Learning systems since 1993. One platform.
CleanAim® was built by a founder who has been building capture-pair-learn systems since 1993. Backed by years of self-funded R&D.
THE FOUNDER
From enterprise learning to AI governance. The same methodology, applied to a new frontier
Tom E. Killi has been building systems that capture decisions, pair them with outcomes, and enable compound improvement since 1993. The methodology has evolved across four companies. But the core architecture has remained the same.
Where x.hlp paired decisions by people with learning results over days, CleanAim pairs AI decisions with outcomes in milliseconds. The principle is identical. The speed is different.
Prior patents cited from 2001 onward by 50+ patents from Microsoft, Apple, Samsung, IBM and SAP, the last of which went on to acquire the technology. The same methodology is now applied to the most urgent problem in enterprise AI.
THE TECHNOLOGY ASSET
Backed by years of self-funded R&D. The platform, patents, and methodology were built with conviction, not committees.
CleanAim® is a fully self-funded technology asset with clear IP ownership and zero external obligations.
8 patents filed. PCT international phase pending.
1.1M+ lines of production code. 7 LLM providers supported. 93.3% cross-model transfer efficiency (internal testing across Claude, GPT, Gemini and Grok; 250 tasks).
THE DISCOVERY
We pointed our own verification system at our own codebase
Every test passed. CI was green. Health checks said HEALTHY.
Then we pointed our own verification system at our own codebase. And found 4 silently broken data pipelines, 17,952 calibration records that nothing had computed, and 131 mutations where there should have been eleven thousand.
None of this showed up in tests, monitoring, or code review. That discovery became the product.
THE TECHNOLOGY
Numbers that matter
Built, measured, and verified. Not projected.
Self-funded R&D investment
Patents filed (Swiss FIIP)
Lines of production code
LLM providers supported
Cross-model transfer efficiency (internal testing)
Patent citations (Microsoft, Apple, Samsung, IBM, SAP)
FOUNDER & CEO
Tom E. Killi
Founder & CEO
Tom E. Killi has built systems that learn from the prediction-outcome loop since 1993.
In 1996, he founded x.hlp Technologies, which developed capture-pair-learn methodology for enterprise training. The company served 30+ Fortune 500 clients. JP Morgan, Shell, McKinsey, NATO. Before acquisition in 2004. That technology now operates inside SAP.
After a decade in the energy sector building grid analytics and prediction-outcome systems, he founded CleanAim® to apply the same methodology to AI governance. The most urgent reliability problem in enterprise software.
Learning Systems Since
Patent Citations
Fortune 500 Clients
THE MISSION
Proving AI code actually works. Not just that it compiles and passes tests
Most AI governance observes. CleanAim® verifies. We built infrastructure that captures what AI systems actually do, pairs decisions with outcomes, and produces the evidence that compliance requires. Automatically, continuously, and independently of any provider.
APPROACH
How we build
Four architectural principles guide everything we create.
Constitutional
Systems that enforce their own rules. Not guidelines that can be ignored, but architectural constraints that cannot be bypassed.
Compound
Continuous improvement, not one-time optimization. Systems that get better every day through the capture-pair-learn loop.
Portable
Intelligence that survives provider switches. 93.3% cross-model transfer (internal testing) means no vendor lock-in.
Honest
Systems that admit when they don't know. A 98/100 score with explanation is more trustworthy than 100/100 that papers over gaps.
COMPANY
Company facts
See the Research
Explore the evidence behind AI Code Audit. Validated metrics, patent portfolio, and compound learning results.
See the Research