Professional Services in Generative AI on AWS
Instituto Ingenieria Conocimiento · Cybersecurity & IT
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
We offer an end-to-end approach for the design, development, evaluation, deployment, and maintenance of Generative AI systems on AWS, with a strong focus on real business use cases, security, quality, and cost reduction.
**Systematic evaluation and tool selection**
Show the rest of the publisher’s description (44 more lines)
We conduct rigorous evaluations to measure the performance of language models or conversational agents against specific business use cases. Our methodology includes:
- Continuous benchmarking. Ongoing [comparative evaluation](https://www.iic.uam.es/procesamiento-del-lenguaje-natural/evaluacion-llm-corpus-personalizado-espanol/) of the Amazon Bedrock Generative AI providers.
- Specialized testing. Custom-designed test sets for each client and use case, simulating real production conditions.
- Production performance prediction. Tests that help forecast system behavior under real load and with complex queries.
**Model customization and fine-tuning**
We adapt and [fine-tune Amazon Bedrock language models](https://www.iic.uam.es/procesamiento-del-lenguaje-natural/que-es-fine-tuning-por-que-util-llms/) using client-specific data to improve accuracy, relevance, and business alignment. This includes:
- Supervised fine-tuning and [customization](https://www.iic.uam.es/procesamiento-del-lenguaje-natural/mejora-y-evaluacion-modelo-embeddings-espanol/).
- Adaptation to specific terminology, style, and business context.
- Optimization for [targeted tasks](https://www.iic.uam.es/noticias/entrenando-llm-ser-mas-fiel-al-contexto/) (e.g., customer support, report generation, etc.).
- Experience in projects requiring multimodal solutions that combine text, audio, images, or video.
**Security by Design**
We guarantee secure deployments with the following measures:
- [Guardrails by design](https://www.iic.uam.es/noticias/que-son-los-guardarrailes-llms/). We incorporate mechanisms to prevent inappropriate, off-topic, or sensitive outputs.
- Regulatory compliance. Full alignment with standards like the AI Act (RIA) and best practices in secure software development.
**Cost Reduction**
We design [efficient solutions](https://www.iic.uam.es/noticias/ia-tradicional-vs-ia-generativa-cual-aplico/) that reduce the Total Cost of Ownership (TCO):
- LLM optimization and compression. Reducing model size and operating costs through specialization, pruning, and distillation techniques.
- Use-case-based tuning. Tailoring architectures to maximize efficiency and minimize resource consumption.
**Secure and Ethical Development Methodologies**
We apply secure software development standards and AI engineering best practices, including:
- [Ethical AI policy](https://www.iic.uam.es/noticias/inteligencia-artificial-legal-etica-y-robusta/). Designing and deploying solutions under principles of transparency, non-discrimination, and accountability.
- Quality assurance. Continuous validation with testing cycles, QA processes, and expert reviews at each phase.
**Multidisciplinary Team**
Our team includes experts covering every phase of the Generative AI lifecycle on AWS:
- Data Scientists:
- Specialized fine-tuning.
- Automation of testing pipelines and large-scale evaluation.
- Computational Linguists:
- Creation of evaluation and training datasets.
- Manual evaluation of model outputs with linguistic and business criteria.
- Prompt engineering and guardrail configuration.
- Data and Security Engineers:
- Secure software development.
- Integration into AWS production environments.
**Scalability and RAG (Retrieval-Augmented Generation)**
We provide a [proprietary RAG platform](https://www.iic.uam.es/procesamiento-del-lenguaje-natural/que-son-los-sistemas-de-rag-respuestas-ia-generativa/) (René) offering:
- Ready to use on AWS.
- High scalability. Reduced development times and faster production deployment.
- Built-in reliability and security. Pre-configured guardrails and full AI Act compliance.
- Risk-minimizing evaluation methodology. Ensures quality and stability before production rollout.
**Landmarks: Spanish-Centric LLMs and Scalable GenAI Solutions**
- Pioneers in Spanish LLMs: In-house development of [Rigochat](https://www.iic.uam.es/publicaciones/rigochat-2-adapted-language-model-to-spanish/) and [RigoBERTa](https://www.iic.uam.es/noticias/lanzamos-nueva-version-modelo-lenguaje-rigoberta-2/), language models tailored for Spanish. Both models are available on AWS Marketplace.
- Proven LLM and RAG [evaluation framework](https://www.iic.uam.es/procesamiento-del-lenguaje-natural/evaluacion-llm-corpus-personalizado-espanol).
- René: A scalable, production-ready [RAG system](https://www.iic.uam.es/innovacion/que-son-los-sistemas-de-rag-respuestas-ia-generativa/).
Highlights
Highlighted by the publisher on AWS Marketplace.
We pioneer Spanish language models with Rigochat and RigoBERTa, developing in-house LLMs tailored for Spanish. Our expertise covers prompting, fine-tuning, data curation, alignment to human preferences (RLHF, DPO), and red teaming for robust and ethical AI behavior.
We bring a proven methodology for evaluating NLP and Generative AI/RAG projects, ensuring business impact and quality. Our approach combines advanced prompting strategies with extensive experience in data preparation, backed by the development of over hundreds of custom corpora for real-world use cases.
We have proven experience in building reliable, scalable RAG systems, leveraging our proprietary platform René. We specialize in deploying GenAI/RAG solutions on AWS production environment, handling high data volumes and low-latency requirements.
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Sources
Publisher resources
3 linksLinked repositories
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