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AWS Premier Tier Services Partner
one of 93 in the US, of 130,000 worldwide

AWS AI Services Competency AWS Migration and Modernization Competency

Move your AI workloads to Amazon Bedrock,
inside the account you already audit.

The question isn't which model. It's where it runs, who it acts as and what it's allowed to touch. The Amazon Bedrock Migration Workshop is one day with your engineering, security and finance leads, and you leave with a findings report, a target architecture and a costed roadmap.

Where your AI calls run, today and on Amazon Bedrock

Today
Your AWS accountYour AI agent
A model maker's API

Calls as One shared key nobody owns

Data Leaves on every call

Cost Nobody can say per team

Controls Another vendor to vet

On Amazon Bedrock
Your AWS accountYour AI agentAmazon Bedrock

Calls as Its own AWS identity

Data Kept from the model maker

Cost Per token, on your AWS bill

Controls Your IAM, CloudTrail and KMS

about 2 weeks

to repoint every call. Code written for the model makers' own SDKs keeps working: the code stays and the boundary moves.

What the day leaves you with

  • Morning

    We map every model call.

    • Models, SDKs, endpoints and who calls them
    • Where inference runs, under whose identity
    • AI spend beside unused AWS commitment; Bedrock isn't cheaper by default
  • Afternoon

    We design the target.

    • Amazon Bedrock in the account and Region you audit
    • AgentCore runtime, gateway, identity and tool policy
    • Guardrails, evals and routing by cost tier, modeled on your real volumes
  • End of day

    A costed roadmap your teams own.

    • Findings report and target architecture
    • A phased plan, with effort and cost
    • A business case, with us or without us
Ours, engineering-led
Solutions architectThe engineers who'd do the work
Yours, the leads who decide
EngineeringSecurityFinance

More than 500 AWS customer launches
1,300+ engineers

The calls move in about two weeks. The platform around them is the real project.

Identity, rules, answers that hold and cost by team: the work around the calls is ours.

AWS

Amazon Bedrock serves models

Ours

We repoint the calls

Ours

We wire identity and rules

Ours

We prove the answers

Ours

We meter the cost

Same models, inside.New models, and some agent features, usually arrive after their maker's own API.

Base URL and credentials.A VPC endpoint; credentials from its own AWS identity.

No shared key.AgentCore Identity; a Cedar policy at the gateway, deny by default.

Same answers first.Your prompts scored with Bedrock Evaluations, in shadow first.

Cost by team.Every call on a name: AK Run's Agent ControlPlane.

Each AI agent, sorted firstRepointBuild around itRebuild a partStays where it is

Same code; prompts and evals rerun

Identity, policy and who approves it

Connectors, memory, UI from its platform

Its model not yet in your Region

What it has done for clients

A government case platform 80–90%

of form onboarding automated on Amazon Bedrock

6 monthsWeeks
A U.S. cinema chain 30%

faster call handling, with AI agents on Amazon Bedrock AgentCore

BeforeAfter
Ryno Strategic Solutions under 2 of 4 weeks

to production-ready: AI call analysis on Amazon Nova

PlannedReady

An executive search firm~20 tenant application stacks moved before its vendor's shutdown, without disruptionCTO, a financial services feedback platformOn the migration: "By far, the smoothest I've experienced."The proofs of concept we scope70% reach production

Book the Amazon Bedrock Migration Workshop.

  • One day, booked for a date that suits you
  • Free: AWS funding typically covers it
  • Your engineering, security and finance leads
  • A costed roadmap, yours with us or without us

Scan to book
hello@armakuni.com
or ask your AWS account team