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ADVOCACY PROGRAM

A dedicated AI quality partner, not another point tool.

Ongoing expert guidance, priority support and monthly reviews across CI/CD and cloud-native delivery. One partner and one workflow instead of a stack of isolated tools, kept current with AI trends instead of quietly going stale.

One dedicated advocate,
not a rotating support queue.

01.

Onboarding & baseline

Your dedicated advocate reviews existing evaluation pipelines, test coverage and governance posture to set a baseline before the first review cycle.

02.

Monthly reviews

Recurring reviews of quality metrics, safety benchmarks and CI/CD integration. Issues get caught in the review cycle, not in production.

03.

Priority access & support

Direct, priority access to the senior engineers running your pipeline. No ticket queue, no account-manager relay.

04.

Continuous improvement

Your quality stack is kept current with AI trends and tooling updates automatically, instead of quietly going stale like an unmaintained in-house platform.

One partner and one workflow, instead of a stack of isolated tools.

STACK OF POINT TOOLS

Isolated, unmaintained tooling

  • Different vendors for evaluation, monitoring and governance that don't talk to each other.
  • No one accountable for the platform staying current with AI trends.
  • Support tickets routed through a queue instead of a named engineer.
OPENCREVO

Advocacy Program

  • One dedicated advocate covering evaluation, CI/CD integration and governance together.
  • Monthly reviews keep the stack current instead of quietly going stale.
  • Priority, direct access to the senior engineers who know your systems.

24h

Engineer response time

0%

Client churn

6 wks

Avg. roadmap to production

Not ready for an ongoing partnership yet?

Book an AI Transformation Consultation

Need a platform assessed before you commit?

See Platform Evaluation
START YOUR QUALITY JOURNEY

Your next chapter starts with a conversation.

Book a free quality audit. We'll review your AI system, identify the highest-risk failure modes, and map a quality roadmap tailored to your stack.