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NEC to launch cotomi Gateway in November for secure, cost-optimized AI routing

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NEC to launch cotomi Gateway in November for secure, cost-optimized AI routing

3 Key Points

  1. What happened

    NEC will release a software version of cotomi Gateway in November, with SaaS rollout to follow. It evaluates factors like confidentiality, task difficulty, answer quality, and cost to automatically route requests to appropriate AI models, and can connect to existing systems via API.

  2. Why it matters

    The gateway automatically detects and masks confidential information so external AI models can be used while keeping data hidden, and handles hard-to-mask tasks with on-premises models. It also compresses redundant prompts to cut token consumption, reducing manual operational load, according to NEC.

WHO IT HITSEnterprise IT teams and business units using multiple AI models will be able to centralize routing and security controls through one gateway, potentially lowering token costs and reducing manual masking work, based on NEC's stated capabilities.

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Context & Analysis

NEC's move comes as companies increasingly use multiple AI models for different tasks, which can raise both security concerns and token costs. By offering a common gateway that automatically selects models based on confidentiality, task difficulty, answer quality, and cost, NEC aims to let businesses adopt AI without overhauling existing workflows. The software edition will be followed by a SaaS version, giving companies an on-premises option first and a cloud-based rollout later. The gateway's masking and routing features are designed to reduce manual operational load, while its dashboard allows real-time monitoring of usage and cost savings.

FAQ
When will cotomi Gateway be available?
NEC plans to provide the software version in November, with SaaS deployment to follow sequentially.
How does cotomi Gateway protect confidential information?
It automatically detects and masks confidential information so external AI models can be used with data kept hidden. For tasks difficult to handle via masking, it uses AI models running in an on-premises environment.
How does it reduce token costs?
It compresses redundant parts of prompts and unnecessary information to suppress token consumption. It also uses lightweight regression and statistical models to make comprehensive judgments based on prompt content, past usage history, conversation flow, and cache status.
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