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The Problem

Most scheduling tools just show “available times” chronologically. The first free slot might be:
  • 6am for someone in a different timezone
  • During lunch hour
  • Friday at 5pm
  • Technically free, but terrible
Syncline solves this. We rank slots by quality, not chronology.

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How It Works

Every time slot gets a score from 0 to 1, where higher scores indicate better matches for all attendees. Our algorithm considers multiple factors to find times that work well for everyone.

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Key Factors

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Timezone Fairness

Goal: No one should have awkward meeting times. We ensure meeting times fall within reasonable working hours for all attendees. If a time would be too early or too late for anyone, it gets significantly penalized. Example:
  • Alice (PST): 10am = ✓ Good
  • Bob (EST): 1pm = ✓ Good
  • Result: High score
Bad Example:
  • Alice (PST): 7am = ❌ Too early
  • Bob (EST): 10am = ✓ Good
  • Result: Low score
Timezone fairness is our most important factor. We prioritize times that work for everyone.

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Time-of-Day Preferences

Goal: Schedule at times when people are most receptive. Research and data show certain times of day work better for most professionals. We boost scores for these optimal windows while penalizing less ideal times. Why this matters: Morning meetings typically have higher acceptance rates than late afternoon meetings.

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Day-of-Week Patterns

Goal: Respect common work patterns. People tend to protect certain days or times for focused work. Our algorithm recognizes these patterns and adjusts scores accordingly. Example: Many professionals prefer to keep Friday afternoons meeting-free for wrapping up the week.

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Meeting Urgency

Goal: Balance urgency with quality. For time-sensitive meetings, we boost scores for nearer-term slots. For less urgent meetings, we prioritize optimal times even if they’re further out. Why this matters: Momentum matters for introductions and urgent discussions.

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Putting It Together

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Example Comparison

TimeScoreWhy
Tue 10amExcellentIdeal time, mid-week, good for both timezones
Wed 2pmGoodSolid afternoon slot, this week
Fri 3pmFairFriday afternoon, less ideal
Mon 12pmFairLunch hour, some inconvenience
Sat 10amPoorWeekend (if not enabled)

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User Preferences

The base algorithm applies to everyone, but individual preferences take priority:
If you set “9am-5pm Mon-Fri,” we only suggest times within that window.This completely overrides our default recommendations.
If you set a 15-minute buffer, we exclude slots that would create back-to-back meetings.Prevents scheduling fatigue.
If you set “max 5 meetings/day,” we stop suggesting slots once that limit is reached.Protects against meeting overload.

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Why This Matters

Without smart ranking:
  • 40% of suggested times get rejected
  • Requires multiple back-and-forth rounds
  • Wastes time and frustrates users
With smart ranking:
  • 85% of first suggestions accepted
  • One-shot scheduling
  • Happy users, efficient workflows

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Integration

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Using the API

The algorithm runs automatically when you request availability: 
curl -X POST https://api.syncline.run/v1/availability \
  -H "X-API-Key: sk_live_..." \
  -d '{
    "attendees": ["alice@example.com", "bob@example.com"],
    "duration_minutes": 30
  }'
Response includes:
  • score: Quality rating for each slot (0-1)
  • reason: Human-readable explanation
  • Slots automatically sorted by score (best first)

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Understanding Scores

  • 0.9-1.0: Excellent match, highly recommended
  • 0.7-0.9: Good match, solid choice
  • 0.5-0.7: Fair match, acceptable
  • 0.3-0.5: Poor match, avoid if possible
  • 0.0-0.3: Very poor match, last resort

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Best Practices

1. Trust the Rankings 
// Use the first slot - it's ranked best for a reason
const bestSlot = availability.slots[0];
await syncline.schedule({
  attendees: [...],
  start_time: bestSlot.time
});
2. Provide Context 
// Help us understand the meeting type
await syncline.findAvailability({
  attendees: [...],
  meeting_context: 'investor_pitch',  // Affects ranking
  duration_minutes: 60
});
3. Set User Preferences 
// Let users control their scheduling preferences
await syncline.updatePreferences({
  work_hours: { start: 9, end: 17 },
  buffer_minutes: 15,
  max_meetings_per_day: 6
});

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Continuous Improvement

Our algorithm gets smarter over time by learning from:
  • Meeting acceptance rates
  • Reschedule patterns
  • User feedback
  • Seasonal trends
The more your users interact with Syncline, the better the recommendations become.

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Testing the Algorithm

Try it yourself and see the scoring in action: 
curl -X POST https://api.syncline.run/v1/availability \
  -H "X-API-Key: sk_live_..." \
  -d '{
    "attendees": ["alice@example.com", "bob@example.com"],
    "duration_minutes": 30,
    "search_window_days": 7
  }'
Look at the score field in each slot. The algorithm automatically sorts slots with highest scores first.

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Next Steps

Try It Now

See the algorithm in action

API Reference

Full endpoint documentation

User Preferences

Customize scoring behavior

AI Learning

How we improve over time