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Implementing Corti AI: A Pilot & Adoption Guide for Partners

Updated over 2 weeks ago

1. Align on Project Goals & KPIs

Start by clarifying why you’re running the pilot:

  • Efficiency (e.g., 50–70 % reduction in documentation time)

  • Clinician well-being (e.g., burnout reduction, improved focus)

  • Documentation quality and patient experience improvement

  • Define measurable KPIs—such as adoption rate, documentation time saved, clinician satisfaction—to anchor pilot success.

2. Estimate Usage Volume

Discuss with your customer:

  • Number of clinicians (by specialty, if applicable)

  • Frequency of sessions per clinician per day/week

  • Phased or full-scale rollout plans

This helps inform pricing discussions, infrastructure readiness, and support planning.

3. Define Essential Workflows & Features

Work with clinicians to map:

  • Workflows: transcription, live documentation, editing, templates, coding

Clarifying these helps guide feature configuration and trade-off decisions.

4. Confirm Budget & Commercial Terms

Ensure clarity around pricing:

  • Per-seat costs vs potential free tiers or trial periods

  • Any overage or ancillary fees

  • Alignment with ROI expectations

This keeps vendor selection and pilot scope aligned with budget constraints.

5. Engage Clinician Sentiment Early

Solicit feedback from clinical staff about AI documentation:

  • Use surveys or interviews to gather needs e.g. exemplary templates / clinical notes and concerns

  • Identify potential adoption barriers

Appoint clinical champions to model usage and drive uptake.

6. Ensure Regulatory & Security Compliance

Show how Corti supports standards such as HIPAA, GDPR, or local equivalents via secure deployment on Azure—geographically tailored per customer—and strong data management protocols (help.corti.app).

Discuss configurations—multi-tenant vs standalone—and reassure customers about:

  • Access control, encryption, key management

  • Data isolation, backups, auditing, and recovery (help.corti.app).

7. Plan a Structured Deployment Timeline & Training

Lay out a phased approach:

  • Pilot launch: small group of max. 3-5 end users, train on basic use and integration

  • Scale: springboard to broader use (> double-digit users) once adoption is proving out

Define responsibilities for training, communications, and support.

8. Provide Strong Support & Infrastructure

Rely on Corti’s robust infrastructure and service model:

  • Fully managed service on Azure, minimizing IT burden (help.corti.app)

  • 99 %+ uptime SLAs, rapid escalation paths, and 24/7 support (help.corti.app)

  • Comprehensive Help Center and documentation for self-service (help.corti.app)

9. Monitor Adoption, Gather Feedback, Iterate

Track:

  • Activation rates and usage frequency

  • Time savings in documentation

  • Clinician feedback (e.g., ease of editing, workflow fit)

Use insights to refine templates, onboarding, integrations, or training.

10. Scale with Confidence

Once pilot metrics meet expectations (e.g. adoption rate above 60 %), plan a broader rollout:

  • Leverage clinician champions to drive success

  • Share ROI data and testimonials to build momentum

  • Expand training, support, and integration coverage as needed


Sample Pilot Timeline for Partners

Phase

Activities

Planning

Align goals, define KPIs, estimate usage, formalize scope

Setup

Provision Corti instance, configure deployment (Azure, ML vs standalone)

Onboarding

Train clinical champions and early users, align workflows and templates

Pilot Launch

Monitor uptake, gather feedback, resolve blockers via support

Evaluation

Review KPIs, clinician sentiment, usage data, adjust as needed

Scale-Up

Expand usage, templates, training, and integrations across departments


Summary: Best Practices for Pilot Success

  1. Start with clear goals and KPIs

  2. Understand clinician workflows and feature needs

  3. Set realistic expectations around adoption and budget

  4. Leverage Corti’s secure, compliant infrastructure

  5. Maintain proactive training and support

  6. Monitor and iterate based on real-world usage

  7. Use positive results to drive broader rollout

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