Kuanta Engine
Evaluating the transition from MVP to a scalable, Agentic AI architecture for startup analysis.
Built to make a difference.
The MVP Monolith
Initial version was a tightly coupled application with synchronous processing. Functional but struggled with LLM timeout issues and was difficult to extend.
The Strategic Pivot
Architected a Modular Monolith — decoupled analysis logic from the API layer and introduced async task queues to handle intensive AI workloads.
Agentic Architecture
Moved to an Agent-based approach. Specialized agents (Team, Finance, Market) run independently, orchestrated by a central engine for parallel processing.
Core features.
Everything built into Kuanta Engine — no add-ons required.
Specialized AI Agents
A suite of focused agents (Team, Finance, Market, etc.) that specialize in analyzing specific aspects of a startup pitch deck.
Async Orchestration
Built on Celery and Redis to handle long-running AI tasks asynchronously, preventing timeouts and ensuring system stability.
Real-time Progress
WebSocket integration allows users to see detailed analysis progress in real-time as different agents complete their tasks.
Modular Monolith
A structured architectural approach that balances the simplicity of a monolith with the flexibility of microservices.
Unified Data Layer
Seamless integration with existing databases (MongoDB) to fetch deck_metadata and store structured agent results.
Multi-LLM Support
Flexible AI core capable of switching between models (Gemini 2.0, OpenAI) for optimized performance and cost.
Built with.
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