Custom & private GPT models to empower your business
AI platform that utilizes your proprietary datasets to train ChatGPT-like models, creating intelligent applications capable of sophisticated interactions within your business ecosystem.
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Key players in finance, legal, and e-commerce sectors depend on our platform
Top 5
commercial bank in a Spain
Top 10
wealth management firm
Category-leading eCommerce
with thousands of products
*Confidential as it has not been announced yet
what we do
LLM Ops to easily train and deploy models on your data, in your secure environment
Large language models (LLMs) are shaking up the field with their incredible abilities to generate text, analyse sentiment, translate languages, and much more.
In order to train an LLMs to become an expert in a particular domain, context management or fine-tuning is usually required and brings with it a unique set of challenges:
Selecting an appropriate foundational model, employing LLMs for task-specific applications, evaluating their performance, and eventually deploying and monitoring the models in real-world scenarios.
In order to train an LLMs to become an expert in a particular domain, context management or fine-tuning is usually required and brings with it a unique set of challenges:
Selecting an appropriate foundational model, employing LLMs for task-specific applications, evaluating their performance, and eventually deploying and monitoring the models in real-world scenarios.
Custom-trained in your data, your most valuable asset
Maximizing security and data control with SaaS, On-Premise, and Hybrid paradigms
Cheaper than using third-party models like chatGPT
Seamless integration with our data connectors and data consumers
OUR END-USER PRODUCTS
An application for every use case
With its modular architecture, enjoy unmatched flexibility and scalability, allowing seamless customization and integration of language models into your business.
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LLMOps
LLMOps: MLOps for Large Language Models
LLMOps focuses on the operational capabilities and infrastructure required to fine-tune existing foundational models and deploying these refined models as part of a product. To most observers of the MLOps movement, LLMOps isn't anything new (except as a term) but rather a sub-category of MLOps. A narrower definition might, however, help drill into more specific requirements that fine-tuning and deploying these types of models has.
Latest case studies
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