GenAI
GenAI in production, on your infrastructure and your data
Assistants, agents and automation with Amazon Bedrock, built by the same team that already runs your cloud. From use case prioritization to production, with evaluation and cost under control.
Betterfly: 10,000+ users across 5+ countries
You don't build AI in a vacuum: you build it on your infrastructure, your data and your security. So it makes sense for the partner who knows your cloud end to end to build it. This line runs from the initial assessment to agents in production, with the same engineering and FinOps discipline we apply to everything else.
GenAI
What this line covers
AI Workloads to Bedrock
We migrate your GenAI workloads to Amazon Bedrock: your perimeter, your model choice, your cost under control.
Learn moreCustom AI Agent Development
Agents that query your data and operate your systems, with permissions, evaluation and observability.
Learn moreAI Call Center (Amazon Connect)
Voice and chat support with GenAI self-service and real-time agent assistance.
Learn moreGenAI Consulting & Assessment
Use case prioritization, reference architecture and a roadmap with estimated costs.
Learn more
AWS Competency
AWS AI Services Competency
The AWS AI Services Competency recognizes our technical expertise and our ability to take AI solutions into production, with real projects and a focus on results.
We combine strategy, data and artificial intelligence to identify opportunities with concrete impact for each business, reduce uncertainty during implementation and turn ideas into scalable solutions.
This competency also complements our experience in AWS migrations, allowing us to support our customers from cloud infrastructure all the way to the implementation of AI solutions.
Featured case
Betterfly
For Betterfly we built 'Buddy AI', a multichannel GenAI assistant: RAG over 1,000+ documents, 5+ conversational personalities and ticketing integration. It now serves 10,000+ users across 5+ countries. We launched it in 8 weeks.
Built on AWS, with Amazon Bedrock
We choose the model by result and by cost, not by hype. We work with Amazon Bedrock as the foundation (including Anthropic's Claude models) and we're on track for the AWS Generative AI competency, on top of our Advanced Tier, AI Services Competency, EKS Service Delivery and Migration & Modernization Services Competency credentials.
Before the AI, the data
If the use case depends on your internal knowledge, the outcome is decided in the data preparation. That part lives in the Data & Analytics line and runs in parallel.
See Data & AnalyticsHow we work
Discovery
We identify the highest-impact use case and validate technical and data feasibility. No hype: we prioritize what moves the needle.
Plan & Quote
We design the architecture (model, data, security, cost) and propose a tight MVP at a closed price.
Execution
We build the MVP, evaluate it with real metrics and iterate until it's production-ready.
Hand-off & MSP
We leave it in production, monitored and cost-controlled. We can keep operating and evolving it with you.
FAQ
Do you build GenAI from scratch or on what I already have?
Both, but the most common and most valuable path is adding GenAI on top of the infrastructure and data you already have on AWS.
Which models do you use?
Mainly Amazon Bedrock, which includes models such as Anthropic's Claude, depending on the use case. We choose the model by result and by cost.
Do you have a real case in production?
Yes: Betterfly. We built 'Buddy AI', a GenAI assistant with RAG over 1,000+ documents that now serves 10,000+ users across 5+ countries, launched in 8 weeks.
How do you control AI costs?
With the same FinOps discipline we apply to the whole cloud: AI in production has to be sustainable, not a surprise on the bill.
