FloLogix AI provides a self‑hosted platform that runs private large language models and retrieval‑augmented generation on on‑premise or edge infrastructure, keeping all AI processing within the enterprise network. The solution includes fine‑tuning, agentic workflow orchestration, and a unified admin console with audit‑ready logging to meet HIPAA, GDPR, and ISO compliance, offered under a predictable annual licensing model.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises in regulated sectors need to leverage large language models and AI-driven automation, but public cloud services expose sensitive data, incur unpredictable token‑based costs, and require specialized NLP expertise to deploy context‑aware solutions securely.
Solution
FloLogix AI delivers a self‑hosted AI platform that runs private large language models, retrieval‑augmented generation (RAG), and automated workflows entirely on an organization’s on‑premise or edge infrastructure. The stack supports custom model fine‑tuning, document ingestion for domain‑specific knowledge bases, and agentic orchestration that can invoke internal APIs, IoT devices, robotics, or scientific libraries. All processing stays within the customer’s network, ensuring data sovereignty, audit‑ready logging, and compliance with standards such as HIPAA, GDPR, and ISO. Administrators manage users, models, and analytics through a unified web console, while developers integrate AI capabilities via RESTful APIs and SDKs. Predictable annual licensing eliminates variable cloud token fees and provides a clear total cost of ownership.
Target Audience
Primary customers are regulated enterprises—such as manufacturing, defense & aerospace, healthcare, legal, and research labs—that require on‑premise AI with strict data‑privacy and compliance mandates.
Features
- Private model hosting engine that runs custom or open‑source LLMs on on‑premise or edge hardware, with token‑usage monitoring and no external API calls
- Retrieval‑augmented generation (RAG) pipeline that indexes enterprise documents, databases, and APIs to deliver context‑grounded responses
- Agentic workflow orchestration allowing AI agents to trigger actions, invoke ML libraries, and control IoT sensors, robotics, or lab equipment
- Built‑in fine‑tuning workflow for domain adaptation, supporting incremental training on proprietary data without leaving the secure perimeter
- Centralized admin console with chat UI, model manager, usage analytics, role‑based access control, and immutable audit logs for regulatory reporting
- Open REST/GraphQL APIs and SDKs (Python, Java) for seamless integration with existing enterprise applications and CI/CD pipelines
- Enterprise‑grade security stack: end‑to‑end encryption, FIPS‑validated cryptography, and compliance‑ready logging and reporting modules
- Optional hardware bundle and one‑time setup service to accelerate deployment on customer‑owned servers or edge appliances