Agentic Tools for Business Systems on AWS | Cloud Life Consulting

Companies adopt AI assistants to make their people more productive, only to find they can't scale them across teams or lines of business because the assistant answers from general knowledge instead of the systems that hold their real-time data. As a result, answers come back wrong or stale, and people stop using it. Cloud Life Consulting connects the assistants your teams already use to the systems your business runs on, so they work from live data, get real work done, and can only do what each person is already allowed to do. We build it with Amazon Bedrock AgentCore Gateway on the interfaces your systems already have, so nothing is rebuilt and nobody maintains a custom integration per system.

DISCOVER

API review -- We read your backend source code or endpoint documentation end to end and pick out the operations that make good tools. We start with read-only lookups such as device state, orders, test results, tickets or inventory. Anything that writes to a system is identified and set aside until you approve it.

Identity and authorization design -- Your agent signs in through the identity provider you already run, whether that's Auth0, Amazon Cognito or another OIDC provider. We then set an authorization scope on every tool, so the agent can only call what its user is allowed to call and nothing more.

Platform decision -- We decide between AgentCore Gateway and a custom MCP server against your requirements, and we write the reasons down so you can see why we landed where we did.

BUILD

AgentCore Gateway deployment -- We deploy Gateway in your AWS account and wire it to your identity provider. Gateway reads your API definition, publishes each operation as a tool, and routes calls to Lambda targets that talk to your API where it already runs. The IAM roles, logging and Terraform land in your repository. We start in staging with read-only tools and promote to production on your approval.

Tool sets -- A tool set is a group of related operations from your API, each backed by a Lambda target with its own authorization scope. We add write operations once your users have worked with the read paths. Each additional system or line of business becomes another tool set on the same gateway, under the same identity model, rather than a new integration.

Custom MCP server -- Where Gateway isn't the right fit, we build a custom MCP server instead. It covers authentication, tool definitions shaped from what we learned in discovery, deployment to your account as a container or Lambda, tests, and handover documentation.

EQUIP

Skills -- We take a repeatable task and turn it into a skill your users install in their agent alongside the tools. Each skill is written against your own documentation and published to a repository, public or private, with install instructions.

Output validation -- Left alone, an agent will confidently produce a valid-looking configuration or test plan that contains commands your system doesn't have. We build a catalogue of the commands and formats your systems accept, and a validation step that checks generated output against it before anything is used. That is what keeps invented commands out of production.

PROVE

User test sessions -- Your users exercise the tools from the agent they already use against the live gateway. We record what we find, fix it, and keep the results as the baseline for the next tool set.

Tracing -- We put Amazon CloudWatch and AWS X-Ray across the full request path, from the prompt to the tool call, the API response and the cost, correlated end to end so a wrong answer can be traced back to its cause.

HANDOFF

Production promotion -- Before anything lands in production we add Amazon Bedrock Guardrails, review the authorization on every tool, and document a rollback for each change.

Runbook -- We write the runbook for the team that will operate the gateway, tools and skills after we leave, and it covers the failure modes we saw during testing.

DELIVERABLES

AgentCore Gateway, or a custom MCP server, running in your AWS account and wired to your identity provider.

Tool sets published from your internal API with per-tool authorization scopes, tested by your users.

Skills in a repository with install instructions and a validation step against your system's real command set.

Tracing and guardrails in production, a rollback for every change, and a runbook your team owns.

Everything we build is delivered as infrastructure as code that you own, in your repository or one we set up for you. Scope and pricing depend on how many systems you connect and what you want the agent to do with them, and we agree both with you before any work starts.