Modernize Your AI on Amazon Bedrock
Partner with Basis to move your existing AI applications, models, prompts, and data pipelines to Amazon Bedrock with a secure, structured migration strategy.
Basis’ AI Migration to Amazon Bedrock solution enables organizations to securely migrate existing AI workloads to Amazon Bedrock with minimal disruption. Combining deep cloud migration expertise with advanced AI model evaluation, we provide end-to-end support throughout the migration lifecycle, from assessing existing AI implementations and evaluating foundation models to refactoring prompts, redesigning application architectures, and optimizing AI workloads for AWS.
Our Bedrock experts help organizations align their existing AI environment with business goals and performance requirements, with the goal of improving scalability, cost efficiency, security, and operational performance. By incorporating embedding and multimodal capabilities and leveraging AWS-native foundation models, including Amazon Titan, we help organizations confidently modernize AI workloads and maximize the long-term value of AI on AWS.
Whether you’re migrating AI workloads and data pipelines to AWS-native infrastructure, modernizing existing AI applications, or building a business case for AI migration, Basis provides the technical expertise and proven methodology to help you successfully transition to Amazon Bedrock.
Organizations are increasingly migrating AI workloads to Amazon Bedrock to simplify operations, reduce costs, and build a secure, scalable foundation for future innovation. As AI environments mature, organizations often face new challenges such as model retirements, scaling constraints, growing multi-model requirements, repeated security reviews, regional data-processing needs, and rising cross-cloud egress costs.
Amazon Bedrock helps address these challenges by consolidating AI workloads within a single AWS-native platform, reducing operational complexity while giving teams the flexibility to evaluate and adopt the foundation models best suited to each use case.
Managing multiple AI providers often results in fragmented billing, duplicated infrastructure, unpredictable inference costs, and additional data egress expenses. Consolidating workloads on Amazon Bedrock improves visibility into AI spending, reduces unnecessary cross-cloud data movement, and creates opportunities to optimize long-term operating costs.
Managing multiple AI providers often results in fragmented billing, duplicated infrastructure, unpredictable inference costs, and additional data egress expenses. Consolidating workloads on Amazon Bedrock improves visibility into AI spending, reduces unnecessary cross-cloud data movement, and creates opportunities to optimize long-term operating costs.
AI models evolve quickly, and organizations need the flexibility to adapt. Amazon Bedrock provides access to multiple leading foundation models through a single API, allowing teams to evaluate, compare, and switch models as performance requirements or model availability changes, without rebuilding the surrounding AI infrastructure.
Keeping AI workloads within AWS enables organizations to leverage native security, identity management, networking, encryption, monitoring, and governance capabilities. This helps protect sensitive business data, simplify compliance, and establish stronger operational controls across AI environments.
Consolidating AI infrastructure on AWS reduces engineering complexity by centralizing deployment, monitoring, access management, and operational workflows. This enables development teams to spend less time managing infrastructure and more time delivering business value.
As AI adoption grows, organizations often encounter rate limits, regional processing requirements, or infrastructure constraints. Migrating to Amazon Bedrock enables businesses to easily adopt new foundation models, expand agentic AI capabilities, and scale AI workloads as their business and technology needs evolve.
Basis follows a proven 5-stage framework that helps organizations reduce migration risk while accelerating AI modernization to Amazon Bedrock.
Stage 1
Discovery & Strategy
Every migration begins with understanding your current AI environment and defining what success looks like. Working closely with business and technical stakeholders, we identify opportunities to modernize AI workloads while aligning your migration strategy with business objectives.
Stage 2
Assess
Once business objectives are established, Basis performs a comprehensive technical assessment to determine migration readiness and identify the most effective modernization strategy. This assessment provides visibility into workload complexity, application dependencies, cost optimization opportunities, and potential risks before migration begins.
Stage 3
Mobilize
With a validated migration strategy in place, Basis transitions AI workloads to Amazon Bedrock using a phased implementation approach that minimizes disruption while modernizing the underlying AI architecture.
