RevoTech PRO

RevoTech PRO is a Polish software development company that builds backends, frontends, and AI systems for 100+ clients across fintech, healthcare, manufacturing, and marketplace sectors. The company works in full-cycle development—architecture, backend, data science, frontend, QA—and engages primarily through fixed-term projects staffed with dedicated teams rather than single augmented developers. Their projects typically run 8–18 months with team sizes of 5–12 people, including project managers, system analysts, QA engineers, and specialists like data scientists or DevOps engineers. The source does not disclose a founding year, headquarters location details beyond "Poland," or total headcount, but project documentation shows they scale from small AI efforts to large financial infrastructure builds.

Services and capabilities

RevoTech PRO's primary service is custom software development. Their published work falls into distinct tracks:

FinTech & Banking. They have shipped multiple live banking platforms: a B2B2C mobile banking app using PWA, Spring, Kafka, Kubernetes, and Flutter (12 months, 12-person team); electronic document management for a bank with CRM integration, digital signature via CryptoPro, and antivirus scanning (18 months, 12-person team); an EDI system handling EDIFACT, ANSI X12, XML, and JSON with Camunda orchestration (11 months, 9-person team); and a bank payment system with subscription management, invoice automation, and multi-channel settlement (18 months, 13-person team). They also built a personal/family financial assistant for Android and iOS with AI-driven spend categorization, partner offers, and fraud detection (8 months, 11-person team), which reached 100,000 installs in the first 11 months.

AI & Data Systems. For an emerging tech startup, they delivered a Python/React/FastAPI workflow assistant that aggregates data from experiment tracking, pipeline logs, and cloud metrics, surfaces it via Slack, and includes predictive analytics—all GDPR-compliant. For a U.S. digital health startup, they built the core ML pipeline for radiology interpretation: TensorFlow models on Kubernetes, MLflow for experiment tracking and deployment, a DataOps framework for DICOM ingestion and validation, and continuous monitoring for data/concept drift. For a B2B SaaS market research platform, they developed an MVP with Elasticsearch for indexing, Kafka for streaming, Snowflake for analytics, and React dashboards with dynamic visualization and ML-driven recommendations.

Enterprise & Manufacturing. They implemented an MES (Manufacturing Execution System) for coke production: a PyTorch/XGBoost/CatBoost charge optimization engine that predicts coke quality without replacing human technologists, paired with a data science training platform (8 months, 6-person team). For a multi-branch manufacturing group, they deployed electronic document management across legal entities with centralized storage, format transformation, and document routing (14 months, 12-person team). They also modernized laboratory instrument control, replacing legacy PC-dependent panels with cross-platform Android tablets that connect via WiFi and manage experimental workflows in real time (10 months, 5-person team).

Across all projects, the company uses a mature tech stack: Java, Spring, Spring Boot, Kafka, RabbitMQ, PostgreSQL, MongoDB, Redis, Docker, Kubernetes, OpenShift, and Camunda for workflow orchestration; Python, React, Redux, TypeScript for frontend; TensorFlow, PyTorch, XGBoost, Scikit-learn for ML; and cloud platforms like Google Cloud Platform and monitoring tools like Prometheus, ELK, MLflow.

Notable work

Three fintech projects illustrate their depth. A 12-month digital banking system used PWA technology, Spring microservices, and Kafka to handle real-time payments, virtual card issuance, SWIFT/SEPA transfers, and horizontal scaling as clients grew. An 18-month bank document system unified approval workflows, cutting signing time and removing manual overhead through CRM integration and Kaspersky virus scanning. An 11-month EDI core rewrote legacy organization configuration and document processing in Camunda, reducing user connection time by five times and lowering operational costs.

On the AI side, a market research MVP moved from zero to market in a single MVP cycle, allowing the client to launch monetization quickly and build a subscription model; the recommendation engine continuously scored companies based on user feedback. A radiology processing platform integrated DICOM ingestion, distributed model training, MLflow versioning, and Kubernetes inference, addressing regulatory compliance and data quality in medical imaging. A workflow assistant for developers aggregated experiment tracking and calendar data, delivered insights via Slack, and was designed for future SaaS monetization.

How they work

RevoTech PRO staffs projects with fixed teams—typically 5–13 people—rather than offering individual contractors. A standard project includes a project manager, 3–7 developers, 1–2 system analysts, 1–2 QA engineers, and sometimes a DevOps engineer or data scientist. Engagements run 8–18 months. Pricing and contract terms are not disclosed in the source. They claim "clear & transparent communication" and mention keeping clients "informed at every stage," but no concrete detail on communication cadence (weekly syncs, demos, etc.) appears in the material. The company emphasizes alignment with client vision and integrity in the sales process.

Team and credentials

No founders, CEO, or CTO are named in the source. Team size is not stated. The company claims to have delivered "over 100 successfully delivered projects," but no certifications (ISO 27001, SOC 2, GDPR compliance attestation, HIPAA) are mentioned. No partner badges (AWS, Google Cloud, Microsoft, Shopify) are listed, though they use these platforms. No Clutch, G2, or other third-party ratings are cited. English proficiency is assumed (all case studies and service descriptions are in fluent English), and Arabic localization is mentioned for the financial assistant app.