The Open-Source Microservices Framework for Narrative Intelligence and Story Engineering.
FountainAI is a sophisticated, open-source microservices ecosystem designed for the high-fidelity management of narrative data and creative workflows. Positioned for the 2026 agentic economy, FountainAI treats stories not as static documents, but as dynamic, interconnected data structures. The architecture is built on FastAPI and follows a strict OpenAPI 3.1 specification, enabling seamless integration with LLM-driven agents. Its core philosophy revolves around 'Hypermedia as the Engine of Application State' (HATEOAS), ensuring that every narrative element—from character arcs to specific dialogue snippets—is addressable and verifiable via unique URIs. This framework solves the consistency problem in generative AI by providing a 'Source of Truth' for plot logic, character traits, and sequence timing. For enterprise creative studios, FountainAI offers a modular backend to automate script breakdowns, maintain continuity across vast cinematic universes, and orchestrate complex storytelling tasks across distributed AI agents. By 2026, it is recognized as the industry standard for bridging the gap between traditional scriptwriting formats (Fountain) and modern, scalable AI production pipelines.
Implements RESTful hypermedia constraints to allow AI agents to navigate story nodes via links rather than hardcoded endpoints.
The premier deep-learning fiction assistant for multi-language narrative drafting and world-building consistency.
Architecting high-conversion narrative frameworks for the 2026 attention economy.
Architecting complex narrative universes with high-fidelity semantic consistency and dynamic plot logic.
Architecting immersive narrative universes through RAG-enhanced generative AI.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Breaks scripts into granular units (actions, dialogues, transitions) stored as searchable JSON-LD.
Uses a centralized registry to ensure character attributes remain consistent across different scripts and sequels.
Integrates with vector databases to map story beats against emotional and structural benchmarks.
Every microservice generates its own dynamic API documentation.
Automatically generates Neo4j-compatible graph models from script text.
Checks the chronological consistency of events using temporal logic gates.
Manually checking if a character's eye color or back-story changes over 50 episodes is error-prone.
Registry Updated:2/7/2026
AI writers often produce incoherent scenes that don't fit the established structure.
Difficulty in estimating costs based on the number of locations and characters.