ML and AI programs need high quality data at scale to realistically improve efficiency. Computer vision is closing the gap between real word images and perceived images captured by cameras.
We have significant expertise to initiate, create, and deliver a variety of data collection initiatives in the areas of verbal speech, human gestures, and inanimate objects and spaces.
This capability mitigates time and budget constraints.
We have deep experience in capturing granular behavioral data to tune the user experience for selective demographics, age groups, geographical locations and cultures.
Our team develops innovative solutions for capturing ground truth data for various objects including documents, media and an array of everyday and unique items.
Our team has innovative solutions for simulating real world scenarios that include a combination of spaces, human actors, real world objects and locations.
We are experts in developing international initiatives for capture of high-resolution spatial data in homes, offices, and public spaces.
We have extensive experience running initiatives of varied scale to capture accents, dialects, speech patterns and other speech behaviors for NLG, NLP and speech recognition applications.
The importance of data to be collected at scale is tantamount to any collection engagements and the scaling must be properly managed to be usable for ML and AI programs.
We believe that appropriate data management at all stages including ingestion, triage, tagging and annotation certifies the programs get the most from any data collection effort.
For any data collection program to be successful, the quality of output is key to its success. Lessons learned in the collection process often lead to changes in data requirements, e.g. requiring new information or prioritizing it in a different way.
Our corporate mission is a focus on Quality, and we have built processes and practices to ensure that we deliver the highest quality of data at every stage of the data collection and annotation process.
“Garbage in-garbage out” is a classic phrase suggesting the cleaner the data, the better the results. Because data purity starts at the point of collection, we establish the proper data intake and processing parameters, monitoring data collection in real time to ensure it is accurately validated, prioritized, and dispatched in the QA process.
Data Tagging and Annotation
Tagging and annotation is a critical stage to ensure that data is properly labeled so machine algorithms can actually “learn.” We work with you to determine the best tagging paradigms based on data types including text, audio, and computer vision images and video. Our teams constantly monitor the gathered data to confirm it precisely meets your quality requirements. Our objective is to provide data to be used instantly without additional analysis or manipulation; whether leveraging software tools, or performing manual analysis to ensure accuracy, or some combination of both approaches.
Automated Annotation Tools
Our QSmartTag™ software leverages advanced AI-powered deep learning technology that enables automated image labeling to improve speed and accuracy. The software is capable of producing ground truth from a range of sensor data sets, including cameras, Lidar and radar data. QSmartTag handles 2D, 3D, and fused data, sequences or single frame, with capabilities ranging from 3D bounding boxes to 3D point level segmentation. It does not require API connectivity to source data systems and can annotate data in the cloud or securely to dedicated in-house servers. Our highly-skilled human workforce then refines the tagging to ensure complete accuracy and precision.
Triaging data can be a tricky process. Lessons learned in the process often lead to changes in data requirements, e.g. requiring new information or prioritizing it a different way. Our experts verify your most important data in any domain - including multi-lingual triage for speech data, efficient grading of human gestures, or accurate recognition of spaces and objects - to ensure that your user experience is optimal and continually improves.
Our Mission is a Focus on Quality
We have built processes and practices to ensure that we deliver the highest quality of data at every stage of the collection and management process.
THE Q ANALYSTS DIFFERENCE
Running a good data collection and ingestion program requires considerable expertise in creating an optimized solution for each business situation. There is no global “one size fits all” solution. This is where our years of experience in running programs for some of the leading AI firms in the world can help you deliver the right data on time and within budget.
Globally Experienced Teams
We have global expertise in delivering data collection and management initiatives from precision to mass scale for speech, humans and spaces. We have developed optimized methodologies and approaches to run global programs to collect, manage, triage, tag and annotate data needed for sophisticated AI based products in the world of Augmented Reality, Virtual Reality and Mixed Reality, 2D and 3D Maps, speech assistance, and other future tech products.
Crowd sourcing platforms may seem simple to use but running an effective program takes significant expertise in knowing how to design the appropriate instrument and monitor it for bots and other “bad actors” and iterate to improve final outcomes. We have expertise in designing, creating, and running programs utilizing commercial crowd sourcing platforms with the appropriate oversight to ensure targeted participation and a favorable outcome.
Flexible Delivery Options
We offer a range of delivery options leveraging our global workforce. Any element of our Ground Truth Data Services can be delivered via a combination of onsite at a client facility, offsite at our dedicated Q TestLab facilities in Kirkland, Washington, offshore at our dedicated facilities in Bangalore, India, or through our global partner ecosystem. Our processes are designed to offer a seamless solution to our Client’s regardless of delivery location.