AI, automation and AWS to help your business run better, securely and with costs under control

It depends on the size and complexity of your environment. The assessment (1–2 weeks) produces a wave plan with an estimated timeline for each step.

The plan aims for minimal impact: a pilot migration, agreed windows and a rollback plan for each step.

We provide an estimate based on your actual usage, built with the AWS Pricing Calculator, and set up budgets and alerts.

Yes. We choose the right strategy for each case (for example AWS DMS or backup and restore) and validate the data at the end.

No. The assessment uses a read-only IAM role that you create and can remove at any time.

We don’t promise a percentage before analyzing your account. The report shows each opportunity, its mechanism and an estimate calculated from your own data.

Every recommendation comes with its risk. Production changes are only made with your approval and a rollback plan.

The practice of continuously tracking and optimizing cloud spend, bringing together engineering, finance and business: visibility (tags, reports), optimization and governance (budgets, alerts, monthly reviews).

With the process that takes the most team time and follows clear rules. The assessment helps pick that first use case.

We propose architectures inside your AWS account, with encryption, least privilege and logs. On Amazon Bedrock, your inputs are not used to train the models.

Automation follows fixed rules (if X, do Y). An AI agent interprets text and requests and chooses the next step within defined limits. Many solutions combine both.

It depends on usage volume and the chosen model. We estimate monthly cost before building and set spending alerts.

None as a one-size-fits-all recipe. In the assessment we look at the process, the data and the risk; we use market tools we already know in practice (Claude/Claude Code, GPT/Codex, Grok Bot, Gemini, Perplexity, n8n, Devin, Kiro and Manus, and, where it fits, Amazon Bedrock inside your AWS account) and recommend the combination that best matches the case — sometimes the best answer is automation with no generative model.

It depends on the team, the repository and the type of task. Claude Code and Codex (OpenAI) are strong options for coding agents; in the assessment we compare quality, cost, data limits and how each fits your workflow (including Grok Bot in Cursor, Devin, or Kiro on AWS when the scenario calls for it). The choice is documented in the MVP plan.

Both, when it makes sense. n8n shines at fast automations and integrations between systems; on AWS we use Lambda, Step Functions and EventBridge when the flow needs scale, infrastructure as code and governance. The assessment tells which path (or both) fits your process.

With the AI & Automation assessment form and an intro call, followed by the paid assessment (1–2 weeks), the MVP and, if it makes sense, monthly evolution.

The minimum required. For the assessment, read-only access (a read-only IAM role on AWS). Write access only during implementation, with defined scope and duration, and removed at the end.

We process only the data needed for the service, under an NDA and data-protection clauses in the contract. See our Privacy Policy.

Yes. We work remotely with international clients in English; contracts and billing [in USD — terms to be defined by Sergio].

Brasília time (UTC-3). Meeting hours for North American and European clients: [to be confirmed by Sergio].

Companies across many industries. We work with companies from many sectors. Due to prior contractual commitments, some segments are not served at this time.