An agentic research tool that automatically transforms complex real-world events into interactive, cross-domain causal graphs using a multi-agent ai pipeline and a custom flutter canvas.
what makes it unique: the "surprise link" mechanics: unlike standard search tools or llms that dump flat summaries, aftermath specifically uses a dedicated synthesis agent to map hidden, non-obvious cross-domain dependencies (like connecting agricultural shifts directly to public discourse changes). a mathematically grounded custom canvas: it completely skips rigid, cookie-cutter layout engines to build a custom custompainter graph canvas from scratch, utilizing an organic ellipse-spread layout with seeded jitter so that massive data structures read like natural, interconnected thoughts rather than mechanical flowcharts. production-grade multi-agent topology: it moves past typical prompt-and-pray structures by isolating 12 separate domains into parallel, sandboxed agent specialists with pydantic constraint caps and distinct failure mode error routing, proving that complex ai pipelines can be engineered with strict predictability.