Profil Software

Advanced

Custom Software Development Company

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Overview

employees

2008

founded

Gdynia

Poland

We are a first-class custom software development company. We provide dedicated agile teams that deliver complex custom applications. We transform development experience into product confidence.

Profil Software (Python Software House) leverage high-level technical experience and proven development processes to ensure successful outcomes and confidence in product development. In more details that is taking idea to code to actual product in customer's hand. Our Python Development Company hires 70+ inhouse developers, has 10+ years of experience. Company provides premium software solutions for SMB and startups across 10+ countries on 4 continents. We build innovative and high-value products and specialize in creating products with the highest return on investment versus risk.

Contact details

Business info

Publicly traded: No
Majority shareholders: Management & Employees

Locations

Profil Software, Poland

Headquarters

Founded2008

Employees75

Sportowa 8b, 81-300 Gdynia, Poland

Service lines

Web Development40%

Custom Software Development40%

Industries

Freight Transport & Logistics20%

Real Estate20%

Healthcare20%

Financial Services20%

Energy & Utilities20%

Technologies

Amazon Web Services (AWS)AngularDjangoDockerFigmaFlaskJavaScriptMongoDBOpenCVPostgreSQLPythonReact NativeReact.jsVue.js

Case studies

View all1 / 4

Tarot Analytics - Route Planning and Optimization Software

Discover the game-changing solution for last-mile Enterprise vehicle fleets: Tarot Routing. Harnessing cutting-edge algorithms, Tarot Routing revolutionizes route optimization, ensuring streamlined driving routes with unprecedented efficiency. Experience a remarkable 30% reduction in driving time, accompanied by substantial decreases in CO₂ emissions, fuel consumption, driver salaries, and more.

Soop - Energy Management Software

Introducing our advanced system for solar power plant optimization. Our platform monitors each panel, swiftly identifying issues like scaling or shading. By maximizing energy output and minimizing disruptions, we ensure peak performance. Experience the future of solar management today.

JOG.AI - Speech Recognition Software

Introducing Jog.ai, your trusted companion for managing conference and phone calls effortlessly. Our platform provides recordings and accurate transcriptions, freeing you from the need to take notes during calls. With Jog.ai, you can focus on meaningful conversations without distractions, ensuring that every detail is captured and easily accessible whenever you need it.

Indicative rates

Rates not shared by provider.

Certifications⁰

Profil Software has declared they do not currently hold any ISO certifications.

Leadership

Filip Kowalski

CEO

Michał Skałkowski

COO

Insights

RAG vs GraphRAG: Choosing Retrieval Architectures

Choosing the right retrieval architecture directly impacts the accuracy and explainability of GenAI applications. The article compares standard Retrieval-Augmented Generation (RAG) with GraphRAG, highlighting how vector-based retrieval handles unstructured similarity, while graph-based approaches capture relationships, context, and multi-hop reasoning. It explains architectural trade-offs in data modeling, query complexity, and scalability. Technology leaders should align retrieval design with use case complexity, especially where context, traceability, and reasoning depth are critical.

From Static RAG to Agentic AI Workflows

Organizations are moving beyond static retrieval-based AI systems toward agentic workflows that can plan, execute, validate, and refine complex tasks autonomously. This article explains why traditional RAG architectures struggle with multi-step reasoning, uncertainty handling, and adaptive decision-making in dynamic environments. It outlines how agentic systems combine AI agents, LLMs, APIs, and human oversight to support more resilient automation across operations, finance, and enterprise workflows. For technology leaders, the key challenge is no longer whether to adopt AI workflows, but how to select architectures that balance autonomy, reliability, governance, and scalability.

AI-Assisted Development Needs Architectural Discipline

As AI-generated code accelerates software delivery, engineering leaders face a growing trade-off between speed and long-term maintainability. This discussion highlights how increased AI adoption can reduce refactoring, increase code duplication, and weaken delivery stability when teams rely on agents without architectural controls. It outlines practical governance patterns including AI-ready repositories, structured planning workflows, context engineering, reference-based prompting, and mandatory self-review practices. The core message is that AI works best when developers define system boundaries, interfaces, and conventions before generation begins. For CTOs and engineering leaders, the challenge is no longer code generation itself, but preserving engineering quality and maintainability

Events

No events data available.

Transparency Wins Ecosystem Context

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