NeuroFlows
NeuroFlows is a multi-tenant SaaS platform designed to orchestrate complex, agentic AI workflows. We built a scalable foundation capable of handling real-time speech-to-text, sophisticated RAG pipelines, and deterministic business logic for diverse enterprise clients.
The core challenge of NeuroFlows was not just integrating LLMs, but orchestrating them within a rigid, deterministic business environment. Clients needed the flexibility of generative AI combined with the reliability of traditional state machines.
We approached this by decoupling the "intelligence" from the "execution." LLMs were treated as unreliable co-processors within a robust orchestration engine, requiring extensive fallback mechanisms, prompt versioning, and rigorous output validation schemas.
Key Decisions
Moved away from synchronous API calls to an asynchronous, Kafka-backed event architecture. This prevented long-running LLM inferences from blocking critical UI threads and allowed for robust retry mechanisms on failure.
Implemented strict logical separation within the vector database. Each tenant's embeddings were namespace-isolated, with application-level middleware enforcing role-based access control before any similarity search execution.
Designed a custom state machine to track multi-step agent interactions. This provided auditability, allowed human-in-the-loop interventions, and ensured non-deterministic LLM paths always converged on valid business states.
The architecture enabled rapid onboarding of enterprise clients, handling significant throughput while maintaining strict latency SLAs for real-time transcription and generative responses.