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About 3Lc Ai
What is 3Lc Ai?
3Lc Ai is a data-quality layer for AI training, specifically for physical and industrial AI applications. It gives per-sample, per-epoch visibility inside your existing training loop. Using just three lines of Python, it integrates with PyTorch, TensorFlow, Ultralytics YOLO, HuggingFace, and SAM, without rewriting your model or dataloaders. It surfaces mislabels, edge cases, and drift, enabling you to curate, edit, and retrain immediately.
Why use 3Lc Ai?
Computer-vision AI is often bottlenecked by data, not the model. Mislabels and noise hide in plain sight, domain shift breaks deployed models, and adding more data often adds little. 3Lc Ai solves these by letting you view each sample's contribution to model error, rank problematic samples, and fix them. It runs air-gapped, on-premise, or cloud-native, ensuring your data never leaves your infrastructure.
Who is 3Lc Ai for?
It is designed for data scientists and AI engineers working in energy, aerospace, agriculture, and industrial automation. It's for teams that need to improve model accuracy in production, reduce training data requirements, and shorten iteration cycles. It is not for hobbyists or those seeking a low-code solution; it requires coding skills and integrates with existing Python-based workflows.
Key features
- Per-sample metrics — View every sample's contribution to model error, surfacing mislabels and edge cases.
- Three-line integration — Add data quality monitoring to your existing training loop with minimal code changes.
- Data curation — Browse, filter, fix labels, weight samples, and retrain immediately to accelerate improvement.
- Deployment flexibility — Runs air-gapped, on-premise, or cloud-native, ensuring data security and compliance.
- Audit lineage — Full lineage tracking for every data change, essential for regulated industries.
- Framework support — Compatible with PyTorch, TensorFlow, Ultralytics YOLO, HuggingFace, and SAM.
SaaSpartout Score
7.1
/10
Editorial score from our review methodology — not user ratings.
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3Lc Ai Pricing
3Lc Ai pricing: Custom pricing based on team size and deployment.
For comparison: the median starting price in AI Other is $19/month, measured across 206 tools we track. See the full SaaS Pricing Index →
Proof of Concept (PoC)
Costs one user license for a 2–4 week engagement, with daily 10-minute touchpoints to validate value on your data.
Annual License
After a successful PoC, move to annual pricing sized to your team headcount, deployment topology (on-prem or air-gapped), and support requirements. Every customer gets the full platform from day one.
Free SDK
Individual developers can freely install the SDK from PyPI for experimentation.
Frequently asked questions
How much does 3Lc Ai cost?
3Lc Ai does not publish public pricing. It offers a paid Proof of Concept (2-4 weeks) that costs one user license, followed by annual licensing based on your team size, deployment, and support needs. An SDK is freely available for individual developers.
Is there a free trial of 3Lc Ai?
Yes, for individual developers, the SDK is freely installable from PyPI for experimentation. For teams, the PoC engagement serves as a trial, costing one user license.
Who is 3Lc Ai best for?
It is best for data scientists and AI engineers in physical and industrial AI domains—such as energy, aerospace, agriculture, and manufacturing—who need to improve model accuracy by curating training data.
How does 3Lc Ai work?
3Lc Ai integrates into your existing training loop with three lines of Python. It collects per-sample metrics (like loss and confidence) during one inference pass, then lets you view, filter, and fix data issues, and retrain instantly.
What are the top alternatives to 3Lc Ai?
Alternatives include data-centric AI platforms like Labelbox, Scale AI, and Snorkel, which focus on data labeling and management. However, 3Lc Ai's unique per-epoch visibility and integration into the training loop set it apart.
What is the main limitation of 3Lc Ai?
The main limitation is that it requires coding knowledge and is not a no-code solution. It is specifically tailored for computer vision tasks, so general-purpose AI or NLP teams may not find it suitable.
