Janix provides an enterprise AI gateway and control platform that enables secure, scalable integration of Large Language Models (LLMs) with existing enterprise systems. Its model-agnostic architecture facilitates tool calling and data access without code changes, while offering robust data privacy, centralized governance, and audit trails for compliant LLM adoption.
Funding
$200K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations face significant challenges in securely integrating Large Language Models (LLMs) with existing enterprise systems, primarily due to concerns around data privacy, security, and the complexity of managing diverse AI capabilities. This gap hinders the adoption of LLMs, preventing businesses from leveraging their full potential while maintaining regulatory compliance and operational control.
Solution
Janix provides an enterprise-grade AI gateway and control platform designed to facilitate secure and scalable LLM integration. The platform offers a model-agnostic architecture that connects LLMs with existing enterprise systems, enabling tool calling and data access without requiring code modifications. It addresses key implementation barriers by providing robust data privacy controls, comprehensive audit trails for trust and verification, and centralized governance for managing AI capabilities. Janix also offers features for automated tool discovery, cost visibility, and network orchestration, transforming experimental AI initiatives into enterprise-ready solutions.
Target Audience
The primary target audience includes enterprises and IT leaders seeking to securely integrate and scale LLM capabilities within their existing technology stacks, particularly those in regulated industries or with strict data governance requirements.
Features
- **Enterprise AI Gateway:** High-performance network orchestration with intelligent load balancing, automatic failover, and advanced traffic management for reliable AI infrastructure.
- **Model-Agnostic Integration:** Connects LLMs with existing enterprise systems via an API-to-MCP (Model Context Protocol) transformation layer, requiring zero code changes to legacy applications.
- **Secure Data Access:** DB-to-MCP layer provides governed data access for AI agents with query optimization and built-in data protection.
- **Centralized Control & Management:** Enterprise OAuth 2.1 integration for agent authentication, role-based access control, and centralized tool governance.
- **Automated Tool Discovery:** Facilitates the discovery and management of enterprise tools with usage analytics and context-aware suggestions.
- **Cost Visibility & Control:** Executive-level reporting on departmental AI spending, budget allocation, and financial oversight for AI investments.
- **Enhanced AI Agent Success:** Achieves up to 3x higher AI agent success rates through purpose-built composite tools and agentic intelligence.
- **Continuous Learning Platform:** Self-improving architecture that learns from usage patterns, detects failures, and reduces operational overhead.