Glas Intelligence
Scenario intelligence for strategic decision-making
Multi-agent AI simulation that shows how complex stakeholder situations evolve. Describe a scenario; the engine models the most relevant actors across critical decision points.
Glas Intelligence
Multi-agent AI simulation that shows how complex stakeholder situations evolve. Describe a scenario; the engine models the most relevant actors across critical decision points.
A regulation change, market shift, or operational shock. One prompt starts the run.
Source documents are turned into entities and relationships the agents can reason over.
Stakeholder agents react across decision rounds. You get a structured analysis, not a vibe.
This is a frozen report from a real Glas run. The live simulation stack is not on this site. An interviewer can read the artifact without an account.
Stakeholder narratives, access risk, and system strain after a consultation payment cap. Recorded output from the engine.
Open the report →How suppliers, regulators, and consumers react to deregulated pricing over successive rounds.
Example scenarioBanks, fintechs, and supervisors adapting to new capital rules over 18 months.
Example scenarioGlas Intelligence is a product by Sam McDonnell: Vue frontend, Flask API, OASIS multi-agent simulation, GraphRAG, Supabase. This public site is a static demo for interviews. The full engine is in the GitHub repo.