Engineering studio

AI engineering studio for agents, data pipelines, and production full‑stack builds.

Axentrea builds systems where reliability matters: scraping & ETL, LLM/agent workflows, and full-stack products with the observability and delivery discipline to keep them running.

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live pipeline

running

axentrea/pipeline

00:00.0▸ingest.vendor_portals()

00:02.1▸extract.listings → normalize.uom()

00:05.4▸validate.schema() → upsert.postgres()

00:07.9▸export.xlsx → deliver.onedrive()

00:09.2▸agent.notify() (slack/email)

Technical work is only valuable if it survives real traffic, retries, and edge cases.

Positioning

Three pillars. No filler.

Axentrea is an engineering partner for teams that need senior execution across AI, extraction, and full-stack delivery.

AI agents & LLM applications

Ship AI systems that are reliable in production: tool use, RAG, evals, guardrails, and human-in-the-loop workflows.

Pillar

Agent workflows (tools, memory, scheduling, retries)
RAG + search + structured outputs with fallbacks
Model routing, prompt engineering, evaluation harnesses
Automation glue (n8n, queues, cron, webhooks)

Data extraction & pipelines

Turn messy sources into dependable datasets: scraping, normalization, dedupe, storage, and exports your ops can trust.

Pillar

Scraping at scale (Playwright/Selenium, anti-bot aware)
ETL/ELT pipelines, validation, and idempotent upserts
Postgres/MySQL storage + S3/CSV/Sheets exports
Observability: logs, metrics, failure triage

Full-stack product builds

Build the UI, API, database, and infrastructure—so the thing actually runs, ships, and stays maintained after launch.

Pillar

Next.js apps, dashboards, internal tools, SaaS MVPs
APIs, workers, queues, and background processing
Auth, permissions, audit logs, and admin UX
Deployment, CI/CD, monitoring, and hardening

Who we serve

Teams that value engineering rigor

If you need senior technical ownership—architecture, execution, and delivery—we're a fit.

Founder-led teams that need senior engineering execution
Ops-heavy businesses drowning in manual workflows and unreliable data
Product teams that need a technical partner to scope, ship, and own delivery

How We Build

We turn scattered work into a system that runs itself

Most projects reach us as manual hours, disconnected tools and data nobody trusts. This is the stack we put in its place.

Case studies

A few builds we can walk you through

Problem, architecture, stack, and outcomes—no vague screenshots with no context.

OCH Manager: automated inventory extraction + normalization + ops workflow

A full-stack automation system that extracts inventory from multiple vendor portals, normalizes units and product data, schedules repeatable runs with worker capacity, and delivers ops-ready exports with visibility into jobs and failures.

PythonDjangoPostgreSQLPlaywright

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