When people talk about AI in digital health, the conversation often jumps straight to chatbots and clinical scribes.

That’s understandable — they’re visible, tangible, and easy to demo.

But they’re not the most important applications of AI.

The most impactful uses of AI in healthcare aren’t about replacing people.
They’re about supporting the humans responsible for care — and scaling trust, safety, and outcomes.

AI That Augments, Not Replaces

At MEMOTEXT, we’ve been hard at work applying AI where it matters most:
high-touch patient interactions.

Our focus is on augmenting patient support communications by:

• Supporting clinical, peer, and support staff in patient programs with real-time next-best-action prompts
• Helping certified peers using digital mental health tools stay grounded, safe, and supported
• Layering context over call center and support interactions without adding cognitive burden
• Surfacing early signals of distress, disengagement, or misunderstanding from patient interactions

This is not automation for automation’s sake.
It’s AI designed to strengthen human judgment, not bypass it.

AI in High-Touch Patient Interactions: Real Use Cases

When applied responsibly, AI can play several critical roles:

• Conversation co-pilot – supporting staff with context and guidance in real time
• Conversation guardrail – helping ensure safety, tone, and appropriateness
• Early disengagement warning – identifying when patients are drifting away
• Early readmissions warning – detecting signals that intervention may be needed

These capabilities support real-world environments, including:

• Patient Support Programs (PSPs)
• Case Management teams
• Certified Peer Support programs
• CCBHCs
• Provider systems

Non-Negotiables: Safety, Oversight, and Transparency

AI in healthcare only works when it operates within clear boundaries.

That’s why our approach ensures:

• Human-in-the-loop oversight
• Clear escalation paths, including centralized options
• Non-negotiable safety and transparency

AI should never be a black box — especially in patient support.

Our Long-Standing Goal

Since 2012, MEMOTEXT’s mission has been simple and consistent:
make health data useful and scale the healthcare conversation.

Today, that means deploying AI to help detect risk in patient engagement — responsibly and in context.

How This Is Working in Practice Today

In collaboration with a local hospital (CAMH), we co-created a patient engagement app for individuals using digital mental health support.

Here’s what made this work different:

• Tens of thousands of patient text and image posts were collected
• Every post was manually moderated by Certified Peer Support Workers
• This real-world, safety-reviewed data was used to train AI models — starting with NLP and evolving to LLMs — to:
  • Detect risk
  • Flag concerning language
  • Recommend next steps to peer support workers

Importantly:

The AI does not make decisions.
It supports the people who do.

This approach helps certified peers scale their impact while staying aligned with safety, ethics, and real-world workflows.

The Key Takeaway

AI supporting patient engagement isn’t just about chatbots and scribes.

It’s about:

• Knowing when not to speak — and when to escalate
• Supporting accountability across systems, economic, and clinical outcomes
• Operating within real constraints: privacy, trust, safety, and proof

When done right, AI becomes an invisible ally — one that helps humans deliver better care at scale.

Learn More

Download the co creation case study 

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