AWSAIConsulting

Amazon Bedrock Implementation

Amazon Bedrock provides managed access to foundation models. We help you evaluate models for your task, build retrieval-augmented generation (RAG) pipelines, and configure agents to use approved tools within the permissions and review steps you define.

• Foundation model selection and evaluation for your use case
• Knowledge base configuration with Amazon OpenSearch and S3
• Bedrock Agents with tool use and action groups
• Guardrails configuration for content filtering and PII protection
• Cost optimization through model routing and caching

SageMaker ML Operations

When a managed foundation model is not the right fit, SageMaker AI can support custom model training, fine-tuning, deployment, and monitoring. We design the lifecycle stages your workload needs, from data preparation through inference and operations.

• Custom model training with SageMaker Training Jobs
• Model fine-tuning for domain-specific performance
• SageMaker Pipelines for automated ML workflows
• Real-time and batch inference endpoint management
• Model monitoring, drift detection, and retraining automation

AWS AI Architecture Design

An AI workload involves more than the model layer. We design the data, application, model-serving, workflow, security, and monitoring components needed for your use case, then test how they work together.

• Event-driven architectures with Lambda and Step Functions
• Data lake and feature store design with S3, Glue, and Athena
• Vector database integration for semantic search and RAG
• API Gateway and AppSync for AI-powered application layers
• Multi-region and high-availability configurations

Data Pipelines for AI on AWS

Useful AI depends on relevant, accessible, and well-managed data. We build the path from ingestion and transformation through quality checks and delivery to model training or inference.

• Data ingestion with Kinesis, MSK, and EventBridge
• ETL and transformation with AWS Glue and Step Functions
• Data quality validation and lineage tracking
• Amazon Kendra for enterprise document understanding
• Real-time feature computation for ML inference

Security, Compliance & AI Governance on AWS

AI workloads add model access, prompt and response handling, tool permissions, evaluation, and runtime monitoring to the cloud security model. We design those controls around your data, risk, and review requirements.

• IAM policies for model and data access control
• VPC isolation and PrivateLink for AI endpoints
• CloudTrail and CloudWatch for AI system observability
• Bedrock Guardrails for content safety and PII handling
• Compliance mapping for HIPAA, SOC 2, FedRAMP, and industry standards

AWS MAP Funding & Migration

AWS offers migration programs for some qualifying workloads. Tactical Edge can assess your workload, prepare the business case and migration plan, and submit the information AWS needs to make its eligibility and benefit decision.

• Program-readiness assessment and business-case development
• Workload migration planning for AI-ready infrastructure
• Legacy system modernization with AI capabilities
• Cost models based on your usage, architecture, and contract assumptions
• Ongoing reviews of model, infrastructure, and commitment-plan costs

What is AWS AI consulting?

AWS AI consulting helps organizations design, build, test, and operate AI and machine-learning workloads on Amazon Web Services. Depending on the workload, this can include architecture design, Amazon Bedrock or SageMaker AI implementation, data engineering, evaluation, security controls, and ongoing operations.

What is Tactical Edge's AWS partner status?

Yes. Tactical Edge is an AWS Advanced Tier Services Partner with a Strategic Collaboration Agreement (SCA). We bring AWS architecture and AI implementation experience into one delivery team and coordinate with AWS when a customer and workload qualify for an AWS program.

What AWS AI services does Tactical Edge implement?

Tactical Edge selects AWS services around the customer workload. Common building blocks include Amazon Bedrock for generative AI, SageMaker AI for machine learning, AWS Lambda and Step Functions for workflow coordination, Amazon S3 and AWS Glue for data pipelines, and AWS identity, logging, and monitoring services.

Can I get AWS funding for AI projects?

AWS offers programs for some qualifying workloads. Tactical Edge can assess your workload, prepare the business case and migration plan, and submit the information AWS needs to make its eligibility and benefit decision.

How is AWS AI consulting different from general cloud consulting?

Compared with a general cloud engagement, an AI engagement also addresses model selection and evaluation, training or inference, retrieval, prompt and response handling, tool permissions, monitoring, and AI-specific governance. Those concerns still depend on sound compute, storage, networking, identity, and data architecture.