Amazon Bedrock Development & Implementation
Amazon Bedrock engineering for real AI requirements
Codersarts helps organizations build, implement, integrate, customize, evaluate, and deploy generative AI applications using Amazon Bedrock.
Our AI engineers work across foundation models, prompt engineering, RAG, agents, knowledge bases, tool use, model evaluation, APIs, application development, and AWS infrastructure to turn generative AI requirements into production systems.
What we can do with Amazon Bedrock
Build | Implement | Integrate |
Build generative AI applications, assistants, agents, RAG systems, and AI-powered workflows. | Implement Amazon Bedrock around an existing AI or business requirement. | Connect foundation models and Bedrock capabilities with applications, APIs, databases, and enterprise systems. |
RAG | AI Agents | Knowledge Systems |
Build retrieval-augmented generation systems using enterprise documents and data. | Build agents that use models, knowledge, tools, APIs, and business workflows. | Build AI systems that retrieve and use organization-specific information. |
Customize | Evaluate | Deploy |
Customize AI behavior through prompts, model configuration, knowledge, tools, and supported model adaptation approaches. | Evaluate model responses, relevance, accuracy, safety, latency, and business performance. | Deploy Bedrock-powered applications through APIs, cloud infrastructure, and production systems. |
What are you trying to accomplish with Amazon Bedrock?
Build | Implement | Connect |
Build AI applications using foundation models available through Bedrock. | Implement Bedrock into an existing application, product, or enterprise workflow. | Connect Bedrock with databases, documents, APIs, applications, and business systems. |
Retrieve | Reason | Act |
Give AI applications access to enterprise knowledge through retrieval and knowledge bases. | Build AI workflows that use models to analyze information and determine appropriate next steps. | Connect agents with approved tools and APIs so they can perform defined actions. |
Automate | Evaluate | Optimize |
Automate knowledge, customer-support, research, document, and business workflows. | Evaluate models and applications against quality, safety, and business requirements. | Improve response quality, latency, reliability, scalability, and operating cost. |
What can we build with Amazon Bedrock?
Generative AI Applications | RAG Applications | AI Assistants |
Build applications that use foundation models for generation, analysis, summarization, classification, and reasoning. | Build document and knowledge-grounded AI applications. | Build assistants for employees, customers, developers, researchers, and operations teams. |
AI Agents | Document AI Applications | Customer Support AI |
Build agents that use models, knowledge, tools, APIs, and workflows. | Combine document processing, retrieval, LLMs, and business workflows. | Build AI-powered knowledge retrieval, response generation, ticket assistance, and support workflows. |
Enterprise Search | Research Assistants | AI Workflow Automation |
Build natural-language interfaces for enterprise knowledge and information discovery. | Build systems for document analysis, research, summarization, and information synthesis. | Connect Bedrock with business systems to automate defined AI-powered workflows. |
Amazon Bedrock solutions for different customers
Enterprise | Companies | Software & Product Companies |
Build enterprise AI applications connected to organizational knowledge, systems, and workflows. | Add generative AI capabilities to existing applications and business processes. | Integrate Bedrock-powered AI into products, SaaS platforms, and customer experiences. |
Startups | Agencies & Consultancies | Implementation & Delivery Partners |
Build AI-native products without developing foundation models from scratch. | Add Bedrock engineering capacity to client generative AI projects. | Extend delivery teams with AWS, AI, RAG, agent, and application engineering. |
Get the Amazon Bedrock expertise you need
Bedrock Developer | Generative AI Engineer | AI Agent Developer |
Build Bedrock-powered applications, APIs, prompts, integrations, and AI workflows. | Design and implement LLM applications, RAG, evaluation, model workflows, and AI systems. | Build agents that retrieve information, use tools, and execute approved workflows. |
RAG Engineer | AWS AI Engineer | Generative AI Engineering Team |
Build document ingestion, retrieval, embeddings, knowledge, and generation workflows. | Combine Bedrock with AWS infrastructure, data, security, APIs, and applications. | Combine AI, software, data, cloud, agent, and integration engineering. |
Amazon Bedrock technology ecosystem
Foundation Models | AI Application Layer | Knowledge & Data |
