Turn any AI endpoint into a managed API

Traefik AI Gateway accelerates AI adoption by turning any AI endpoint into an API that can be managed with unprecedented ease, speed & control

A diagram to illustrate the AI Gateway

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Top 15 in Docker hub
50K stars on github
Oss insight #1 api gateway 2019-present
Gartner cool vendor 2021
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Challenges

5 Key Challenges of Deploying AI in the Enterprise

Organizations adopting AI, language models, and autonomous agents to drive innovation face a new set of challenges:

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1. Mitigating Vendor Lock-In and Inflexibility

Dependence on a single AI provider limits adaptability, stifles innovation by restricting experimentation with new LLMs, and weakens negotiation leverage due to vendor reliance.

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2. Overcoming Integration Complexity Across Multiple AI Models

Managing different LLMs with unique APIs and SDKs is complex, resource-intensive, and delays AI solutions due to time-consuming integrations and extended development efforts.

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3. Enhancing Security and Credential Management

Managing sensitive API credentials is challenging due to exposure risks from disparate systems, inconsistent security protocols complicating policy enforcement, and compliance difficulties arising from scattered credential management.

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4. Establishing Unified Governance, Enforcing Policy & Reigning in Shadow IT

Without centralized governance, inconsistent policies impede uniform enforcement of authentication, authorization, and rate limiting. This leads to inefficiencies, potential misuse of AI resources, and allows shadow IT to thrive, further escalating security risks and regulatory non-compliance.

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5. Navigating Limited Observability and Monitoring

Without unified visibility, AI operations are significantly hindered by limited observability. Fragmented monitoring tools and data silos obstruct comprehensive analysis, making it challenging to optimize workflows without holistic insights.