Isidor builds secure, vertically integrated pipelines that convert raw, unstructured proprietary data into reinforcement‑learning‑ready curricula for enterprise model training.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often possess large volumes of raw, unstructured proprietary data that cannot be directly used to train reinforcement‑learning (RL) models, leading to missed opportunities for automating complex, domain‑specific workflows. Additionally, existing pipelines for preparing such data lack robust security and compliance controls, exposing sensitive information to risk.
Solution
Isidor offers a secure, vertically integrated platform that transforms raw, unstructured enterprise data into RL‑ready curricula. The system captures detailed workflow traces, reverse‑engineers them into training sequences, and applies post‑processing verifiers to ensure generated outputs meet stringent enterprise standards. Built‑in state‑of‑the‑art benchmarks and agentic evaluations provide industry‑specific performance metrics, while enterprise‑grade guardrails guarantee end‑to‑end privacy, security, and regulatory compliance. Customers can fine‑tune and align foundation models on their own data, enabling scalable, firm‑specific AI solutions without exposing proprietary information.
Target Audience
Primary customers are large enterprises and organizations that need to develop custom AI agents for domain‑specific processes, such as manufacturing, finance, healthcare, and logistics, while maintaining strict data security and compliance.
Features
- Automated ingestion and structuring of heterogeneous proprietary data into reinforcement‑learning curricula
- Capture and reverse‑engineering of complex workflow trace data for accurate task modeling
- Integrated SOTA benchmarks and agentic evaluation suites tailored to specific industry verticals
- Post‑processing verification layer that validates generative AI outputs against granular enterprise criteria
- Secure, end‑to‑end encryption and compliance‑focused guardrails throughout the data pipeline
- Fine‑tuning and alignment tools for foundation models using in‑house data and practices