services
Generative AI
At BigCheese, we believe that generative AI is not just a promise for the future, but a tangible tool for solving challenges today.
We specialize in designing solutions that combine foundational models, internal data, and a secure cloud architecture so that companies can evolve with confidence.
Think Big. Start Small. Start with a case. Scale up with results.
Ideas
Using GenAI to make a real impact can be a challenge.
That’s why we’re sharing six ideas based on our hands-on experience implementing projects across various industries. Real-world cases, real needs, solutions that work.
GenAI Thinking Workshop
Together with your team, we identify your users’ “WOW” moments and the opportunities with the greatest impact. A hands-on space to define your first real-world use cases.
GenAI Chatbot
Conversational assistants, co-pilots for call center agents, and analysis of customer interactions. Faster, more accurate, and more human responses.
Free up your team’s time
From employee onboarding to complex legal analysis. AI that handles repetitive tasks and frees up your team’s time.
Enhanced Decision-Making and Strategy
Models that analyze data, segment customers, or make more transparent credit decisions by integrating business rules with AI.
Personalized Experiences
Recommendation and natural language search engines to better understand your customers and offer them what they need without friction
Science, Health, and Logistics
From visual cargo recognition to melanoma detection. AI that sees, predicts, and improves critical processes in your operation.
We’re not the ones saying it. AWS confirms it.
We were recognized with the official AWS GenAI certification, a distinction reserved for a select few partners in the region who have demonstrated proven expertise and best practices in applying generative artificial intelligence in production.
GENERATIVE ARTIFICIAL INTELLIGENCE
It’s not enough to just have a good idea.
Bringing a GenAI project to life requires experience, tools, guidance, and proven results.
Here are 6 reasons why BigCheese is the ideal partner to help you bring your initiative to production with confidence.
Confirmed cases in production
We have implemented real-world GenAI solutions in industries such as banking, healthcare, retail, education, logistics, and technology.
AWS GenAI Official Certification
Recognition of our experience and results in real-world projects.
AWS Premier Partner in Latin America
With expertise in AI/ML, Migration, DevOps, Security, and more.
Funding for Your First Projects
Access to AWS programs to cover a significant portion of the PoC.
Secure, scalable, and responsible architecture
We design using Bedrock, SageMaker, and Amazon Q, in accordance with security and governance standards.
Training and Knowledge Transfer
We help you build internal capabilities so you can scale independently.
8 Real-World Business Cases
Note: Client names have been omitted for confidentiality reasons.
Chatbot with real-time access to the data repository (retail)
We created an interactive knowledge base that answers questions about regulations, products, and policies in natural language, for both employees and website visitors.
In-Store Assistant with Conversational AI (retail)
We’ve implemented a sales assistant that allows salespeople to check inventory, product details, and recommendations in real time, improving the in-store customer experience.
Contract Legal Analysis Engine (legal)
We use GenAI to process and understand complex contracts, accurately and quickly extracting key clauses and executive summaries, thereby improving the work of the legal and compliance departments.
Hospital Diagnosis and Stay Management Using AI (healthcare)
We develop models that group patients according to clinical criteria and optimize the length of hospital stays, thereby reducing operating costs and improving hospital management.
Automated onboarding for new employees (fintech)
We created a smart assistant that guides new employees through their first few days, answering frequently asked questions and streamlining their integration into the team.
Personalized content recommender for users (wellness)
We designed a recommendation engine based on behavioral patterns that suggests relevant content for each user, improving retention and the personalized experience.
Visual Cargo Recognition and Optimal Logistics Recommendations (logistics)
We use computer vision to automatically identify products being loaded and recommend the most efficient vehicle for their transport, thereby optimizing time and resources.
FAQS
Quick answers to your questions
What is generative AI, and how is it different from other types of AI?
It is a type of artificial intelligence capable of creating new content—text, images, code, and more—rather than just classifying or predicting.
What do I need to get started?
Just an idea and a challenge. Our GenAI Thinking workshop helps you chart your course.
What information do I need to have?
It depends on the situation. We can work with your structured data, documents, and conversations, or connect to your data lake.
Is it safe to use GenAI?
Yes. We use tools such as Bedrock Guardrails and follow best practices in privacy, security, and data governance.
Who trains the models?
We use pre-trained foundational models (such as Claude or Titan) and customize them with your data.
What AWS technologies do you use to implement GenAI?
We work with tools such as Amazon Bedrock, Amazon Q, SageMaker, Kendra, Lambda, S3, Glue, and OpenSearch. Each solution is tailored to the client’s objectives and the type of data available.
What is Amazon Bedrock, and why do people use it?
Amazon Bedrock provides access to foundational models (such as Claude, Titan, or Mistral) without the need to manage infrastructure. It’s ideal for building assistants, co-pilots, or generating personalized content, all with enterprise-grade security.
What happens to my data when I use GenAI on AWS?
Your data is secure and private. It is not used to train models or shared with third parties. AWS ensures that processing is performed in isolation, under your own controls and security settings.
Is my data used to train AI models?
No. With Amazon Bedrock, the models do not retain or learn from your data. They are used in real time to provide responses, but the data is not stored or reused.
How do you ensure the security of your solutions?
We use end-to-end encryption, access control via IAM, monitoring with CloudWatch, and auditing with CloudTrail. In addition, we use tools such as Bedrock Guardrails to filter sensitive or inappropriate content.
What is a RAG system, and why is it so widely used?
RAG (Retrieval-Augmented Generation) is a technique that allows the AI model to consult internal data before generating a response. It is key to ensuring that responses are contextual, accurate, and reliable.
Can I customize the template with my own information?
Yes. We can customize models using fine-tuning or prompt engineering, depending on the sensitivity, volume, and format of your data.
Where is my data stored?
In your own AWS environment, using the services you control (such as Amazon S3 or DynamoDB). BigCheese designs the architecture so that you retain full control.
Do they comply with international regulations?
Yes. The solutions are implemented in accordance with standards such as ISO 27001, SOC 2, GDPR, and other standards specific to regulated industries such as healthcare and finance.
Customers
They trust us
