We provide AI technology consulting services for businesses looking to build, validate, or scale their AI systems. With over 10 years of experience in AI as well as cloud infrastructure, software architecture, and distributed computing, we create reliable, efficient solutions that perform in commercial environments.
consult with ai expertsPartnering with us is a strategic investment in speed, certainty, and expertise. We help you avoid
common pitfalls and maximize the return on your AI initiatives.
You believe that AI can automate your processes, enhance a product, or unlock new value, but you’re not sure where to start. You need a partner to help you move from a business idea to a concrete use case, evaluate your AI readiness, and test the concept’s potential.
You’ve identified a potential AI tool but need to ensure it’s the right fit for your business problem. You need an unbiased, in-depth review to de-risk your decision, ensuring the technology you choose is scalable, cost-effective, and perfectly aligned with your long-term goals.
You need a partner with a product mindset to guide the deployment of your working solution – aligning the technical solution with business objectives, planning the integration, and ensuring the final product delivers measurable business value.
Your deployed model struggles with growing user traffic, leading to high latency and rising cloud costs. You need MLOps and cloud engineering expertise to re-architect the system for high performance, reliability, and cost-efficiency.
Your solution is already in operation, but isn’t meeting expectations – model accuracy is low, inference is slow, operational costs are too high, and you need an unbiased review to identify and fix the root cause.
Your team is constrained by the AI tools or platforms you’re using that have poor documentation or hidden limitations. You need an objective review to choose an open, flexible, and scalable tech stack that ensures your independence and future-proofs your AI infrastructure.
We start with the most crucial question: “Will AI help you to reach your goal?” We analyze your business processes to identify the highest-impact opportunities for AI integration.
We provide a detailed technical and business proposal to turn the selected AI opportunity into a clear, scoped project, ready for prototyping or full development.
Based on our Solution Proposal, we build a small, functional version of the proposed solution to validate technical feasibility and demonstrate business value in real conditions.
We provide a 360-degree expert evaluation of your AI system – from code to cloud – and turn insights into clear optimization and cost-saving actions.
We provide an expert assessment of your architecture, code quality to identify potential risks before they become critical problems.
We conduct a rigorous evaluation of your AI models against key performance metrics, including accuracy, fairness, and robustness, as well as identify areas for improvement.
We analyze your spending on cloud infrastructure and AI model APIs and deliver a clear optimization plan to reduce operational costs without sacrificing performance.
We deliver an actionable execution plan: what to fix, how long it takes, and how to measure improvement.
A strategic operations leader, Ivan defines and executes infrastructure vision across cloud, hybrid cloud, and on-premise environments. Focusing on governance, disaster recovery, and security, he builds a resilient and cost-effective operational roadmap, ensuring business continuity.
As a technology native, Aleksandr sets the company's technical vision and strategy. He specializes in designing and implementing scalable, high-performance, and resilient software architectures, translating complex business requirements and challenges into robust technical solutions.
A leading expert in computer vision and geodata analytics, Michael architects AI solutions that interpret satellite and drone data. He solves critical business challenges through predictive modeling, business process automation, and building AI models for large-scale monitoring applications.
A PhD in theoretical physics who architects scalable data pipelines and geospatial systems for the Agritech and GIS sectors, as well as contributes to data-driven products with a strong focus on reliability and scalability for Fintech.
An AI leader and Kaggle Grandmaster specializing in GenAI and LLMs. He leads the end-to-end delivery of AI products while building and scaling cross-functional teams of 15+. With deep expertise in NLP, Computer Vision, and MLOps, he excels in pre-sales, customer engagement, and mentorship.
A tech leader with recent experience in utilizing GenAI (AI assistants, data processing, automation) for FinTech and enterprise clients. His expertise spans from customer engagement to architecture design, with a personal interest in reengineering complex, high-load distributed systems.
Established an AI in-house team in 2015 before the GenAI hype
Deep hands-on with foundation models and prompt optimization
Full-cycle AI delivery
LLM systems integrated with complex workflows and APIs
CI/CD pipelines, model monitoring, and production-readiness
Multiple engagement levels support: from API-based usage to fine-tuning and full model deployment
Experience with both proprietary and open-source models
Deliver classical data science solutions and modern GenAI workflows
Dedicated unit for process standardization and R&D
Internal knowledge base, reusable assets, and process maturity
Applied research in LLM fine-tuning, RAG, and multi-agent orchestration
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
AI readiness means having access to the right data, infrastructure, and technologies. Our AI Readiness Evaluation assesses these areas, including your data integration capabilities and team skills, and provides a strategic roadmap to bridge any gaps so you can fully prepare for AI adoption.
