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Custom AI Solutions
We design and integrate AI systems that work inside real products and business processes. That can mean building a solution from scratch, integrating existing AI tools into your infrastructure, or extending the systems you already have.
Our work ranges from voice automation and intelligent assistants to data analysis and decision-support systems.
Our work ranges from voice automation and intelligent assistants to data analysis and decision-support systems.
Technologies we work with include:
- LLM systems & RAG architectures
- Voice AI and speech processing
- Predictive and analytical models
- Data pipelines and AI infrastructure
Engineering Capabilities
We provide full-cycle software development and dedicated engineering teams for companies building digital products.
We build web and mobile applications, backend systems and cloud infrastructure, and help teams scale existing platforms or modernise legacy systems.
We build web and mobile applications, backend systems and cloud infrastructure, and help teams scale existing platforms or modernise legacy systems.
Our engineering stack includes:
- Backend systems (.NET, Java, Node.js, Go)
- Web development (React, Next.js)
- Mobile applications (Flutter, Android)
- Cloud infrastructure (AWS, Azure, Kubernetes)
Voice sentiment analysis for call quality
2025
Real-estate price forecasting
2025
NDA
Let’s talk about your case
2025
2024
If you’re exploring an idea or trying to understand whether AI makes sense for your product or operations, we’re always open to a conversation.
Not all projects are presented here, most of them are under NDA. Too bad, but that's part of the job.
Robust speech sentiment analysis systems, leveraging audio preprocessing, spectrogram analysis, and custom models to interpret nuanced emotional tones.
Business intelligence platform for smarter growth in real estate, combining location intelligence and AI to enable better decisions.
Product discovery and recommendation system
2024
An advanced recommendation system for product personalisation which leverages data from custom web scraping pipelines and APIs to enrich recommendations.
Examples of what we’ve built
AI VoIP Platform
2025
A scalable, cloud-based voice platform with coverage in 190+ countries and local DIDs in 100+. Proven to lift call-answer rates to as high as 96% in customer deployments.
Smartificial
Smartificial
Smartificial
Smartificial
Give the agent a lead list — it will call, qualify, and hand off leads with next steps. It can also handle inbound calls and stay consistently on-message.
Smart Voice Agents
Legal assistant trained on local legislation
AI assistant that searches through laws and regulations, answers complex questions and simplifies legal research.
Our team
We are a team of experienced engineers building NLP, voice and data systems for years. Our work is shaped by a strong engineering culture and guided by a scientific approach.
- Daniil KrasnoproshinData Scientist & AI/ML EngineerDaniil brings a research-driven approach to AI development, focusing on careful data preparation, structured evaluation and a clear understanding of how models behave in production.
He has extensive experience building NLP and voice systems, RAG-based assistants and full agentic architectures, with a focus on reliability, low latency and cost efficiency in production. - Ilya KislenkaFounder & CTOIlya is the founder and CTO of the company with over a decade of hands-on engineering and leadership experience.
For the past five years, he has led delivery and technology management — from early pre-sale discussions to overseeing engineering teams, technical standards and internal infrastructure. He focuses on structure, clarity and building systems that are reliable in production, not just on paper. - Gregory PapraukaSenior DeveloperGregory leads core engineering across Smartificial projects. With strong experience in Golang, Java, Node.js and AWS, he oversees technical execution, system architecture and code quality across client solutions.
All production systems and integrations are built and reviewed under his supervision. His focus is on performance, infrastructure efficiency and ensuring complex systems remain maintainable as they scale.
From Prototype to Production
Our background spans more than 10 years of full-cycle software development: backend, frontend, mobile, architecture, and distributed systems.
This foundation allows us to take AI ideas all the way to production — integrate them into existing products, build the surrounding infrastructure and ensure they perform reliably at scale.
This foundation allows us to take AI ideas all the way to production — integrate them into existing products, build the surrounding infrastructure and ensure they perform reliably at scale.
We’ve deployed AI into environments with high call volume, dense legal documents, regional market data and operational workflows that can’t afford downtime.
Our team is used to building systems that need to be stable, maintainable and ready for real traffic — not just prototypes.
Our team is used to building systems that need to be stable, maintainable and ready for real traffic — not just prototypes.
Our projects move forward step by step, with clear decisions and no surprises.
We approach every project as an engineering task: understanding constraints, decomposing the problem and building AI systems that can be deployed, supported and scaled in production.
How we work
01 —
Initial Call
Initial Call
05 —
Deployment & Support
Deployment & Support
We map the problem, understand the goal and check technical feasibility. If the task is clear, we prepare a proposal within a few days.
Once the system is live, we monitor performance, adjust where needed and support the team. When your product evolve, we help the AI evolve with it.
02 —
Pre-Cycle (for complex projects)
Pre-Cycle (for complex projects)
We run a series of calls with a business analyst. The goal is to fully decompose the product: features, data, workflows, constraints and the role AI needs to play. The analyst then translates everything into a detailed brief for the AI and engineering team.
04 —
Development & Integration
Development & Integration
We build the solution end-to-end. The development team integrates the system into the client’s product with minimal disruption.
03 —
Proposal & Planning
Proposal & Planning
We outline the approach, timeline and team setup. If the client is aligned, we move straight into execution.
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