We Solve the “Learning Gap” That Kills 95% of AI Projects
At ArtiQuare, we don’t build generic AI tools. We solve Operational Knowledge Decay – the systematic loss of expertise that makes enterprise AI brittle and unreliable.
MIT’s 2025 research confirmed what we’ve seen across 300,000+ industrial tickets: 95% of AI pilots fail because they operate on incomplete, chaotic data. The successful 5% solve deep operational problems with systems that actually learn from messy reality.
The Problem We Actually Solve
Your most valuable asset – the complete history of every problem your organization has solved – is trapped in what we call “data graveyards.” Jira tickets marked “done” with no context. Confluence pages that answer yesterday’s questions. Expert knowledge locked in heads that walk out the door.
This isn’t just inefficiency. In high-stakes industrial environments, a single hour of downtime can cost $2.3 million (Siemens, 2024). The cost of not finding the right answer, right now.
Our Approach: The Knowledge Refinery
We developed Cognitive Agentic Architecture (CAA) – a systematic approach to excavating your operational knowledge and turning it into structured, actionable intelligence. Not another chatbot searching dead documentation, but a learning system that discovers the hidden patterns driving your business.
Our R&D has earned BSFZ certification from the German government, validating our systematic approach to solving the enterprise AI reliability problem. Months later, NVIDIA published similar architectural principles in their “Code Agency” research – confirming the direction we’ve been building toward.
Built by People Who Understand Industrial Reality
Our team combines deep enterprise experience with active research in operational knowledge automation. We’ve worked with global industrial leaders and understand that real-world operations don’t fit textbook workflows.
We specialize in:
- Systematic knowledge excavation from operational chaos
- Pattern discovery in industrial ticket histories
- Risk-managed automation that integrates into existing workflows
- BSFZ-certified R&D in enterprise AI reliability
The Diagnostic-First Difference
We don’t start with solutions. We start with systematic diagnosis. Our Friction Audit excavates your data graveyard, discovers the hidden workflow patterns, and delivers a ranked, data-backed roadmap for automation that actually works.
MIT found that partnering with specialized vendors doubles AI deployment success. We’re not generalists trying to solve everything – we’re specialists who understand why AI fails and how to build systems that learn.
Our Partners
