Robocorp Implementation for Open-Source RPA with AI

We design and deploy artificial intelligence systems: from prototype to production-ready solutions. Our team combines expertise in machine learning, data engineering and MLOps to make AI work not in the lab, but in real business.
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Robocorp Implementation for Open-Source RPA with AI
Medium
from 1 week to 3 months
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Robocorp Implementation for Open-Source RPA with AI

Imagine your procurement department drowning in PDF invoice processing, while developers have been promising an RPA bot on UiPath for a year, but licenses haven't been approved. That's a familiar situation. We replaced UiPath with Robocorp in three retail and logistics companies — the RPA budget dropped 5–10 times, and development speed tripled.

Robocorp is a developer-first RPA platform based on Robot Framework (Python). Unlike UiPath/AA, Robocorp targets developers: code in Git, CI/CD, testing like in regular software development. The open-source core (Robot Framework, RPA Framework) is free, and Robocorp Cloud orchestration costs significantly less than enterprise alternatives.

Why Code-Based RPA Wins Over GUI Alternatives

Versioning and code review. Any robot change becomes a pull request with code review, just like in a regular dev team. Rolling back changes is a single git revert. In UiPath, workflow changes are non-deterministic, and debugging is complex.

Testability. Robot Framework supports BDD syntax, unit tests in Python, and integration with pytest. We achieved 85% code coverage on a typical project — something we haven't seen in GUI RPA.

Integration flexibility. A robot can call transformers.pipeline, run a LangChain Agent, or deploy spaCy for NER — all standard Python imports. No paid activity packages needed.

Criterion Robocorp UiPath/AA
Development language Python GUI + VB.NET/C#
Versioning Git + PR Poorly supported
Testing Robot Framework + pytest Built-in but weak
AI integration Any Python ML library Limited ML activities

How Robocorp Solves Real Business Problems

Problem 1: Maintenance complexity of GUI robots. In one retail chain, UiPath robots broke with every ERP update. Migration to Robocorp: Python code, test coverage, CI/CD — failure rate dropped from 30% to 2%.

Problem 2: Handling unstructured data. Invoices in PDF with different templates. Previously: OCR + manual verification. We trained a model on an invoice dataset and deployed Document AI with a fallback to LayoutLMv3 in the robot. Extraction accuracy: 92% vs. 60% with UiPath Document Understanding.

Problem 3: Scaling without exploding license costs. An additional robot in Robocorp Cloud is 4x cheaper than in UiPath (comparing unattended robots). If peak load requires 50 robots for 2 hours, we simply scale parallel sessions.

How a RAG Pipeline Works in a Procurement Automation Project

For one client (a large logistics company with 1,200 suppliers), we deployed a hybrid RAG pipeline. The Robocorp robot parses incoming invoices from SAP, runs them through Document AI (OCR + LayoutLMv3), then a LangChain agent verifies details via state API and EGRUL. The vector database ChromaDB stores template embeddings, enabling automatic invoice classification 95% of the time. Only 5% of complex cases go to human-in-the-loop. Document processing time dropped from 15 minutes to 40 seconds.

Implementation Process: 2–8 Weeks Turnkey

Stage Duration Result
Analysis 3–7 days Technical process audit, migration/creation plan, E2E pilot scenario tests
Design 1–2 weeks Robot architecture, vector DB selection, RAG model, few-shot prompt design
Development 1–4 weeks Robot code in Python + Robot Framework, unit tests, integration with 1C/SAP/web
Testing 3–5 days QA in staging: edge cases, A/B testing against current procedure
Deployment 1–2 days Robocorp Cloud / self-hosted Control Room setup, CI/CD pipeline (GitLab Actions + Docker)
Training 2–3 days Workshop for developers and operators: writing new robots, troubleshooting, debugging

Each stage includes documentation and access rights transfer. Official Robot Framework documentation serves as the baseline for training.

What's Included in the Work

Robust pipeline: robots meeting NFRs (p99 latency < 30s, throughput up to 500 requests/hour). MLOps infrastructure: model cards for used models, drift monitoring, A/B experiments. Security: Robocorp Vault for secrets, encryption at rest and in transit, role-based access. Warranty: 3 months of free support after deployment, SLA for bug fixes — 24 hours.

We are a team with 5+ years in AI/ML, 30+ RPA and NLP projects. We've contributed to open-source libraries for Robot Framework. License cost savings when switching to Robocorp reach 80%, with an ROI from 6 months.

Get a consultation: we'll assess your process in 2 days, propose a plan and timeline. Order implementation — save time and money without sacrificing quality.