Brimit helpt organisaties het potentieel van data en AI te benutten door oplossingen te leveren die operaties verbeteren, kosten verlagen en resultaten verbeteren—brancheoverschrijdend en over alle bedrijfsfuncties heen.
WHAT WE DO
Defining the visual task, target action, success metric, and acceptable error level before any model work begins. Computer vision covers a wide range—classification, object detection, segmentation, OCR, tracking, document understanding, and video analytics. Each requires different data, validation, and integration. Getting the scope right prevents building the wrong solution.
Developing and validating models for classification, detection, segmentation, OCR, tracking, or video event recognition. Validation covers accuracy, false positives, false negatives, edge cases, processing speed, and human review needs—judged against the business process, not just a lab metric.
Starting with one line, product family, document type, camera feed, or visual task. The pilot validates data quality, model performance, workflow fit, and business value—with monitoring, retraining, and support included because visual conditions change over time.
Reviewing camera setup, lighting, image quality, sampling strategy, annotation approach, labeling consistency, privacy constraints, edge or cloud processing decisions, and dataset governance. In many operational environments, data capture quality matters as much as model choice.
Building baselines, testing modeling approaches, fine-tuning LLMs where appropriate, and analyzing errors. Evaluation covers metrics, edge cases, explainability, confidence thresholds, latency, and cost—translated into business risk and value, not just technical scores.
Building baselines, testing modeling approaches, fine-tuning LLMs where appropriate, and analyzing errors. Evaluation covers metrics, edge cases, explainability, confidence thresholds, latency, and cost—translated into business risk and value, not just technical scores.
