RPA 2.0 IS HERE

Keep it Coded.
Naturally.

We transform classic RPA and VBA solutions in favor of modern automation in Python – faster, smarter, and
fully yours
.

@ to mention / for commands
The Team

The People Behind codenature

We're three senior RPA developers who've spent the last decade building and running automations for some of the world's largest companies. From oil and automotive to banking, real estate, and aerospace - we've been part of every stage of automation, from early process discovery to full-scale production and maintenance.

10+

Years Each in RPA

3

Founders

5+

Industries Automated

100+

Processes Automated

Full Automation Lifecycle

We've handled every stage of RPA - from process analysis and development to infrastructure setup, run operations, and long-term maintenance.

Enterprise-Scale Expertise

Our background spans consulting for global enterprises - building secure, high-availability automation platforms with real business impact.

Consulting & Strategy

We bridge business and tech - helping companies rethink automation strategies, migrate away from rigid RPA tools, and embrace open, AI-driven solutions.

Developer First

Code simply does more.

Traditional RPA struggles with intelligence. We build Python-native foundations that integrate seamlessly with modern AI, giving you a competitive edge.

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100% Ownership

No black boxes.

Unlike RPA platforms that hide logic behind proprietary files, this is pure Python. You own the IP, the logic, and the git history.

Infinite Ecosystem

Import anything.

Need to parse a PDF? `import pypdf`. Need to call an API? `import requests`. The entire open-source world is your toolkit.

AI Native

LLMs built-in.

Don't just scrape screens. Use LLMs to understand unstructured data, make decisions, and generate human-like responses.

Transformation

Legacy Modernization

Transforming outdated tools into modern code

VBA
PY

Excel/VBA Modernization

We transform outdated macros and spreadsheets into modern, stable automated processes in Python.

Full Automation Processes run on schedule without manual clicks.
Data Stability Eliminating human errors and large file issues.
API Integrations Direct data exchange with ERP/CRM systems.
MDB
SQL

MS Access Transformation

We migrate business logic from Access to a scalable Python backend with a modern web interface, enabling multi-user collaboration.

Data Migration Secure SQL Server / PostgreSQL instead of local files.
Web UI Multi-user access via browser.
Security Centralized access control and backups.
The Stack

We build on Open Standards

No black boxes. Tap the stream to inspect the technology powering your automation.

Google Cloud

Google Cloud

Cloud Infra

Scalable infrastructure for high-performance computing.

AWS

AWS

Cloud Infra

Market-leading cloud services for robust deployments.

Azure

Azure

Cloud Infra

Enterprise-grade serverless functions and security.

Docker

Docker

Containers

Consistent environments from dev to production.

RAG

Knowledge

Retrieval-Augmented Generation for data-aware AI.

MCP

Protocol

Standardized context protocol for AI agents.

AI Agents

Intelligence

Autonomous reasoning engines for complex tasks.

Playwright

Playwright

Browser Engine

Reliable, modern end-to-end browser automation.

Python

Python

Native Logic

Pure, efficient, and owner-controlled codebase.

Google Cloud

Google Cloud

Cloud Infra

Scalable infrastructure for high-performance computing.

AWS

AWS

Cloud Infra

Market-leading cloud services for robust deployments.

Azure

Azure

Cloud Infra

Enterprise-grade serverless functions and security.

Docker

Docker

Containers

Consistent environments from dev to production.

RAG

Knowledge

Retrieval-Augmented Generation for data-aware AI.

MCP

Protocol

Standardized context protocol for AI agents.

AI Agents

Intelligence

Autonomous reasoning engines for complex tasks.

Playwright

Playwright

Browser Engine

Reliable, modern end-to-end browser automation.

Python

Python

Native Logic

Pure, efficient, and owner-controlled codebase.

Pure Code Foundation

Processes created in standard Python – fully readable, auditable, and easy to develop.

Deploy Anywhere

We create deployments running on Azure Functions, AWS Lambda, Docker, or local VMs – without being tied to a specific cloud.

AI & MCP Ready

Native support for Model Context Protocol means your bots don't just click - they understand data and act intelligently.

Trust & Control

Governance & Security at Scale

We don't just write scripts, we build sustainable automation ecosystems. Our solutions are designed with strict governance protocols and data protection standards, ensuring they remain secure and maintainable for years to come.

Security & Data Privacy

We adhere to strict data retention policies and security best practices. Your sensitive data is handled with care, processed securely, and never stored longer than necessary.

Built for Governance

Every solution includes comprehensive logging, error handling, and standardized architecture. This ensures full auditability and makes long-term maintenance straightforward.

Data_Protection_Policy
ACTIVE
Audit_Logging_Module
ENABLED
Code_Maintainability
HIGH
System StatusALL SYSTEMS GO
AI-Accelerated Workflow

Don't code alone.
Code with AI.

Proprietary platforms struggle to keep pace with AI innovation. By switching to Python, your team unlocks the full power of LLMs directly in the IDE-making development faster, cleaner, and smarter.

Copilot is your Pair Programmer

Why drag-and-drop boxes when AI can write the logic for you? Your team can use GitHub Copilot or other AI tools to generate complex automation scripts in seconds, not hours.

Instant AI Debugging

Classic RPA environments make error diagnostics difficult. In Python, you use an IDE integrated with an LLM, which significantly speeds up the debugging process.

Auto-Documentation

Static PDDs become obsolete the moment code changes. Move to 'Docs-as-Code'-where AI reads your logic to keep specifications, flowcharts, and READMEs in perfect sync with reality.

invoice_parser.py
1import pandas as pd
2from openai import OpenAI
3
4# TODO: Extract total amount and vendor from PDF text
5def extract_data(text_content):
6     client = OpenAI()
    prompt = f"Extract vendor and total from: {text_content}"
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}]
    )
    return response.choices[0].message.content
Copilot Suggestion [Tab] to accept
14
main*0 errors
Python 3.11Copilot: Active
The Loop

The Neural Bridge

It's not just about one or the other. It's about the flow. RPA handles the hands-on work - AI handles the thinking.

The Body

Structured Automation

  • Clicks & Types
  • Extracts Data
  • API Requests
Context & Data
Decisions & Actions

The Brain

Adaptive Intelligence

  • Analyzes Intent
  • Classifies Docs
  • Handles Exceptions
Start Cooperation

Ready to Execute?

Let's refactor your automation strategy. No sales fluff, just engineering solutions.

./env_config

CONTACT_EMAIL
office@codenature.io
HQ_LOCATION
Warsaw, Poland
contact_form.py