Indium Software’s data annotation services provide the best-in-class solution for all your training data requirements. Our proven track record, AI enablement, technology expertise and scalable workforce help build high-quality annotations from disparate datasets.
Our machine learning-based data annotation solutions address the modern challenge of generating quality ground truth dataset, which is essential to the success of any project or artificial intelligence model. At Indium, we believe that high-quality annotated and label data combined with machine learning delivers proper and accurate results. We have an experienced team of data scientists who collaborate with our customer’s hand-in-hand throughout the year to generate the desired output.
Indium uses advanced data labeling techniques such as supervised and unsupervised learning, and reinforcement learning to power machine learning and to enhance training data quality.
We leverage AI-based labeling tools such as Labelme, CVAT and more to build, transform, train and test audio, image, video-based content, and other forms of unstructured data.
Annotations on Image, Audio, Video and Text!
Image and Video
Labeling of images in different classes; one label for each image.
Labeling of images in different classes with bounding boxes; multiple labels per image.
Labeling lasso boundaries of real-life objects; different boundaries for different classes of objects.
Labeling lasso boundaries of real-life objects; different boundaries for different classes of objects; differentiate between different instances of same label.
3D Object detection
Draw a 3D bounding box around object of interest.
3D LIDAR Annotation
Tagging X, Y, Z coordinates for LIDAR models.
Labeling tables of interest, pages of interest etc. to train a model to identify them.
Want to do
business with us?
Would you like to speak to one of our technical experts over the phone? Just submit your details and we’ll be in touch shortly. You can also email us at firstname.lastname@example.org if you would prefer.
Label row of data with one class, examples being label ECG data with sleep stage.
Labeling which customer has churned
Time Series Classification/Outlier Detection
Label outliers in time series data.
The Indium Advantage!
Indium has 2+ decades of experience delivering customer-centric solutions to Fortune 100 companies, global enterprises, and innovative product start-ups. We have served 350+ global clients across digital and QA.
We boast of solution accelerators, customer-centric systems and processes and IP-based solutions.
Accuracy with quality
Get Indium’s best-in-class services combining accuracy with quality in image annotation through stages of reviewing and auditing labelled data.
Build AI and Predictive models
Our experienced team of annotators know exactly the data that’s required for advanced analytics as they work closely with our data science teams who build AI and predictive models with different datasets.
Indium provides a fully scalable data annotation solution with a quick turnaround time to fulfil our client’s unique needs and resolve their main issues. Our extended in-house workforce can annotate any volume of images as per client demand.
We are ISO 27001:2013 certified. We follow industry best practices to ensure safety and security of our clients while ensuring compliance with OWASP and security guidelines. We also address the customer’s additional security protocol requirements if any.
Our Domain Expertise
Indium’s data annotation service spans across several key sectors:
Healthcare and Life Sciences
Healthcare and Life Sciences
We deliver widespread applications across each of the abovementioned industries and offer a continuously evolving architecture depending on the latest industry trends and the research requirements. Our annotation formats cover wide-ranging technical and business use cases.
Examples of Data Annotation
Indium has experience with:
- Graphical user interface-based tools such as GATE, Doccano for text data
- Labelme for image data
- AutoML Vision API for images
- We also have experience working with pre-trained models augmented for annotation