We design and build generative AI applications and agents on AWS, using Amazon Bedrock and serverless services, connected to your data and systems, with access controls and running costs you can see before you start.
Amazon Bedrock: the AI models
AI modelAWS Lambda and API Gateway: logic and integrations
SystemDynamoDB and S3: data and documents
SystemYour team: approvals and review
Human approvalGenerative AI on AWS lets you use foundation models through Amazon Bedrock, combined with the AWS services that run your data, logic and integrations.
Answer staff or customer questions from your approved documents and policies.
Draft replies, summarise conversations and update records, with human review.
Extract data from invoices, forms and contracts into your systems.
AI steps inside AWS Lambda workflows that scale down when idle.
Connect AI on AWS to CRM, ERP and helpdesk systems, including Zoho.
Role-based access, approved data sources and clear escalation rules.
In an example pilot of about 3,000 conversations a month, model costs stay low. Setup is a fixed quote after a scoping call.
*Example: ~4,000 input and ~800 output tokens per conversation at public AWS list prices (US East, September 2026). Excludes taxes, storage and API Gateway usage, which we estimate during scoping. AWS prices may change.
For a scoped use case: a working demo in week one, implementation in week two, and Phase 1 complete by week three or four.
The task, the data it needs, and what good output looks like.
Models, services, access and costs, agreed before the build.
The application on AWS, tested against real and unusual cases.
Go live with monitoring, then improve based on use.
These were AWS application projects, not generative AI deployments. They show the serverless, data and integration work a generative AI build runs on.
A vendor CRM built on AWS Lambda, DynamoDB, S3 and API Gateway for a medical-device and healthcare provider, integrated with procurement tools and Zoho CRM, with approval workflows and real-time dashboards.
Read the case study →A custom AWS-based applicant tracking system for a U.S. healthcare and IT staffing agency handling high-volume hiring across diverse roles.
Read the case study →Sixty One Steps works across AI automation, custom software and business-system integration. We start with your processes and existing tools, then define the data, rules, integrations and human decisions an implementation needs.
Amazon Bedrock is an AWS service that gives access to foundation models from several providers through one API, so you can build generative AI applications without running your own model infrastructure.
Mostly model usage, billed per use. In our example of about 3,000 conversations a month, model costs are roughly US$1–17 a month depending on the model. Our setup fee is a fixed quote after scoping.
AWS states that Amazon Bedrock does not use your prompts or outputs to train its base models. We confirm your data residency and access requirements during scoping.
Yes, where those systems allow integration. Our AWS vendor CRM project, for example, integrated with Zoho CRM and the client’s procurement tools.
A working demo in week one, implementation in week two, and Phase 1 complete by week three or four for a scoped use case. See custom AI agent development for how we design and test agents.
Tell us the use case. We will outline the architecture, the running costs and, for a scoped use case, a first build you can see working in week one.