Next live sessionThu, Nov 5 · 11 am ET · 8 am PT · 16:00 UKStarts soon
Run your AI inside your own AWS account, under controls you already trust.
Move your AI to Amazon Bedrock, inside the AWS account you already trust is a free, one-hour live workshop. Moving the model calls to Amazon Bedrock takes about two weeks, and your OpenAI and Anthropic SDK code keeps working. The hour covers the move and the platform around it that makes it safe to run.
What you'll get
- What moves in two weeks, and where the real work is
- The controls you inherit from your own AWS account
- Cost and quality compared on your own prompts
11 am ET · 8 am PT · 16:00 UK · online, one hour, free
Teams we've built for
- Comic Relief
AWS Premier Tier Services Partner, one of about 300 among more than 130,000 AWS partners.
The model calls move in about two weeks. Identity, guardrails and cost take the care.
Existing OpenAI and Anthropic SDK code keeps working on Amazon Bedrock, so the calls themselves move quickly. The work is the platform around them: identity, guardrails, evals and cost metering.
At the end, your models run inside the AWS account your security team already signs off, under controls it already trusts, on one bill and governed from one place.
What you'll take away from the hour
- 01
Your code keeps working
Code written against the OpenAI and Anthropic SDKs keeps working on Amazon Bedrock, so most of the work goes into the platform around it: identity, guardrails, evals and cost metering.
- 02
One place to govern
Your models run in your own AWS account, under controls your security team has already approved.
- 03
A plan with numbers
You get the target architecture and a costed roadmap in phases, which your engineering, security and finance leads can each check.
Five things we assess before anything moves
Your engineering, security and finance leads will each ask something different before they agree to a move. These are the questions we answer for them.
- 1
Workload shape
Calls per prompt type, how long the context runs, tool-call fan-out and the model mix, from your own usage export.
- 2
Cost curve
Spend today against Amazon Bedrock on demand and with provisioned throughput over twelve months, with the crossover marked.
- 3
Compliance scope
SOC 2, GDPR, the EU AI Act's duties for deployers, residency rules for your sector, and the audit trail each one asks for.
- 4
Model fit
For each prompt type, a head-to-head on your own prompts with Bedrock Evaluations, so a cheaper or closer model is chosen on evidence.
- 5
Deployment architecture
VPC endpoints, sizing, CloudTrail, observability, the fallback when a model or a region has a bad day, and what stays portable.
Where moving is the wrong answer, that is the answer, and you keep the cost model to re-run when things change.
What we bring
What makes the move safe to run is already built.
AK Run's Agent ControlPlane
Every AI agent's model calls go through one gate: only the models you approve, each call tied to the person who asked, cost tagged by team, and limits when you want them.
Runs in your own AWS account, on Amazon Bedrock AgentCore.
One hour, run by the engineers who do the work
See it
The same AI agent repointed from an outside model to Amazon Bedrock, live, with nothing else changed, then its answers scored side by side.
What changes around it
Identity, guardrails, evals and cost metering, one at a time, inside an AWS account.
Your questions
Bring what you run today and the question security keeps asking.
The private workshop: a day with your engineering, security and finance leads
Your AI usage assessed on the five dimensions, your prompts run on the models available in Amazon Bedrock beside your current provider's answers, and a target architecture with a phased, costed roadmap.
Who comes
The engineering lead for the AI features, the security or compliance lead, and whoever owns the cloud budget.
What to bring
The usage export and some traces from your current provider.
Your data
Prompts with personal data taken out, or an example set we build with you from what you describe.
What you leave with
- A clear call on whether to move everything, move some of it or stay where you are
- A cost model you can re-run
- Your prompts scored on Bedrock against today's answers
- A target architecture and a phased, costed plan
What clients say about working with us
I've been involved in many migrations over the years, and there's usually at least a few hiccups along the way. This was, by far, the smoothest I've experienced.
I knew I needed a partner who could earn [the company's] trust, jump in immediately to execute on their timeframe and architect for their compliance requirements.
The Armakuni team has provided both technical and product consulting on AI & automation initiatives keeping us ahead of the curve in terms of technology and optimal architecture.
- Under 0.25%of AWS partners are Premier Tier. We're one of about 300.
- 500+AWS customer launches
- 1,300+engineers across the UK, US, UAE, India and Canada
- 70%of the proofs of concept we scope reach production
Before you sign up
Is there a catch?
No. The hour is free, and so is the private day with your leads. If a project follows and AWS funding fits, we'll name the programme.
Are you only here to sell Amazon Bedrock?
We're an AWS partner, so that's fair to ask. The cost model compares your provider today with Bedrock over twelve months, and if staying wins, the model says so and you keep it.
Will we have to rewrite our code?
Usually not. Existing OpenAI and Anthropic SDK code keeps working on Amazon Bedrock; the work is identity, guardrails, evals and cost metering around it.
Do we lose the models we use?
Many of the same model families run on Amazon Bedrock. Where yours doesn't, we test the closest ones on your own prompts.
What happens after?
Moving the model calls takes about two weeks. The platform around them follows in phases, in the order the plan sets.
Move your AI to Amazon Bedrock, inside the AWS account you already trust
Thursday, November 5, 11 am ET · 8 am PT · 16:00 UK. Starts soon.
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