FAQ
What types of projects do you work on?
We focus on technically complex systems: AI platforms, real-time analytical infrastructure, scientific forecasting systems, hardware-connected software, industrial automation, spatial computing, and custom enterprise platforms.
Most of our projects combine multiple domains at once — data engineering, AI, backend architecture, hardware communication, visualization, and distributed infrastructure.
Do you only work with AI projects?
AI is a major part of our expertise, but most of our systems combine AI with broader engineering infrastructure.
We build platforms where machine learning operates together with:
- real-time backend systems
- telemetry infrastructure
- scientific computing
- hardware communication
- distributed data pipelines
- operational automation
- analytical and decision-support systems
In many cases, AI is one component inside a larger production architecture rather than the entire product.
Can you integrate AI into an existing product?
Yes.
We integrate:
- LLMs
- RAG pipelines
- semantic search
- embeddings
- forecasting models
- AI-assisted workflows
- automated validation systems
- conversational interfaces
We work with both cloud APIs and self-hosted models depending on security, privacy, and infrastructure requirements.
Do you work with hardware and embedded systems?
Yes.
We have experience integrating software with:
- LiDAR
- IMU sensors
- laser systems
- telemetry modules
- serial devices
- embedded controllers
- industrial communication interfaces
This includes real-time synchronization, protocol design, device communication layers, and operational monitoring systems.
What technologies do you use?
Our core stack includes:
- Python / FastAPI
- React / Next.js / TypeScript
- Swift / SwiftUI
- PostgreSQL / ClickHouse / Redis
- Qdrant / Neo4j
- Docker / CI/CD infrastructure
- LangChain / RAG architectures
- scientific computing libraries (NumPy, SciPy, xarray, Cartopy)
But we do not force technologies into projects.
The architecture is always chosen based on the problem itself.
Do you build production systems or prototypes?
Production systems.
Most of our work is designed for:
- continuous operation
- unstable real-world conditions
- large-scale data processing
- asynchronous workflows
- telemetry interruptions
- hardware synchronization
- long-running infrastructure
We build systems expected to operate continuously, not isolated demonstrations.
Can you work with scientific or research-heavy domains?
Yes.
A significant part of our experience involves:
- environmental simulations
- oceanographic forecasting
- mathematical modeling
- probabilistic systems
- geospatial visualization
- sensor-based infrastructure
- scientific data processing
We are comfortable working in domains that require deep technical immersion and non-standard engineering approaches.
How is the development process organized?
We usually work iteratively.
The project is divided into stages with working intermediate results:
- architecture and research
- MVP
- infrastructure setup
- core functionality
- validation and optimization
- deployment and monitoring
This allows clients to see progress early and adjust priorities based on real usage instead of assumptions.
Do you provide support after launch?
Yes.
We support and evolve systems after deployment:
- monitoring
- infrastructure maintenance
- scaling
- performance optimization
- feature expansion
- operational stability improvements
Most of our systems run with automated deployment and monitoring infrastructure.
Can you work with confidential or internal infrastructure?
Yes.
We can work with:
- private servers
- isolated infrastructure
- self-hosted AI models
- VPN-restricted systems
- internal APIs
- enterprise environments
For some projects, all AI processing can remain entirely inside the client’s infrastructure.
What industries do you work with?
Our projects span multiple industries, including:
- AI and analytics
- industrial systems
- scientific research
- agriculture
- aerospace and UAV systems
- interior and spatial visualization
- finance and trading
- enterprise ERP ecosystems
We are particularly interested in domains where software interacts with complex real-world environments.
Do you work internationally?
Yes.
We work remotely and collaborate with clients internationally. Communication is available in English and Russian.
What is the minimum project size?
There is no fixed minimum.
We usually participate in projects where:
- architecture matters
- technical complexity is high
- scalability is important
- standard solutions are insufficient
The best way to start is a technical discussion about the problem itself.
Can you help with architecture and technical strategy before development starts?
Yes.
In many cases we begin with:
- architecture planning
- infrastructure strategy
- AI feasibility analysis
- technology selection
- risk assessment
- data flow design
- hardware/software interaction planning
This stage often helps clients avoid expensive engineering mistakes later.
What makes AIST different from a typical software agency?
We are not focused on producing generic websites or standard SaaS clones.
Most of our work exists at the intersection of:
- software engineering
- AI systems
- infrastructure
- scientific computing
- hardware integration
- operational reliability
We are most useful in projects where the technical uncertainty is high and off-the-shelf solutions are not enough.