SciForce: who we are

Published: January 9, 2018

SciForce is a Ukraine-based IT company specializing in development of software solutions based on science-driven information technologies.

We have wide-ranging expertise in many key AI technologies, including Data Mining, Digital Signal Processing, Natural Language Processing, Machine Learning, Image Processing, and Computer Vision. This focus allows us to offer state-of-the-art solutions in data science-related projects for commerce, banking and finance, healthcare, gaming, media and publishing industry, and education. We offer AI solutions to any organization or industry that deals with massive amounts of data. Our applications help reduce costs, improve customer satisfaction and productivity, and increase revenues.

Our team boasts over 40 versatile specialists in two offices in Kharkiv and Lviv — the regional capitals and the most rapidly developing IT centers of Eastern and Western Ukraine. Our specialists include managers, architects, developers, designers, and QA specialists, as well as data scientists, medical professionals, and linguists.

With such an organizational structure, we have the flexibility to help our customers both launch short-term small or medium projects and build long-term partnerships that would strengthen our partners’ in-house teams and change the vision of an offshore team from mere contractors to an important part of the organization with the corresponding motivation and loyalty.

Aside from the development of software per se, SciForce renders the full range of consulting services in deploying a new project or fine-tuning an ongoing project that needs re-evaluation or restructuring.

The philosophy of SciForce is not only to hire experienced professionals but to foster specialists through mentoring and knowledge sharing. The dedicated SciForce Academy project helps us find young talents, which not only facilitates internal hiring and transfers but also creates a productive atmosphere of mutual respect, trust, and patience.

In our corporate blog, we are going to share our knowledge and insights into frontier information technologies, provide expert opinions from our specialists, and offer you a glance at our daily life.

Stay with us!

RELATED BLOG ARTICLES

View all Articles

How to Build Reliable AgTech AI When Farm Data Is Incomplete

In agriculture, missing data is part of the job. Farm data comes from different sources, under changing field conditions, and at different points in the growing cycle, so a complete and perfectly synchronized dataset is rare. AgTech models still have to work with whatever information is available. Some gaps barely affect the result, while others remove an important part of the signal. Knowing the difference is what makes the model useful outside a clean development dataset. Agricultural data is

# Agriculture

# AI / ML

# Data Science

Building Domain-Specific LLM Systems: When to Use RAG, Fine-Tuning, or Neither

When an Air Canada customer asked the airline’s website chatbot about bereavement fares, it told him he could book first and claim the discount within 90 days. The same answer linked to a policy page saying retroactive requests weren’t allowed. The passenger followed the chatbot’s instructions and later had his refund request rejected. The civil tribunal found the airline liable for negligent misrepresentation after concluding that he’d reasonably relied on the inaccurate guidance. The correct i

# AI / ML

# Data Science

# LLM

Scaling AI Infrastructure: Navigating GPU Orchestration and Cloud Costs

Microsoft spent $37.5 billion on infrastructure in the quarter ending December 2025, with roughly two-thirds going mainly to GPUs and CPUs. At this scale, even modest waste is expensive. NVIDIA found that idle workloads consumed about 5.5% of GPU capacity across its research clusters. By combining GPU telemetry with job data and automatically clearing stalled or abandoned workloads, it reduced that waste to about 1%, potentially saving millions. Scale down the arithmetic and the pattern holds: a

# AI / ML

# DevOps

What Is a Forward Deployed Engineer and How to Become One

Forward deployed engineer was once a niche title used mainly by companies such as Palantir. It now appears across OpenAI, Anthropic, Google Cloud, Scale AI, and other enterprise AI providers. FDE brings software engineering, technical consulting, and project delivery into one role. Its growth also shows what enterprise AI companies now need from engineers: an understanding of customer workflows, the ability to make sound technical decisions, and responsibility for moving a system into production

# Tech

# AI / ML