ASPL Blog
Insights on physical AI, training data, engineering AI and agentic AI.
2026-09-30
How to Choose a Data Labeling Platform for Enterprise AI Projects
A practical guide to evaluating a data labeling platform for enterprise AI projects: annotation capabilities, AI assistance, human review, and security.
2026-09-29
How AI Can Help Manufacturers Find Cost Savings Hidden in Engineering Drawings
Engineering drawing AI reads tolerances, materials, and geometry to surface pricing mismatches, duplicate parts, and sourcing risk manufacturers can't find manually.
2026-09-09
How Do You Extract Information From Engineering Drawings Using AI?
AI can extract part numbers, materials, tolerances, and GD&T from engineering drawings, turning them into searchable, structured data.
2026-08-29
Arena PLM Alternatives: How SourceOptima Bridges the Engineering Drawing Intelligence Gap
Explore Arena PLM alternatives and see how SourceOptima adds engineering drawing intelligence to PLM for smarter cost analysis and sourcing decisions.
2026-08-01
Agentic AI in Manufacturing: Real Use Cases
Agentic AI in manufacturing goes beyond chatbots. Real use cases: procurement AI, engineering drawings, supply chain, and how ASPL helps you deploy AI
2026-07-19
What Are Geospatial Annotation Services? A Complete Guide for AI, GIS and ADAS Projects
Learn what geospatial annotation services are, including LiDAR annotation, HD map annotation, satellite imagery, GIS annotation, and geospatial data labeling workflows.
2026-06-25
Agentic AI Evaluation: Why Agents Stall Before Production
Most AI agents never reach production. See why evaluation, not model quality, decides whether your agentic AI system succeeds.
2026-06-14
RAG Pipeline for Proposal Automation: Hybrid Retrieval, HyDE, and Reranking
A practical guide to building a production RAG pipeline for proposal automation using hybrid retrieval (BM25 + vector), HyDE, RRF, cross-encoder reranking, and faithfulness scoring.
2026-05-16
From Pixels to Parcels: A Practical Guide to GIS Annotation
Geospatial data annotation is the invisible backbone of autonomous vehicles, smart cities, and precision agriculture. Here's how it works — and why it's harder than it looks.
2025-02-12
Multimodal Data Annotation for Automotive: A Practical Guide
How multimodal data annotation for automotive ML powers ADAS and autonomous driving — sensor fusion, LiDAR, QA workflows, and ROI explained.
2025-01-29
ADLC — Building AI That Works: The Agent Development Lifecycle Guide
ADLC — Building AI That Works explains the Agent Development Lifecycle, its six phases, and why data annotation is the foundation of reliable agentic AI.