Kodif AI

Kodif’s differentiation begins with a hybrid reasoning layer that combines retrieval-augmented generation (RAG) with deterministic rule-based logic. Instead of relying solely on large language model (LLM) stochasticity, the platform pre-compiles a customer-specific knowledge graph from CRM data, past tickets, product catalogs, order tables, and policy manuals. At runtime, the orchestration engine decides—in milliseconds—whether a query is better served by a strict policy rule (e.g., refund eligibility window) or by generative text that references the knowledge graph. To mitigate hallucination and ensure PCI/PII compliance, Kodif deploys a two-tier guardrail stack:

• Policy Layer: Custom DSL (Domain-Specific Language) codifies business rules in plain English, then compiles into executable bytecode. A violation here triggers an immediate agent hand-off.
• Safety Layer: A lightweight fine-tuned DistilBERT classifier flags toxic language, payment card numbers, or attempts at prompt injection before the LLM ever receives the prompt.

All conversations are vectorized in real time using an in-house embedding model optimized for support lexicons (cosine similarity threshold 0.83), enabling semantic search across 10 million historical tickets in <120 ms latency.