Alastor
Powerful computer agents are still far too complicated to set up, and unreliable to use. Alastor is our answer. In stealth.
An independent AI lab. We ship tools, publish research, and run exploratory experiments.
Powerful computer agents are still far too complicated to set up, and unreliable to use. Alastor is our answer. In stealth.
Hypothesize-and-verify architecture for reducing LLM hallucination. Extracts claims, routes them to verifiers, and accumulates a verified cache over time.
Open-source CLI that generates and maintains repository context for AI coding assistants.
A multi-agent system that researches financial markets. It generates hypotheses, runs quantitative experiments against market data, and surfaces the findings that survive independent meta-review.
An autonomous multi-agent loop that probes the structure of the Voynich Manuscript end to end. It ran over 600 corpus-statistical experiments and over 5400 cipher-mechanism simulations, and it surfaced novel findings.
A methodology for refining repo-level guidance via synthetic bug-fix probes; raises SWE-bench Verified resolve rate to 33.0% from a 25.5% unguided baseline over 4 trials, with gains driven by coverage rather than precision, plus evidence of cross-model degradation.
Read →A companion to probe-and-refine: can comparable guidance be assembled without ever tuning on the target repo? Mining transferable edits from 50 external repositories yields guidance that resolves 45.4% of SWE-bench Verified vs. 39.6% baseline.
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