AI & Computer Vision
Turn visual information into software decisions.
We build computer-vision and intelligent processing systems that transform images, video, and visual application data into structured, actionable information.
PiBert develops computer-vision and intelligent processing workflows for applications where software needs to detect, recognize, extract, classify, or respond to information contained in images and video.
From real-time recognition and OCR to application-screen analysis and automated visual validation, we combine vision models, image processing, and application logic to build complete operational systems—not isolated model demonstrations.
Discuss a vision problem- InputReady
- DetectionComplete
- Quality / PreprocessGood
- AnalysisContext applied
- ValidationComplete
- DecisionValidated
{ type: "visual_event", state: "validated" }Visual processing connected to application behavior.
Vision systems can combine inputs, models, validation, historical context, and application rules to produce structured results.
Computer Vision Systems
Build pipelines that detect, analyze, track, or classify visual information from images, video streams, cameras, and application interfaces.
Face Detection & Recognition
Develop recognition workflows incorporating face detection, embeddings, similarity matching, tracking, confidence handling, and controlled unknown-person processing.
OCR & Visual Data Extraction
Extract useful information from screenshots, documents, application interfaces, labels, prices, statuses, and other visual sources using OCR combined with image preprocessing and validation.
Real-Time Video Processing
Process camera and video streams with detection, tracking, recognition, event handling, and downstream application integration.
Visual Application Intelligence
Analyze application screenshots and interface regions to detect states, extract values, validate UI information, and provide structured results to automation systems.
Model & Rule Integration
Combine model predictions with thresholds, business rules, historical observations, validation, and application state so decisions are based on more than a single inference result.
From model output to reliable application behavior
A prediction alone is rarely the finished system. PiBert combines detection and inference with preprocessing, confidence handling, temporal context, validation, state management, and application logic to turn visual signals into dependable software behavior.
- 01Visual Input
- 02Preprocess
- 03Detect / Extract
- 04Analyze
- 05Validate
- 06Decision / Event
- 07Structured Output
From interface region to structured value.
A detected region is prepared for OCR, interpreted, validated, and converted into application data.
- Region detection
- OCR
- Validation
eta: 7
unit: "min"Confidence needs context.
Real-world vision systems operate with imperfect frames, changing lighting, motion, partial visibility, varying object sizes, and uncertain predictions.
Instead of treating every model result as absolute, PiBert systems can combine confidence thresholds, repeated observations, quality checks, tracking history, and domain rules before producing a final event or decision.
Where visual processing fits.
- Real-time camera analysis
- Face recognition workflows
- Unknown-person detection
- OCR and text extraction
- Application screenshot analysis
- Automated visual validation
- UI-state detection
- Image classification
- Video-stream processing
- Visual monitoring systems
- Data extraction from images
- Vision-assisted automation
Tools selected for the system.
Models, inference runtimes, preprocessing techniques, and thresholds are selected according to the visual problem, latency requirements, deployment environment, and required level of validation.
Have images, video, or application screens that software needs to understand?
Bring PiBert the visual-processing problem, its operating conditions, and the decisions the system needs to support.