Aalekh - A Solution Space Map Visualizer - AI Tinkerers - New York City Hackathon
AI Tinkerers - New York City
Hackathon Showcase

Aalekh - A Solution Space Map Visualizer

Team of Stony Brook MS Data Science builders with experience at Deloitte, Oracle, and KPMG, specializing in RAG, agentic workflows, GNNs, and multimodal AI systems.

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Aalekh — A Solution Space Map Visualizer

Aalekh is a spatial, timeline-driven reasoning experience that turns conversation into an explorable map of decisions. Instead of placing Claude inside a standard chat window, Aalekh makes the interface itself the innovation: users don’t just read answers—they manipulate Claude’s thinking as a living structure.

A session begins with a single problem statement. Aalekh then runs a focused interrogation loop across five constraint dimensions (resources, timeline, risk tolerance, market, founder context). Each user answer visibly “constructs” the solution space: constraint chips appear on the canvas, the map transitions through a fog-to-clarity system, and the experience culminates in an ignition moment where Claude generates a full node tree (12–15 nodes) with hierarchy, conflicts, explanations, and spatial positioning. This output isn’t a static visualization—Claude’s reasoning drives the schema that the UI renders in real time.

Prototype stability comes from a strict separation of concerns and defensive execution. Phase 1 (backend brain) uses LangGraph to model Claude’s work as discrete reasoning nodes (interrogator, map generator, expander, fork regenerator) operating over a canonical state object. Redis persists the session state and stores map snapshots per timeline index, enabling instant rewind and branch switching without recomputing. Every Claude response is schema-validated; malformed JSON triggers a controlled retry and graceful fallback.

Phase 2 (frontend experience) uses CopilotKit for real-time state sync (useCoAgent) and human-in-the-loop confirmation (renderAndWait). Aalekh shatters UI conventions through playful interaction: a timeline scrubber rewinds reasoning like video editing, and forking lets users branch alternate realities from earlier answers—making exploration the core loop, not chatting.

Technologies, Frameworks, Libraries:

Claude Sonnet via Anthropic API

LangGraph (Python) + LangChain

Redis (session persistence + snapshot versioning)

CopilotKit (useCoAgent, useCopilotAction, useCoAgentStateRender)

Next.js (frontend + runtime API routes)

React

SVG (edges/graph connections)

CSS transitions + keyframes (fog, ignition, panel choreography)

Anthropic CSS transitions + keyframes (fog CopilotKit CopilotKit (useCoAgent LangGraph (Python) + LangChain Next.js (frontend + runtime API routes) React Redis Redis (session persistence + snapshot versioning) SVG (edges/graph connections) ignition panel choreography) useCoAgentStateRender) useCopilotAction

Github Repo with all our code

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