For product and technical leaders

Bring AI agents into engineering workflows without weeks of setup.

Navegante helps technical teams run tools like OpenClaw and Hermes inside real engineering workflows, so agents can support project work in the cloud without your team spending weeks on configuration and security hardening.

Book an free agentic engineering audit Read the agentic engineering checklist
bring your own

API keys or AI subscription

free deployments

during the pilot

1 week

setup window

Common problems with agentic engineering workflows

Agentic engineering starts as a workflow experiment, then becomes infrastructure work.

AI agents need more than coding tools before they can participate in real engineering workflows. Teams need isolated execution, scoped access, deployment paths, and review visibility before a pilot can safely move beyond local experiments.

Problem 1

Agents need isolated machines, scoped credentials, and logs.

Problem 2

Local laptop workflows do not scale to a team of human and AI contributors.

Problem 3

Production access boundaries are unclear before the first real pilot.

Problem 4

Internal platform work delays agentic engineering adoption.

What we offer

A focused, hands-on sprint to help you eliminate pain points from your deployment workflows.

Step 1

We take a look at how your team wants to use AI agents and where infrastructure boundaries matter first.

Step 2

You pick which repo, product team, or agent-assisted workflow you want to pilot.

Step 3

We'll work closely with you to set up agent servers, scoped access, deployment paths, and review guardrails.

Step 4

We document the repeatable workflow so your technical leaders and developers can expand it after the pilot.

Best for
  • Founders, CTOs, and C-suite leaders with an existing engineering team.
  • Teams that want agentic workflows but do not want a platform buildout first.
  • Companies moving beyond experiments in ChatGPT, Codex, Cursor, Claude Code, or OpenCode.
  • Product teams that need production discipline around AI-assisted changes.
What's included
  • Custom features built for your team's internal agentic engineering workflows.
  • Managed agent servers for scoped engineering work.
  • GitHub-connected app deployments and branch previews.
  • Credential, service, database, and log workflows in one operating layer.
  • A documented pilot model your team can expand after the first use case.

Skip weeks of configuration and get cloud AI agents working in real engineering workflows.

Let your technical staff focus on product work while we set up the isolated execution environments, deployment paths, and review guardrails to safely bring AI agents into your engineering workflows.

Book an free agentic engineering audit