AI, GenAI and ML Consulting Services
SDG · Cybersecurity & IT
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
SDG delivers end-to-end Generative AI consulting services on AWS, guiding organizations from initial use case discovery through secure deployment and production operations. We begin with a business-led approach to identify and prioritize high-impact GenAI opportunities, then design scalable, AWS-native architectures using proven patterns. Our team implements solutions leveraging services such as Amazon Bedrock and Amazon SageMaker, enabling model selection, orchestration, and customization through prompt engineering, retrieval-augmented generation (RAG), embeddings, and fine-tuning. The result is a production-ready GenAI solution aligned to your business goals and technical environment.
Security, governance, and responsible AI are embedded throughout the lifecycle. SDG ensures the safe use of private data through IAM controls, encryption, and isolation, while implementing guardrails including content moderation, output validation, and risk mitigation strategies. We also establish monitoring, observability, auditability, and lifecycle management practices to ensure your solution remains performant, compliant, and continuously improving over time.
Show the rest of the publisher’s description (1 more line)
Our data scientists and strategists partner with your organization to build new AI-powered products, optimize operations, and navigate legal, financial, ethical, and brand considerations associated with generative AI. Whether accelerating internal productivity or launching customer-facing AI solutions, SDG helps you move confidently from experimentation to scalable, governed GenAI in production on AWS.
Highlights
Highlighted by the publisher on AWS Marketplace.
From Use Case to Production, we lead you though our Business‑led use case discovery and prioritization with Architecture design in mind using proven AWS GenAI patterns
AWS‑Native GenAI Architecture Model selection and orchestration using Amazon Bedrock and SageMaker Customization via prompt engineering, RAG pipelines, embeddings, and fine‑tuning Secure ingestion and use of private data with IAM, encryption, and isolation
Production, Governance, and Responsible AI Built‑in content moderation, output validation, and guardrails Responsible AI practices aligned to AWS expectations Monitoring, observability, auditability, and lifecycle management
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