection controls we'd recommend for production.

Does 'secure prototype' mean it's not production-ready?

It means the controls are production-grade even though the scope is intentionally limited — scaling it is a deliberate next decision, not a surprise gap.

Who needs to be involved from our side?

A business owner for the use case, a technical stakeholder, and ideally someone from risk/compliance for the evaluation phase.

What if the prototype shows the use case isn't worth pursuing?

That's a valid, valuable outcome — you'll have spent a fraction of a full production build to find out.

Ready to get started?

Discuss a Project