Services
Data labelling and data operations delivered as a managed service: scoped with you, produced by trained teams and reviewed before anything reaches you.
Our services
Choose a service by the kind of data you hold, or read how a project is delivered. Each page lists the tasks we actually offer, how quality is checked and what a sample output looks like. The examples below come from programmes already described on this site.
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Annotated image, video, 3D and LiDAR data, from first-pass labelling to QA and correction of existing datasets.
- Boxes, polygons, segmentation, lines, keypoints and pose — used on programmes such as PPE compliance, workplace pose and workplace objects.
- Video and fisheye CCTV work, including queue head detection, retail surveillance, and published mass-transit masks and belongings.
- Instance segmentation for waste-stream classification, plus published identification work such as Japanese telephone poles.
- 3D and point-cloud annotation, from the published neuron and axon project to LiDAR QA and correction on MCAP data as used with Foxglove.
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Annotated text and audio for language and speech models: classification, transcription, utterance collection, extraction and sentiment.
- Sentiment annotation, as in the published COVID sentiment story from tweets and Facebook posts.
- Audio classification, as in the published herding-dog audio project — tagging short recordings such as barking, howling, growling or silence.
- Transcription, utterance collection and entity extraction, scoped against written guidelines and reviewed before delivery.
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Data operations beyond annotation, run by a managed team with review built in, either alongside labelling or as a standalone piece of work.
- Data entry, cleansing and enrichment: capturing, correcting and standardising records.
- Auditing, QA and model validation: checking existing datasets or model outputs against your rules, including correction of labels produced elsewhere.
- Data engineering and ETL, so labelled or cleaned data is delivered in a form ready for training or analysis.
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Every project follows the same four stages, agreed with you before production starts.
- Scope and taxonomy: the classes, attributes and edge cases, written into guidelines.
- Calibration: annotators are checked against your edge cases before volume increases.
- Production, review, acceptance and export, with review built into the work rather than added at the end.
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The tools, formats and quality method we use to hand work back, including LiDAR workflows.
- Delivery in the tool and format agreed for your project, from your own platform to standard export formats.
- LiDAR and multi-sensor handling, including MCAP data as used with Foxglove.
- A documented review method, so you can see how quality is checked before acceptance.
Request a Project Quote
Not sure which service fits, or does your project span more than one? Describe the data and the outcome you need, and we will advise on the right combination.