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Silicon Interfaces® R&D Labs are building a robust Agent using the latest in technologies and best-in-class models (as Small Language or Large Language Models SLM/LLM) as well as Natural Language Processing (NLP) to give you best cost/performance ratio and ensure you high levels of correct responses and limit hallucinations.

This ensures that there is a concentric centralized Lab constantly improving the Agent by reviewing Models and properties/features that are being deployed in the global Machine Learning area, for example, when to use Small versus Large Learning Models, Latency, Token usage (free versus performance), overall pricing, multi-thread models, Etc. The exciting world of AI and ML models is evolving and growing at a very fast pace and Silicon Interfaces is investing and deploying the Agent in multiple website, with the clear advantage as we collate and deploy, all our customer will get the advantage.

Agent Logic

The process flow is similar to most Agent technology, with input mechanism being either text or speech, (may be a pre-processor to filter out routine interactions so not to load the SLM/LLM models and help in our efforts to go green and use less electricity and help in reducing carbon footprint) which is then fed to an NLP engine to channelize queries into usable search key fields. Just in case the inputs where the language is other than English, the data is pre-processed by LLM models to translate to English. Next, the request is submitted as tokens to AI/ML and even AI/DL models which matches patterns on the datasets provided and once an intelligent and robust answer is generated, the responses are gauged for correctness and collated through a process of reasoning, the Agent then uses LLM model to give the responses in the language it was asked in

[User types message] or [Voice speech to text]
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[Pre-processing using pattern matching, save the SLM/LLM and go green]
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[Interpretation using Natural Language Processing (NLP)]
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[Language translation to English using LLM]
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[Send HTTP request through OpenRouter]
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[OpenRouter processes request thru to AI/ML Model]
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[Returns AI response in JSON]
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[Language translation to Native Language using LLM]
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[Display response]


Silicon Interfaces uses a plethora of more than 500 models and deploys the best in class based on latency, token usage, and price.

In brief, the Agents powered by AI™ services undertakes the following:

  • Build a 24/7 Agent powered by AI using C# and Open and Flexible OpenRouter
    • Use OpenRouter's API NLP/ML for intelligent responses
    • Deploy as a scalable web-based assistant with Conversational Interfaces
    • Use user interaction/behavior to improve learning models
  • Userbality Interface using LLMs
    • Speech activation and interaction
    • Multi-lingual interactions








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