BrinqAI x 42T: Automated line clearance.
Working with 42 Technology, Synaptics and Balluff, BrinqAI built an edge-AI demonstrator that automates pharmaceutical line clearance — replacing a manual paper-based check with up to 85% time savings per changeover.
Line Clearance: Too important to do manually
Every idle minute on a production line costs money. Yet before manufacturing can restart, every part of the line must be inspected — an essential but slow and detailed process. In pharmaceutical manufacturing, line clearance — confirming no materials from the previous batch remain — is critical for product integrity and regulatory compliance, yet it stays inefficient, labour-intensive and one of the largest drags on OEE (Overall Equipment Effectiveness).
Existing automated solutions fall short on speed, complexity and cost, limiting real adoption. A new era of AI-driven automation is emerging.
BrinqAI partnered with 42 Technology, Synaptics and Balluff to build the Edge AI Line Clearance Demonstrator — a working proof-of-concept that runs the entire check on the edge. It pairs the Synaptics Astra™ IoT platform and Balluff industrial imaging with BrinqAI's vision models and MLOps tooling, plus 42T's industrial engineering: real-time object and anomaly detection, built for the production floor.
Non-negotiable under GMP (Good Manufacturing Practices).
Inadequate line clearance is consistently cited as a leading root cause of cross-contamination and mislabeling recalls — and missed checks lead to recalls, consent decrees and shutdowns.
Manual line clearance is repetitive, fatiguing and subjective — the conditions under which human inspection is least reliable.
BrinqAI's edge-AI platform closes that gap: an objective inspector that runs continuously, produces a digital evidence trail, and fits the GMP procedures plants already follow.
What manual checks miss.
Cross-contamination
Previous batch residues mix with the next — a leading cause of pharmaceutical recalls.
Residual product
Leftover material goes unnoticed during a manual sweep.
Mislabeled components
Wrong labels or packaging are applied to a run.
Late component swaps
Wrong components introduced after sign-off, with no live verification.
Deep learning that trains itself — on the line.
The new AI-powered approach combines BrinqAI's deep-learning models with Balluff's high-performance image acquisition system and the Synaptics Astra™ SL1680 edge AI processor.
A key limitation of existing automated solutions is the need for extensive on-site training of their machine-learning models at multiple points on live production lines. This platform eliminates that requirement by using deep learning as a stand-alone method for continuous model improvement — a fully automatic process where datasets are developed in real time.
The system's embedded intelligence compensates for variables such as shadows and changing light conditions, while its self-learning capability continuously improves accuracy and reliability during real-time operation — further boosting production efficiencies for pharmaceutical manufacturers.
With some pharmaceutical manufacturers operating up to 100 production lines with 20 or more cameras on each, cost and complexity have been the major barriers to automating line clearance. These solutions promise a real breakthrough.
Built for pharma's cost and performance requirements, the same approach extends to other industries — medical devices and food & beverage. Fixed-position cameras handle key monitoring points, with flexibility for pan-and-tilt cameras to scan wider production areas as the application demands.
A working Line Clearance System, built end-to-end in the 42T labs with BrinqAI.
A Balluff industrial camera images each pill as it passes. AcuSight by BrinqAI models classify the scene on the Synaptics Astra edge device.
The full BrinqAI x 42T technology demonstrator in the 42 Technology development labs.
BrinqAI led the AI side, end to end.
Data strategy, model training, on-device deployment and continuous monitoring — shaped by direct input from leading pharmaceutical manufacturers, so each detection class maps to a real GMP requirement.
- 01Vision pipeline architecture & embedded model design
- 02On-device deep-learning training & optimisation
- 03Continuous MLOps loop for retraining and monitoring
- 04Real-time inference & alerting on the Astra device
- 05GMP-aligned event logging & visual audit trail
- 06Integration with Balluff imaging and 42T mechanical rig
Capture. Infer. Verify.
Capture
A Balluff industrial camera images each pill as it passes. AcuSight by BrinqAI models classify the scene on the Synaptics Astra edge device.
BrinqAI detecting line-clear, in-use and anomaly states on a simulated pharma conveyor.
Infer
BrinqAI's models run directly on the Synaptics Astra™ edge SoC. Five concurrent checks, no cloud round-trip, no extra compute hardware.
Pill and bottle inspection on the same edge stack — one model family, multiple SKUs.
Verify
Operators see a live CLEAR / NOT-CLEAR verdict with timestamped imagery, replacing a paper sign-off with a digital audit trail.
Defect and anomaly detection — heat-seal integrity flagged in real time on the same edge stack.
Five concurrent checks. One edge device.
Pills move along the conveyor and are imaged by the Balluff camera. BrinqAI's embedded models, running on the Astra device, perform five checks in real time:
Line Clearance
Detect material on the line, plus line-in-use and line-clear states.
Materials Analysis
Detect, count and measure flow rate of material under inspection.
Anomaly Detection
Flag foreign or unknown material that doesn't belong on the line.
Contaminant Detection
Identify the wrong material running on the line.
Defect Detection
Identify material that does not meet quality standards.
What changes on the line.
Automated verification doesn't just speed up clearance — it changes the economics, risk profile and audit posture of the packaging hall.
Consistent accuracy
Removes operator fatigue and subjective judgment from a check that runs on every changeover.
Lower recall risk
Catches cross-contamination and mislabeling before product leaves the line.
Faster changeovers
Replaces a paper checklist with seconds of automated verification — more line time, more output.
Built-in evidence
Every check produces a timestamped image record, ready for GMP and regulator audits.
Measurable by design.
Across multiple inspection points on a single line, the BrinqAI approach delivers up to 85% time savings versus the manual process — with a complete visual audit trail for every changeover.
Built by four teams, for one production line.
BrinqAI's edge-AI platform combined with Synaptics silicon, Balluff vision hardware and 42T systems engineering — aimed at a real pharmaceutical production challenge.
)'%20height='31.220082866195465px'%20id='yifxQ20wP'%20transform='translate(0%200)'%20width='71.81477570353618px'%3e%3c/path%3e%3c/svg%3e)
From demonstrator to production line.
The demonstrator is designed for scalable rollout. Next steps focus on integration depth and on-prem training.
- 01Integration with existing automation and industrial PLC systems
- 02On-premises model training for plant-specific SKUs
- 03Support for a wider range of imaging hardware and line speeds
See it on your line.
If you own OEE, quality or compliance in a pharma or food & beverage production environment, we'll run a live demo on your data.