AI Data Platform · 2026
Kriyagni AI
Training Data That Thinks Like a Professional
Overview
Kriyagni AI generates high-fidelity, auditable reasoning traces for LLM fine-tuning. By defining the agent type, users, and output, it models expert cognition to create domain-authentic datasets. It is built for regulated fields like finance, law, medicine, chemistry, and aerospace, powering high-stakes decisions across all timezones.
Design Philosophy
A clean, authoritative interface built for AI researchers and data scientists. It focuses on clarity, structural auditability, and data authenticity, mirroring the precision required in the high-stakes domains it serves.
Highlights
Modeling Expert Cognition
Instead of simply prompting an LLM, we define who the expert is, their role, reasoning patterns, and decision logic.
Agentic Workflow Traces
Generates multi-step reasoning traces with tool calls and professional decision chains, structurally high in auditability.
High-Stakes Domain Focus
Built for fields where precision is non-negotiable, including finance, law, medicine, chemistry, and aerospace.
Framework-driven Scalability
Moves beyond prompt-dependent scaling to offer framework-driven generation of domain-authentic datasets.
Tech Stack
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