- AI
GenAI Solutions on AWS
Harness the Power of Revolutionary LLMs in a Fully Controlled and Secure Manner Within Your Private AWS Environment
We develop generative AI and build custom AWS AI solutions based on Amazon Bedrock, among others, that understand your business specifics, automate processes, and create value from your unique data.
Challenges in Business Application of Generative AI
The potential of generative AI is enormous, but its implementation in a corporate environment raises fundamental challenges:
Data security and privacy risks
Concerns about sending sensitive corporate data (contracts, reports, customer data) to external, uncontrolled services.
Lack of knowledge about your company
Public AI models do not know your internal procedures or product specifications, making their responses generic and often imprecise.
Implementation and integration challenges
Lack of team expertise on how to connect a language model with internal databases and integrate it in a scalable manner with existing applications.
From Concept to Production GenAI Solution on AWS
As a generative AI solutions provider, we operate comprehensively, transforming the potential of this technology into real, secure business tools.
Our generative AI services include:
Workshops and use case identification
Together, we identify the most valuable GenAI applications in your company, such as intelligent assistants, reporting automation, or customer communication analysis.
Building private solutions with Amazon Bedrock
We design and build secure generative AI applications in RAG architecture that allow LLM models to securely utilize your data in AWS.
Fine-tuning models for specialized tasks
We fine-tune a selected model on your data to create an expert assistant, such as a bot that perfectly uses your language.
Full integration with business processes
We build a complete end-to-end solution—from backend, through user interface, to integration with your existing systems.
Your Path to GenAI Innovation Implementation
We operate in an agile manner, focused on rapid value delivery:
1.
Rapid prototype (Proof of Concept)
Within 2-4 weeks, we build a working prototype on a sample of your data to prove value and validate assumptions.
2.
Production solution development (MVP)
We expand the prototype into a robust, scalable, and secure application ready for deployment.
3.
Integration and testing
We integrate the solution with your systems and conduct rigorous functional, performance, and security testing.
4.
Deployment and support
We launch the solution, conduct training, and provide ongoing support and application monitoring.
Frequently Asked Questions
For security, privacy, and control. By building on AWS, your data never leaves your private cloud environment, and you have full control over models, performance, and costs.
It is a managed AWS service that simplifies building generative AI applications, providing secure access to a wide range of leading models (e.g., Claude, Llama) through a single API.
RAG is a technique that allows language models to answer questions based on your private knowledge base (e.g., corporate documents). This is how we build assistants that know your company inside and out.
Practically never—it is too costly. Instead, we use significantly more efficient techniques such as RAG (knowledge retrieval) and fine-tuning (adapting the model to specific style or terminology).