Amazon Bedrock · Foundation Models · Model APIs · Model Configuration | LLM Applications · AI Assistants · Agents · RAG | Documents · S3 · Databases · Knowledge Bases · Vector Search |
AWS Integration | Development | Production Infrastructure |
Lambda · API Gateway · Step Functions · EventBridge | Python · APIs · SDKs · Backend Applications | IAM · CloudWatch · ECS · EKS · Serverless · Security |
From generative AI requirement to production
01 — Understand | 02 — Design | 03 — Build |
Understand users, business workflows, knowledge sources, AI requirements, security, and expected outcomes. | Select appropriate models, prompts, retrieval, tools, agents, integrations, and application architecture. | Build prompts, RAG pipelines, agents, APIs, applications, workflows, and supporting infrastructure. |
04 — Evaluate | 05 — Deploy | 06 — Improve |
Evaluate response quality, grounding, safety, latency, reliability, and business performance. | Deploy the Bedrock-powered application into production AWS infrastructure. | Improve prompts, retrieval, model selection, application performance, cost, and reliability. |
How you can work with Codersarts
Amazon Bedrock Implementation | Dedicated GenAI Engineer | Bedrock Application Development |
Implement Bedrock around a defined enterprise or product AI requirement. | Add ongoing generative AI engineering capacity to your team. | Build complete Bedrock-powered applications and AI workflows. |
RAG Implementation | Bedrock Agent Development | Ongoing GenAI Engineering |
Build enterprise knowledge and document-grounded AI applications. | Build agents that interact with knowledge, tools, APIs, and business systems. | Continue application development, evaluation, optimization, and production improvement. |
Why Codersarts for Amazon Bedrock?
AI + AWS Engineering | Implementation Focus | Production GenAI |
Combine generative AI, software, data, AWS, API, and cloud engineering. | Build Bedrock around an actual application or business requirement rather than a standalone AI demo. | Focus on evaluation, security, reliability, latency, scalability, integration, and cost. |
RAG + Agent Expertise | Flexible Capacity | Project or Ongoing |
Build knowledge-grounded applications and tool-using AI agents. | Access a Bedrock developer, GenAI engineer, RAG engineer, AI agent developer, or complete team. | Engage for implementation, application development, integration, deployment, or ongoing engineering. |
Related Amazon Bedrock Solutions
Generative AI Development | RAG Implementation | AI Agent Development |
Build applications using foundation models for generation, analysis, and intelligent workflows. | Build AI applications grounded in enterprise documents and knowledge. | Build AI agents that retrieve information, use tools, and execute defined actions. |
Enterprise AI Assistant | Document AI + Bedrock | AWS AI Integration |
Build internal and customer-facing AI assistants. | Combine document processing, retrieval, and foundation models. | Connect Bedrock with AWS services, APIs, databases, and enterprise applications. |
Frequently asked questions
What Amazon Bedrock services does Codersarts provide?
We provide Amazon Bedrock development, implementation, RAG development, AI agent development, generative AI applications, integrations, evaluation, deployment, optimization, and ongoing AI engineering.
Can Codersarts build a generative AI application using Bedrock?
Yes. We can build applications using foundation models available through Bedrock and connect them with your application, data, knowledge, and business workflows.
Can you build RAG applications with Amazon Bedrock?
Yes. We can build document ingestion, processing, retrieval, knowledge, prompt, generation, evaluation, and application layers for RAG systems.
Can you build AI agents using Amazon Bedrock?
Yes. We can build agents that combine foundation models with knowledge, tools, APIs, and controlled business actions.
Can you connect Bedrock with our existing systems?
Yes. We can integrate Bedrock-powered applications with APIs, databases, S3, Lambda, enterprise applications, CRM, ERP, and other AWS services.
Can you evaluate a Bedrock application?
Yes. We can design evaluation around response quality, grounding, relevance, safety, latency, reliability, and business-specific metrics.
Can you optimize the cost and performance of a Bedrock application?
Yes. We can evaluate model selection, prompts, retrieval, architecture, caching, invocation patterns, and infrastructure to improve performance and operating efficiency.
Can I hire a Bedrock developer?
Yes. You can engage a Bedrock developer, generative AI engineer, RAG engineer, AI agent developer, AWS AI engineer, or a broader generative AI engineering team.
Have an Amazon Bedrock requirement?
Tell us what you're trying to build, implement, integrate, retrieve, automate, or deploy.