Using the power of AI and computational analytics in service of the UFO phenomenon.
Every great analytical leap in ufology began with someone who refused to read cases one at a time. Two of them made this page possible.
1958 · THE SPATIAL INSTINCT
Aimé Michel
During the great French wave of autumn 1954, hundreds of reports arrived in only a few weeks. The writer and science journalist Aimé Michel plotted them on maps. In Flying Saucers and the Straight-Line Mystery (1958), he argued that sightings on the same day fell along straight lines. He called this orthoteny. Its most famous example was the so-called BAVIC line from Bayonne to Vichy.
Later statisticians showed that such alignments appear by chance in dense data, so orthoteny did not hold up. But the idea behind it did. Michel moved the question from "what did this witness see?" to "what shape does the whole wave make?" That change in method is the starting point of UFO analytics.
1960s–1970s · THE COMPUTATIONAL TURN
Jacques Vallée
Jacques Vallée was trained in astronomy and computer science, and he corresponded with Michel. He took the next step: he put case data into a computer. Working with J. Allen Hynek, he built early machine-readable sighting catalogues. In Passport to Magonia (1969), he published a chronological catalogue of 923 landing reports.
With these catalogues he studied waves over time, daily timing patterns and a striking "law of the times," where reports rise late at night when few people are awake to see them. He concluded that the phenomenon could only be understood in aggregate, across cultures and centuries, and not through any single dramatic case. This lab is built on that idea.
Michel had maps and pins. Vallée had punch cards and mainframes. Today, curated archives, language models and modern statistics let us continue their work at a scale they could only imagine, using the same discipline about what the numbers can and cannot show.
MICHA'S DREAM
A lifetime's idea, finally within reach
Years ago, on the original Blogger site, Micha Verg imagined an archive that could hold every case at once and reveal the patterns no single researcher could see. With the computers of the day it seemed a lifetime's labour. AI-assisted analysis makes that dream practical: this is where it begins.
— Micha Verg, Curator
PROTOTYPE · 12 ILLUSTRATIVE SAMPLE RECORDS · NOT STATISTICAL FINDINGS
Reports by decade
1940s1
1950s2
1960s2
1970s2
1980s2
1990s1
2000s1
2010s1
Reported shape
Disc3
Light2
Ovoid2
Triangle3
Tic Tac1
Sphere1
Sensor corroboration
Single-sensor3
Multi-sensor9
Region
North America7
Europe3
Oceania1
Middle East1
What comes next
Once the structured case database is populated, these charts will draw from documented, sourced records, with sample sizes, provenance and reporting bias stated beside every graph. VCM and VAM scores will become additional analytic dimensions.