AI agents.
Built for your business.
Turn manual tasks into connected workflows. Nuvens helps you design, build and run AI agents on AWS — with the right access, visibility and approvals.
Connect the tools and information your teams already use.
Define permissions, approvals and operating boundaries.
Start with a practical problem and a measurable outcome.
AI that can help
get the work done.
An AI agent can go beyond answering a question. It can gather information, use approved tools and work through a task across your systems.
The opportunity is practical: less time searching, checking and copying information. The challenge is connecting it properly. That is where Nuvens can assist.
Where could an agent
make a difference?
Choose a workflow below. Each is an example of what we could explore together, shaped around your data, systems and approval requirements.
From gathered information to a checked legacy-system entry.
Gather information from the sources agreed for the workflow, check it, and prepare the entry in the browser-based legacy system. Define approvals and send missing or inconsistent information to a person for review.
Amazon Bedrock AgentCore.
A foundation for production agents.
AgentCore provides managed services for running agents, connecting tools, managing access and observing behaviour. We help turn those building blocks into a workflow that fits your business.
Run and scale
AgentCore Runtime hosts agents in isolated sessions, with support for different models and frameworks.
Connect your tools
Gateway makes approved APIs, Lambda functions and MCP tools available to your agent.
Control access
Identity and Policy help define who can use the agent and which tool calls are permitted.
Work through browser screens
AgentCore Browser lets an agent navigate web applications, read information and fill forms, including where an API is unavailable.
See what happened
Observability provides traces and operational visibility to help investigate performance and failures.
Test the quality
Evaluations help assess behaviour and reliability using defined tests and production traces.
Technology reference: Amazon Bedrock AgentCore ↗
A clear path.
From first idea to everyday use.
We start with the work you want to improve, then build the integrations and controls needed to put an agent into use.
Find the right use case
Map the task, the people involved and the outcome you want. Decide what the agent should do and when a person should take over.
Design the controls
Agree the data sources, permissions, approval points and deployment requirements before connecting the agent to your systems.
Prove the approach
Build a focused proof of concept around one workflow. Test it with representative tasks and agree what good performance looks like.
Connect and build
Integrate the approved tools and knowledge sources. Configure the agent, its operating boundaries and the information it retains.
Test and deploy
Check accuracy, access controls, failure handling and cost. Introduce the workflow to a defined group of users before a wider rollout.
Operate and improve
Review traces, feedback and running costs. Refine the workflow and agree the handover or ongoing support that suits your team.
Scope, delivery, pricing and ongoing support are agreed around your use case.
Give the agent a job.
Give it clear boundaries.
Useful automation needs more than a model. We design the workflow around the information it can see, the actions it can take and the people who stay accountable.
- ✓Approved data sources and tools
- ✓Permissions matched to each task
- ✓Human approval before agreed actions
- ✓Traceability and quality checks
- ✓Cost visibility and operational ownership
Before you get started.
Do we need to replace our existing systems?
Often we can work with the systems you already use, through APIs or browser interfaces. We assess access, connectivity and compatibility before agreeing the approach.
Can we automate a system without an API?
For browser-based systems, an agent can gather information, navigate screens and fill forms using AgentCore Browser. A missing API does not necessarily make a workflow permanently manual. We assess each system and process before agreeing what can be automated.
What about installed desktop applications?
AgentCore Browser works with web applications. Installed desktop applications need a separate desktop automation approach, which we assess as part of the workflow design.
Does the agent have to act automatically?
No. It can begin by gathering information and preparing recommendations or drafts. Approval points and any automatic actions are explicit design decisions.
Where does the agent run?
AgentCore Runtime is a managed AWS service for hosting agent code. We design the deployment around your AWS account, identity, networking and data requirements. Model access and connected services are considered separately.
What does a proof of concept cost?
It depends on the workflow, integrations and testing involved. We agree the delivery scope and estimate the associated AWS consumption before starting.
Where could an AI agent
help your business?
Tell us about the task your team repeats, the systems it touches and the outcome you want. We will discuss where an agent could help — and how Nuvens can assist.
Discuss your use case.
A practical conversation about the opportunity, the controls and the next step.
Talk to Nuvens ↗