Building Rizzler: AI That Understands Human Connection

Communication is fundamentally human, yet increasingly mediated by screens. When we started building Rizzler, we asked ourselves a provocative question: can AI help people be more authentically themselves in digital conversations?

The Problem with Digital Communication

Text-based communication strips away 93% of human expression—tone, body language, facial cues. What remains is a narrow bandwidth that often leads to misunderstandings, awkward exchanges, and missed connections.

We’ve all been there: staring at a message, unsure how to respond. Overthinking a text until it sounds robotic. Sending something that lands completely wrong.

Building the Analysis Engine

The core of Rizzler is a multi-modal AI system that understands context, not just content. We trained our models on millions of conversations (anonymized and consented) to recognize patterns that humans intuitively understand but struggle to articulate.

// Simplified conversation analysis pipeline
interface ConversationContext {
  emotionalTone: ToneVector;
  relationshipDynamics: DynamicsScore;
  conversationMomentum: number;
  suggestedApproaches: Approach[];
}

async function analyzeConversation(
  screenshot: ImageBuffer,
): Promise<ConversationContext> {
  const extracted = await ocr.extract(screenshot);
  const messages = parser.parseMessages(extracted);

  return {
    emotionalTone: await toneModel.analyze(messages),
    relationshipDynamics: dynamics.score(messages),
    conversationMomentum: momentum.calculate(messages),
    suggestedApproaches: await suggestions.generate(messages),
  };
}

The Cringe Guard: Preventing Digital Faux Pas

One of our most-requested features emerged from user feedback: people wanted to know before they sent something if it might land poorly. Enter Cringe Guard.

The system analyzes draft messages against the conversation context and flags potential issues:

Tone mismatches that could create awkwardness
Overly eager responses that might seem desperate
Conversation-killing replies that shut down dialogue
Timing considerations based on response patterns

With Cringe Guard enabled, users report a 64% reduction in messages they later regret sending.

Ethical Considerations

Building AI for human communication comes with significant responsibility. We established clear principles early:

Augment, don’t replace — Suggestions are starting points, not scripts
Authenticity over optimization — We help users express themselves better, not become someone else
Privacy by design — Screenshots are processed and immediately discarded
No manipulation — We refuse to build features that help users deceive others

The Results

After analyzing over 120,000 conversations across platforms, the data tells a compelling story:

92% of users report smoother, more natural conversations within their first week
Average response time decreased by 34% (less overthinking)
User-reported conversation satisfaction increased by 47%

What’s Next

We’re exploring voice message analysis, real-time suggestions for video calls, and cross-cultural communication assistance. The goal remains constant: help humans connect more authentically in an increasingly digital world.

Communication technology should bring us closer together. With Rizzler, we’re building the bridge.

Interested in exploring Rizzler? Visit rizzler.guru to try it yourself.

Marcus Johnson Systems Architect, Axiron