Your next AI workflow. Built on AWS.
We build AI workflows in your AWS account. Use Amazon Bedrock to put your enterprise knowledge to work, with access checks before retrieval and human approval before consequential actions.
A working model is only the start.
The answer needs a reliable source
Your documents live in S3 or business systems. An AI answer must point back to the current source and respect who can read it.
An agent needs boundaries
A service account with broad permissions can turn a small mistake into a business problem. Define which tools an agent can call and which actions need approval.
Data access must survive the handoff
A permission on a source table does not automatically protect a copied document or vector index. Test access at every retrieval boundary.
Your team has to operate the result
Set a cost budget and quality threshold before launch. Give the team a runbook with a clear owner for failures.
AWS services, tied to the workflow
Amazon Bedrock applications
Select a model against your own evaluation set. Build assistants with clear refusal behavior when the available evidence cannot support an answer.
Knowledge Bases & Amazon S3
Connect approved documents to Amazon Bedrock Knowledge Bases. Apply user-specific access checks before retrieval and return source citations with the answer.
AgentCore & workflow integration
Scope agent runtimes and tool access with Amazon Bedrock AgentCore. Use AWS Lambda or Step Functions where the process needs a defined execution path.
Governed data foundations
Design S3 data foundations with AWS Glue Data Catalog. Use Lake Formation permissions for supported Athena queries, with separate authorization for any downstream AI retrieval.
Identity & operating controls
Define least-privilege IAM roles and encryption requirements. Configure CloudWatch monitoring and CloudTrail records for supported AWS API activity, with application-level traces for the workflow.
Evaluation & handover
Test denied access as carefully as successful answers. Measure response quality and cost per completed task, then hand over the code with deployment instructions.
Manufacturing
Scope an SOP assistant that cites the approved procedure and escalates unanswered questions.
Pharma & Life Sciences
Design document review support around approved sources and your validation requirements.
Financial Services
Connect policy search to evidence collection, with explicit access boundaries.
Healthcare
Assess data handling requirements and service eligibility before a clinical workflow build.
From workflow to working tool in two weeks.
Scope and sign
We define the workflow, the deliverables, and the acceptance criteria, and sign an agreement on them before anything starts.
Build
We build the tool in your environment, with Claude Code and automated evaluation against your own data.
Pay when it works
$10,000, due only after every criterion in the signed agreement is met. Nothing before that.
We scope one workflow with you and sign the deliverables and acceptance criteria before the build. We build it in your environment in two weeks. You pay $10,000 only after every criterion is met. Nothing upfront. Data platform programs and wider portfolios are scoped separately. AWS usage is separate from the build fee.
Tell us the workflow →Questions buyers ask.
Can we keep our existing AWS environment?
Yes. We scope the build around your AWS account and existing systems. We agree the deployment region, identity model, and data boundaries with your team before implementation.
Can an AWS workflow work with Microsoft 365?
Yes. We can connect approved Microsoft 365 sources or business applications through their APIs. We scope identity mapping and document permissions explicitly so a connector does not broaden access.
Does Lake Formation secure every AI answer automatically?
No. Lake Formation governs supported data access paths. Copies in a document store or retrieval index need their own access controls. We test that each user can retrieve only the information they are permitted to see.
What do we agree before the build starts?
One workflow, its source systems, and the acceptance tests. Those tests cover the useful result and failure cases such as denied access or missing evidence. The scope also names the AWS usage budget and handover requirements.
Ready to ship AI that actually works?
Send us the workflow. We return a fixed scope, price, and acceptance criteria in 48 hours. You pay $10,000 only after it works.
Tell us the workflow →