Zapdos Labs

Compare with Gemini

How Zapdos compares with Google's Gemini for video analysis

Compare with Gemini

When analyzing video content, Zapdos offers significant advantages over Google's Gemini in several key areas:

Speed

AspectZapdosGemini
Processing TimeUltra-fast, selectively analyzes key segmentsSlow, examines every frame sequentially
Indexing ApproachHorizontal-scalable, parallel processing of sparse frame samplesSequential analysis of entire video
Exploration MethodHuman-like exploration building understanding incrementallyProcesses video from start to finish

Zapdos processes hours of video content in minutes by intelligently sampling key frames and processing them in parallel across distributed workers. Unlike Gemini which processes videos sequentially, Zapdos works like a human explorer - strategically sampling frames to build up an understanding of the video content. This approach mimics how people naturally watch videos, focusing on key moments rather than every single frame. Zapdos only uploads and processes the most relevant frames, making the indexing process dramatically faster and more efficient.

Output Detail - Side by Side Comparison

The most significant difference between Zapdos and Gemini is in the detail and structure of their outputs. While both can provide JSON responses, the depth and precision of Zapdos's output is substantially superior.

Zapdos Output

Zapdos provides rich, structured output with precise spatial information and confidence scores:

{
  "items": [
    {
      "type": "frame",
      "timestamp_ms": 0,
      "id": "8c2dd0f5-6fc4-4689-b494-dc1623e93043",
      "description": "Two men are seated in front of a fireplace, engaged in a conversation. The man on the left is wearing a gray blazer over a blue shirt, while the man on the right is dressed in a black suit with a white shirt. They are seated on wooden chairs, with the man on the left gesturing with his hands as he speaks. The fireplace, which is black and ornate, is adorned with a vase of pink flowers and a painting on the wall behind it.",
      "objects": [
        {
          "label": "person",
          "confidence_score": 0.96044921875,
          "box": [975.0, 324.25, 1669.0, 1071.0]
        },
        {
          "label": "person",
          "confidence_score": 0.9599609375,
          "box": [128.88, 352.75, 724.0, 1071.0]
        },
        {
          "label": "chair",
          "confidence_score": 0.89794921875,
          "box": [122.12, 829.0, 849.5, 1077.0]
        },
        {
          "label": "vase",
          "confidence_score": 0.80029296875,
          "box": [842.0, 134.5, 999.5, 234.38]
        }
      ]
    },
    {
      "type": "segment",
      "summary": {
        "metadata": {
          "title": "Conversation between two men",
          "location": "Indoor setting, possibly a study or living room"
        },
        "observations": {
          "visual": {
            "people": [
              {
                "id": "person1",
                "appearance": "Man on the left, wearing glasses.",
                "clothing": "Gray suit jacket/blazer over a blue shirt with white patterns.",
                "gestures": "Gesturing with hands, hands clasped together, right hand resting on lap, left hand touching chin.",
                "facial_expressions": "Serious, thoughtful.",
                "role": "Speaker/participant in conversation"
              }
            ]
          }
        },
        "timeline": [
          {
            "start_ms": "4079400",
            "end_ms": "6000000",
            "description": "Two men are engaged in a conversation in a room with a fireplace.",
            "actions": ["Conversing", "Listening", "Gesturing"],
            "participants": ["person1", "person2"]
          }
        ]
      }
    }
  ]
}

Key advantages of Zapdos output:

  • Precise Object Location: Each object has exact bounding box coordinates [x1, y1, x2, y2]
  • Confidence Scores: Algorithmically computed, numerical confidence levels for each detection
  • Timestamp Precision: Exact millisecond timestamps for each frame
  • Structured Descriptions: Detailed, consistent formatting
  • Comprehensive Metadata: IDs, types, and other identifiers
  • Temporal Analysis: Segment summaries with timeline breakdowns
  • Detailed Observations: Structured analysis of people, objects, and settings
  • Guaranteed Structure: Zapdos guarantees structured output with specific schema, ensuring consistent data formats

Gemini Output

Gemini provides more general descriptions without spatial precision:

{
  "videoAnalysis": {
    "summary": "A video showing two men having a conversation in a room with a fireplace. They appear to be professionally dressed and engaged in a serious discussion.",
    "objects": [
      "Two men in business attire",
      "Fireplace with decorative elements",
      "Chairs or seating furniture",
      "Interior room setting"
    ],
    "keyMoments": [
      "00:00 - Initial scene with both men present",
      "01:00 - Conversation appears to be ongoing"
    ]
  }
}

Limitations of Gemini output:

  • No Spatial Information: Cannot pinpoint exact object locations
  • No Confidence Metrics: No quantitative measure of detection reliability
  • General Descriptions: Lacks specific details about positioning
  • Limited Structure: Less granular, harder to parse programmatically
  • Inconsistent Formats: Output format may vary between requests, requiring JSON cleaning and parsing
  • No Schema Guarantee: No guaranteed structure, making integration more complex

Explainability & Traceability

Zapdos uses an Entity-Attribute-Value (EAV) model for storing all processed results, which provides:

  • Full Traceability: Every piece of analysis can be traced back to specific frames
  • Extensibility: New analysis types can be added without database schema changes
  • Query Flexibility: Combine traditional filters with vector similarity searches
  • Audit Trail: Complete history of all processing steps

This EAV model allows developers to understand exactly how results were generated and enables advanced querying capabilities that aren't possible with Gemini's black-box approach.

Cost

Zapdos Labs’ video processing pipeline offers a structural advantage over traditional solutions like Gemini, thanks to our intelligent sampling approach.

As more videos are added, our AI agents can revisit and leverage insights from the video archive, further improving efficiency. This means that, at scale, processing costs can be reduced significantly—potentially making Zapdos up to 10× cheaper than conventional full-frame analysis solutions.

Use Cases Comparison

Use CaseZapdosGemini
Video Search✓ Semantic search across thousands of videosLimited to individual video analysis
Content Discovery✓ Find similar scenes across video libraryRequires processing each video individually
Analytics & Insights✓ Structured data for business intelligenceUnstructured text requiring additional processing
Integration✓ REST API, SDK, Database access✓ API only
Custom Workflows✓ Extensible analysis pipelineLimited customization

For organizations that need to process large video libraries, build searchable archives, or integrate video analysis into larger systems, Zapdos provides a more powerful, cost-effective, and developer-friendly solution.