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SERVICIOS

AI Model Customization & MLOps

We help teams choose between prompting, RAG, inference deployment and fine-tuning. We do not claim foundation-model training; we focus on measurable evaluation, deployment and monitoring.

Descripción General

We help teams choose between prompting, RAG, inference deployment and fine-tuning. We do not claim foundation-model training; we focus on measurable evaluation, deployment and monitoring.

Nuestro Enfoque

Seguimos un enfoque estructurado para cada compromiso de ai model customization & mlops, asegurando calidad y alineación en cada etapa.

1

Understand your requirements

2

Design the solution

3

Build with modern engineering

4

Deploy and support

Capacidades

Capacidades detalladas dentro de ai model customization & mlops.

Model selection & evaluation

Model selection & evaluation

RAG, embeddings & vector search

RAG, embeddings & vector search

LoRA / QLoRA fine-tuning where justified

LoRA / QLoRA fine-tuning where justified

Inference deployment & optimization

Inference deployment & optimization

Model monitoring & cost control

Model monitoring & cost control

Dataset preparation & quality review

Dataset preparation & quality review

Tecnologías que Usamos

Las decisiones de tecnología siguen las necesidades del producto — no la moda.

OpenAI / Claude / GeminiLlama / Qwen / open modelsRAG & embeddingsLoRA / QLoRAvLLM / inference servingVector databases

Resultados Esperados

Choose the simplest approach that meets the quality bar

Evaluate models against real tasks and data

Control latency and inference cost

Monitor quality after launch

¿Listo para discutir ai model customization & mlops?

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