Eragon provides an AI operating system that integrates with an enterprise’s existing data stack to train and deploy custom models on proprietary data. The platform offers self‑hosted, multi‑agent orchestration across chat, voice, UI, and API, with continuous performance monitoring and enterprise‑grade security.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises generate massive volumes of structured and unstructured data across disparate systems, yet they lack a unified layer that can ingest, interpret, and act on this information in real time. Relying on third‑party foundation models forces companies to rent generic intelligence, exposing proprietary data and limiting competitive advantage. Consequently, operational workflows remain manual, siloed, and difficult to measure against business outcomes.
Solution
Eragon delivers an applied AI operating system that plugs directly into a company’s existing data stack without requiring wholesale replacement. The platform trains purpose‑built models on the organization’s own datasets, producing domain‑specific intelligence that reflects internal terminology and judgment. Trained models are exposed as autonomous agents that can be orchestrated across multiple channels—chat, voice, UI, or API—to execute end‑to‑end workflows. Continuous evaluation benchmarks each agent’s accuracy, latency, and value contribution against defined KPIs, enabling iterative improvement. All components run in a self‑hosted environment with granular access controls, ensuring data never leaves the enterprise perimeter. The system’s control plane provides a single pane of glass for monitoring, scheduling, and updating agents, turning raw bits into actionable operational insight.
Target Audience
The primary customers are large‑scale enterprises—such as financial services, insurance, logistics, and technology firms—that need to embed AI‑driven automation into core operational processes while retaining full control over their data and models.
Features
- Native connectors and adapters for ERP, CRM, data warehouses, and event streams, allowing seamless ingestion of on‑premise and cloud data sources.
- Automated model training pipeline that ingests proprietary data, fine‑tunes large language models, and produces lightweight, inference‑optimized weights owned by the customer.
- Multi‑agent orchestration engine with persistent memory, enabling context‑aware task routing, failover, and composable skill execution.
- Continuous learning loop that captures agent interactions, feeds back performance metrics, and retrains models to improve accuracy over time.
- Enterprise‑grade security stack: self‑hosted deployment options, sandboxed execution, role‑based access, audit logs, and full compliance with SOC 2 and GDPR.
- Centralized gateway providing webhooks, cron scheduling, and real‑time event handling for end‑to‑end automation across all business surfaces.
- Extensible skill marketplace allowing developers to add custom capabilities in minutes using a TypeScript SDK.