Kalebtec
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Kalebtec

Kalebtec AI Agent Infrastructure

juny del 2026

IA i Machine LearningEines per a DesenvolupadorsSaaSTypeScriptModel Context ProtocolPlaywrightCDPZodClaude CodeAstroOAuth 2.1 PKCEPWA
Kalebtec AI agent infrastructure — browxai, docsxai, remotxai, and wrightxai product suite

Kalebtec is building an applied AI infrastructure stack for software teams: browxai for browser control, docsxai for documentation automation, remotxai for long-running agent supervision, and wrightxai for agentic web-workflow execution. The work sharpens Kalebtec's client delivery by dogfooding the same agent infrastructure used to inspect, build, and verify production software.

Cas d'estudi

4
Agent-infrastructure products
1
Browser-control server
0
Model lock-in by design

Repte

Most AI adoption work fails when it stops at prompts. Teams need reliable browser control, repeatable documentation generation, remote supervision, and verification loops before AI agents can safely help with real delivery work.

Enfocament tècnic

Kalebtec built small, composable infrastructure products around real agent workflows, then dogfooded them against client-style tasks: inspect the web, drive applications, generate documentation, supervise long-running coding sessions, and verify results.

Decisions d'IA i infraestructura

The stack favors model-agnostic protocols, typed tool contracts, deterministic replay where possible, and browser-level evidence over vague agent summaries. That makes the tools useful for delivery teams that need auditability and repeatable outcomes.

Resultats

The infrastructure now supports Kalebtec's positioning around applied AI product engineering: not AI theater, but concrete tooling that helps teams decide what to build, build it faster, and verify it before release.

Impacte en el negoci

Client engagements can start from proven workflows for browser automation, documentation, agent supervision, and live-site verification instead of bespoke AI experiments.

Overview

Kalebtec's AI infrastructure work is part product lab, part delivery accelerator. The stack is built to make agents more useful in actual software projects, where browsing, verification, documentation, supervision, and repeatability matter as much as generation.

Infrastructure Components

browxai

An MCP-native, model-agnostic browser-control server that exposes Playwright/CDP capabilities through typed tool contracts for AI agents.

docsxai

A documentation automation engine and Claude Code plugin that walks web applications, follows user flows, and emits screenshot-rich documentation with deterministic replay after calibration.

remotxai and wrightxai

Remote supervision and agentic web-workflow tooling for long-running coding sessions, browser-driven execution, and screenshot-backed verification.

Why It Matters for Clients

  • AI workflow readiness can be assessed against real product surfaces
  • Documentation can be regenerated from browser flows instead of stale hand-written notes
  • Agent output can be verified with live browser evidence
  • The delivery team has hands-on infrastructure experience, not only advisory opinions