Rather than simply migrating prompts or APIs, we redesign AI workloads to fully leverage AWS-native services, improving scalability, observability, security, and long-term operational efficiency.
Stage 4
Validation & Hardening
Before production deployment, Basis validates that migrated workloads meet functional, security, operational, and performance requirements. This stage ensures your AI platform is production-ready and equipped with the governance, monitoring, and operational controls needed for long-term success.
Stage 5
Expansion & Continuous Optimization
Once workloads are successfully running on Amazon Bedrock, Basis works with your team to identify additional opportunities to expand AI across the organization while continuously improving performance and business outcomes.
Basis helps customers modernize applications on AWS through our DevOps, migration, modernization, and AI engineering services. Since 2013, we've served startups like Reklaim and OneLine Health to Fortune 500 companies like HBO and CooperSurgical. Our combined AI expertise and proven migration & modernization framework empowers organizations to migrate AI workloads to Amazon Bedrock with confidence while minimizing disruption and maximizing long-term value.
As an AWS Advanced Tier Services Partner, Basis brings more than a decade of experience helping organizations design, migrate, modernize, and operate workloads on AWS. Our team combines AI, cloud architecture, and DevOps expertise to support customers from initial strategy through deployment and optimization. For eligible engagements, Basis also helps customers identify AWS funding opportunities that can reduce migration and modernization costs.
Organizations migrate AI workloads to Amazon Bedrock to simplify AI operations, improve cost visibility, strengthen security and governance, reduce cross-cloud data movement, and access multiple leading foundation models through one AWS-native environment. Bedrock also provides greater flexibility to evaluate and switch models as business requirements evolve. Organizations can also utilize Amazon Bedrock AgentCore to support the development and operation of more advanced agentic AI workloads.
Common migration signals include upcoming contract renewals or model retirements, scaling or rate-limit challenges, in-region data processing requirements, growing multi-model needs, fragmented provider costs and APIs, repeated security reviews, and rising cross-cloud data egress costs. Basis evaluates these factors alongside your existing architecture, workload performance, security requirements, and business objectives to determine whether migration to Amazon Bedrock is the right path and which workloads should be prioritized.
Basis helps organizations migrate a wide range of AI workloads to Amazon Bedrock, including conversational AI, document processing, summarization, classification, semantic search, retrieval-augmented generation (RAG), AI assistants, embeddings, and multimodal applications. Every engagement begins with a comprehensive assessment to determine the most effective migration and modernization strategy based on your business and technical requirements.
Basis helps organizations migrate AI workloads from third-party AI platforms, including OpenAI, Azure, GCP, and other AI environments to Amazon Bedrock. Our team evaluates your existing architecture, benchmarks foundation models, refactors prompts, modernizes integrations, and validates performance to help ensure a smooth transition with minimal disruption.
Our engagement includes discovery workshops, AI workload assessment, migration planning, foundation model evaluation, prompt refactoring, architecture modernization, implementation, fine-tuning, prompt parity, testing and validation, knowledge transfer, and post-migration optimization. Every engagement follows our proven 5-stage AI Migration & Modernization Framework to help ensure a structured, low-risk migration.
Not necessarily. Some AI applications require only prompt updates and foundation model replacement, while others benefit from broader application or infrastructure modernization. Our migration experts will evaluate your existing environment and recommend the most efficient migration strategy based on your architecture, business objectives, and long-term goals.
Basis follows a structured migration methodology that begins with discovery, assessment, and migration planning before implementation begins. Throughout the engagement, we validate foundation models, test migrated workloads, and optimize performance to help reduce business disruption and ensure production readiness.
Yes. Basis evaluates your existing AI architecture, operating costs, and business objectives to develop a data-driven migration business case. This includes migration readiness, Total Cost of Ownership (TCO) analysis, modernization opportunities, and recommendations to support informed stakeholder decision-making.
Move your existing AI applications, models, prompts, and data pipelines to Amazon Bedrock with a secure, structured migration strategy.
START YOUR AI MIGRATION