Blueprint and governance
The model shortlist, the region and cross-Region inference setting, the Guardrails policy and log retention are agreed with the business owner, security and data protection before any account is opened to users.
Platform implementation
Amazon Bedrock
We build generative AI services on Amazon Bedrock inside your AWS accounts, choosing a model per task and adding Guardrails, Knowledge Bases and evaluation so each service can be trusted in production.
Bedrock offers models from several providers through one API, so the work starts with picking a model for each task on evidence from your own data rather than on reputation. AWS has regions in the UAE and Bahrain, but Bedrock model availability differs by region and cross-Region inference can route requests elsewhere, so we check both against your obligations under the UAE and Saudi data protection laws before design.
Retrieval runs through Bedrock Knowledge Bases on a vector store such as OpenSearch Serverless or Aurora PostgreSQL, Bedrock Agents call your APIs through action groups, and Bedrock Guardrails filter harmful content, sensitive information and off-topic requests. Traffic stays on private VPC endpoints, IAM policies limit which roles may invoke which models, and model invocation logging feeds CloudWatch or S3 for audit.
Amazon Web Services, Amazon Bedrock, and related marks are trademarks of Amazon.com, Inc. or its affiliates.
How we implement Amazon Bedrock
From blueprint to go-live and beyond: configuration, integration and support from one accountable team.
Model evaluation
Evaluation jobs and human review that compare candidate models on your own prompts for accuracy, Arabic quality, latency and cost.
Multilingual embeddings
Embedding models that handle Arabic, such as Cohere's multilingual model, tested for retrieval quality on mixed Arabic and English documents.
Cost and throughput
On-demand use, batch inference or Provisioned Throughput chosen per workload, with cost allocation tags and a budget for each application.
Hypercare and managed support
Bedrock adds models and retires older versions regularly, so we track model lifecycle dates, rerun evaluations before moving to a new version, and watch invocation errors, Guardrails interventions, token spend and latency.
When Amazon Bedrock is the better route
Bedrock fits organisations already running on AWS that want a choice of models from several providers under one set of IAM, network and logging controls.
- An AWS landing zone with accounts and VPCs set aside for AI workloads
- Data classification that decides which sources a model may use
- A shortlist of tasks with sample prompts and expected answers
- A decision on whether cross-Region inference is acceptable
Plan Amazon Bedrock with Hosn Al Tomoh
Tell us what the platform needs to do and when. We will propose a first phase with scope, team and an itemised quotation.