A design element for the webpage. A screenshot demo-ing an annotation interface for speech transcription.

Build and Annotate Massive Datasets. Quickly and Accurately.

AnnotateIt helps you manage your data collection and labeling pipeline with a powerful crowdsourcing platform

A screenshot demo-ing an annotation interface for speech transcription.

BUILT BY RESEARCHERS FROM

The Georgia Tech Logo The University of Michigan Logo

WHAT WE ANNOTATE

AnnotateIt’s verticals include document, speech, image, and NLP.

A frame from the camera of a self-driving vehicle with salient items on the road like traffic lights and other vehicle highlighted
{
  "image": "https://annotate-lab-examples.s3-us-west-1.amazonaws.com/bboxes_1_original.png",
  "dimensions": [640, 480],
  "vehicles": [
    "0": {
      "top_left": [211, 62],
      "size": [82, 61]
    },
    "1": {
      "top_left": [462, 43],
      "size": [88, 64]
    },
    "2": {
      "top_left": [113, 99],
      "size": [71, 63]
    },
    "3": {
      "top_left": [168, 100],
      "size": [88, 60]
    },
    "4": {
      "top_left": [373, 95],
      "size": [101, 72]
    },
    "5": {
      "top_left": [322, 174],
      "size": [85, 63]
    },
    "6": {
      "top_left": [116, 188],
      "size": [81, 57]
    }
  ],
  "lights": [
    "7": {
      "top_left": [122, 257],
      "size": [87, 63]
    },
    "8": {
      "top_left": [0, 327],
      "size": [89, 72]
    },
    "9": {
      "top_left": [227, 336],
      "size": [102, 73]
    }
  ]
}
                            
A satellite image of a parking lot with bounding boxes drawn around each vehicle in the lot
{
  "image": "https://annotate-lab-examples.s3-us-west-1.amazonaws.com/lot_1.png",
  "lat_lon": [33.757477, -84.403346],
  "vehicles": [
    "0": {
      "top_left": [84, 120],
      "size": [12, 33],
      "color": "red",
      "type": "car",
      "angle": 2,
    },
    "1": {
      "top_left": [92, 120],
      "size": [15, 32],
      "color": "black",
      "type": "car",
      "angle": 4,
    },
    "2": {
      "top_left": [105, 119],
      "size": [13, 35],
      "color": "black",
      "type": "car",
      "angle": 6,
    },
    "3": {
      "top_left": [82, 166],
      "size": [17, 42],
      "color": "black",
      "type": "car",
      "angle": 358,
    },
    "4": {
      "top_left": [105, 170],
      "size": [30, 120],
      "color": "black",
      "type": "truck trailer",
      "angle": 1,
    }
  ]
}
                            
A screenshot demo-ing an annotation interface for speech transcription.
A walmart receipt with salient features highlighted and transcribed, like item code, quantity, price, last four digits of the credit card and the address of the store.
{
  "image": "https://annotate-lab-examples.s3-us-west-1.amazonaws.com/rec_1.png",
  "text": [
    "0": {
      "top_left": [84, 120],
      "size": [12, 33],
      "text": "Steam D82 20.00 CARD # 6058120010391266521"
    },
    "1": {
      "top_left": [80, 160],
      "size": [18, 40],
      "text": "Steam D82 20.00 CARD # 605812002931604881"
    },
    "2": {
      "top_left": [89, 190],
      "size": [22, 60],
      "text": "Walmart"
    },
    "3": {
      "top_left": [55, 230],
      "size": [150, 60],
      "text": "404-352-5252 Mgr: JACQUELYN LANG"
    },
    "4": {
      "top_left": [49, 280],
      "size": [32, 84],
      "text": "1801 HOWELL MILL RD NW ATLANTA GA 30318"
    },
    "5": {
      "top_left": [40, 380],
      "size": [12, 120],
      "text": "AMERICAN EXPRESS *** **** ***1 003 I 0"
    }
  ]
}
                

OUR SOLUTIONS

COLLECT AND LABEL TRAINING DATA

AnnotateIt uses a combination of human and machine intelligence to accurately and efficiently label your in-house datasets.

  • Add your own rules and heuristics, or consult with our solutions architects.
  • Optimize the annotation interface with the help of our experienced UX researchers
  • Label partial datasets to bootstrap your models
  • Save on time and redundancy costs with benchmarking and sampling algorithms.
  • Collect and label hard to get data
A diagram showing how AnnotateIt's data collection and labeling workflow works: collect raw data, create a job on the platform, assign the job to labelers and finally get a finished dataset.
HUMAN IN THE LOOP

With a tightly coupled integration, and a network of qualified, on-demand annotators, we augment your training and production artificial intelligence pipelines with human intelligence.

  • Low latency human-machine loops
  • Probabilistic methods to reduce labeling load during training
  • Tight Operations Security for sensitive applications
  • Use customizable SLAs to set label accuracy, latency, and throughput targets that fit within your budget.
A diagram illustrating human in the loop: for low-confidence predictions, a human labeler reviews the annotations and confirms the label or corrects any errors.
MODELS & API

Recruiting and training machine learning scientists and engineers can be expensive. Costs increase manifold if you also need to maintain your training infrastructure.

  • Reduce the start-up time for your machine learning pipelines
  • Cut down on costs for both complex and typical applications.
  • Access the best domain experts for your application
  • Save on hosting and platform costs.
A diagram illustrating AnnotateIt's end-to-end machine learning services. With a tightly coupled training and labeling platform, AnnotateIt can help you deploy your model to the cloud or to edge devices.