services
Generative AI
At BigCheese we believe that generative AI is not just a future promise, but a tangible tool to solve 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 with results.
Ideas
Using GenAI with real impact can be a challenge.
That’s why we share 6 ideas based on our concrete experience implementing projects in various industries. Real cases, real needs, real solutions that work.
GenAI Thinking Workshop
We identify with your team the WOW moments of your users and the opportunities of greatest impact. A practical space to define your first real use cases.
GenAI Chatbot
Conversational assistants, co-pilots for call center agents and customer interaction analysis. Faster, more accurate, more human responses.
Free up your team’s time
From employee onboarding to complex legal analysis. AI that solves repetitive tasks and frees up your team’s time.
Empowered decision and strategy
Models that analyze data, segment customers or make more transparent credit decisions, integrating business rules with AI.
Personalized experiences
Natural language search and recommendation 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 don’t say so. AWS validates it.
We were recognized with the official AWS GenAI Competency, a seal reserved for only a few partners in the region that have demonstrated proven experience and best practices applying generative artificial intelligence in production.
GENERATIVE ARTIFICIAL INTELLIGENCE
It is not enough to have a good idea.
Making a GenAI project a reality requires experience, tools, support and proven results.
These are 6 reasons why BigCheese is the ideal partner to take your initiative to production with confidence.
Proven cases in production
We have implemented real GenAI solutions in sectors such as banking, healthcare, retail, education, logistics and technology.
Official AWS GenAI Certification
Recognition of our experience and results in real projects.
AWS Premier Partner in Latam
With competencies in AI/ML, Migration, DevOps, Security and more.
Financing for your first projects
Access to AWS programs to cover a large part of the PoC.
Secure, scalable and responsible architecture
We design with Bedrock, SageMaker and Amazon Q, under security and governance standards.
Training and knowledge transfer
We help you build internal capabilities to scale with autonomy.
8 real business cases
Note: customer names have been omitted due to confidentiality requirements.
Chatbot with live access to the data repository (retail)
We created an interactive knowledge base that responds in natural language to regulatory, product and policy questions for both employees and website visitors.
Physical store assistant with conversational AI (retail)
We implemented a co-pilot for salespeople that allows them to consult inventory, product characteristics and recommendations in real time, improving the in-store customer experience.
Legal Contract Analysis Engine (legal)
We apply GenAI to process and understand complex contracts, extracting key clauses and executive summaries accurately and quickly, improving the work of the legal and compliance area.
Hospital diagnostics and stay management with AI (health)
We develop models that group patients according to clinical criteria and optimize the duration of hospital stays, reducing operating costs and improving hospital management.
Automated onboarding for new employees (fintech)
We created an intelligent assistant that guides new employees during their first days, answering frequently asked questions and streamlining integration with 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 personalized experience.
Visual cargo recognition and optimal logistics suggestion (logistics)
We implement computer vision to automatically identify products in cargo and recommend the most efficient vehicle for their transportation, optimizing time and resources.
FAQS
Quick answers to your questions
What is generative AI and how does it differ from other 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 define the path.
What data do I need to have?
It depends on the case. We can work with your structured data, documents, conversations or connect you to your datalake.
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 already 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 case is tailored according to the client’s objective and the type of data available.
What is Amazon Bedrock and why do you use it?
Amazon Bedrock provides access to foundational models (such as Claude, Titan, or Mistral) without the need to manage infrastructure. It is ideal for building assistants, co-pilots or generating customized content, with enterprise security.
What happens to my data when I use GenAI on AWS?
Your data is secure and private. No models are trained or shared with third parties. AWS ensures that processing is done in isolation, under your own controls and security settings.
Does my data train AI models?
No. With Amazon Bedrock, models do not retain or learn from your data. They are used in real time to respond, but they are not stored or reused.
How do you ensure the security of your solutions?
We use end-to-end encryption, access control through IAM, monitoring with CloudWatch and auditing with CloudTrail. In addition, we apply tools such as Bedrock Guardrails to filter sensitive or inappropriate content.
What is a RAG system and why do they use it so much?
RAG (Retrieval-Augmented Generation) is a technique that allows the AI model to query internal data before generating a response. It is key to ensuring that responses are contextual, accurate and reliable.
Can I customize the model with my own data?
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, under the services you control (such as Amazon S3 or DynamoDB). BigCheese designs the architecture so that you maintain full control.
Do they comply with international standards?
Yes, solutions are implemented following standards such as ISO 27001, SOC 2, GDPR, and others specific to regulated industries such as healthcare or finance.
Customers
They trust us
