We build AI assistants
BUSINESS
TECHNOLOGY
INTERNATIONAL EXPERIENCE
We combine R&D in LLM and ML with deep understanding of business needs across geographies. This lets us build comprehensive AI solutions applicable around the globe.
Our offering
AI
AI Assistants
Different types of multi‑agent systems that replace dashboards, assist analysts, ensure compliance, and converse with customers.
AI assistants learn business context, connect to internal and external data sources, surface key insights, answer questions, and prepare documents — to support decision‑making.
AI assistants learn business context, connect to internal and external data sources, surface key insights, answer questions, and prepare documents — to support decision‑making.
AI Employees
AI agents that augment or replace real employees.
AI employees are trained on the data of specific organizations to perform company-specific tasks, learn the context and the specifics of the role, and execute work autonomously — just like regular employees.
AI employees are trained on the data of specific organizations to perform company-specific tasks, learn the context and the specifics of the role, and execute work autonomously — just like regular employees.
ML Optimization Tools
Optimization
Tools
ML
Models that maximize business performance.
We build optimization and forecasting models: from CDT for assortment management and recommendation models for cross‑sell to productivity management models for agricultural production — and beyond.
We build optimization and forecasting models: from CDT for assortment management and recommendation models for cross‑sell to productivity management models for agricultural production — and beyond.
What we’re working on right now:
Insurance Agent Assistant
/
Attorney Assistant
/
Agronomist Assistant
/
Procurement Assistant
/
AI data cleaner
/
AI claims manager
/
ML Models for Retail
/
CVM Models
/
Store Director Assistant
/
Consumer Assistant
/
/ What we’re working on right now:
Insurance Agent Assistant
/
Attorney Assistant
/
Agronomist Assistant
/
Procurement Assistant
/
AI data cleaner
/
AI claims manager
/
ML Models for Retail
/
CVM Models
/
Store Director Assistant
/
Consumer Assistant
/
Title
/
Description
Status:
Comparative Multi-Agent System
For tasks requiring documentation and regulatory analysis — compliance and conformity checks.
Sales & Communication Multi-Agent System
For solutions focused on managing sales communications.
Analytical Multi-Agent System
For tasks requiring numerical‑data analysis and recommendation generation.
LLM CORE
LLM Core — the software development kit and architectural principles behind Agentic Lab’s multi‑agent systems.
Comparative Multi-Agent System
For tasks requiring documentation and regulatory analysis — compliance and conformity checks.
Sales & Communication Multi-Agent System
For solutions focused on managing sales communications.
Analytical Multi-Agent System
For tasks requiring numerical‑data analysis and recommendation generation.
Comparative
Multi-Agent System
Multi-Agent System
Sales & Communication Multi-Agent System
Analytical
Multi-Agent System
Multi-Agent System
Examples of implemented solutions /
Attorney Assistant
An intelligent workspace for attorneys. It structures cases, performs legal research and case‑law retrieval, cross‑checks materials, runs comparative analysis against the regulatory base, and tracks deadlines.
Procurement Assistant
A platform for tender documentation and bid analysis that also determines optimal purchase volumes and deduplicates positions. Frees time for large and strategic sourcing.
AI data cleaner
An AI employee that standardizes and cleans data, identifying outliers and errors. Used in underwriting, scoring, pricing, and other tasks where data quality is critical.
AI claims manager
An AI agent that receives and processes insurance claims, checks them against policies and payout limits, and autonomously decides on compensation. Humans get involved only in disputed cases.
Consumer Assistant
An AI assistant embedded in an online store’s search box. It builds personalized product baskets from a single query, reduces time‑to‑purchase by ~4×, and lets retailers manage basket structure. Increases margin, loyalty, and purchase frequency.
Insurance Agent Assistant
A multi‑agent system to manage customer portfolios and sales. It analyzes conversion and loss ratios, tracks renewals, determines the next best offer, and sends alerts and guidance in chat. Scales to any sales‑management processes.
Agronomist Assistant
A system to improve yield and production efficiency. Works with aggregated data (yields, climate, resources) and granular control metrics and inputs — from CO₂ levels to spectral imaging.
Store Director Assistant
A multi‑agent system for managing a retail location. Helps the store director control sales, stock, promos, and operations, providing real‑time analytical hints and prioritized actions.
LLM CORE
Analytical MAS
For tasks requiring numerical‑data analysis and recommendation generation.
Examples of implemented solutions:
Store Director Assistant
A multi‑agent system for managing a retail location. Helps the store director control sales, stock, promos, and operations, providing real‑time analytical hints and prioritized actions.
Agronomist Assistant
A system to improve yield and production efficiency. Works with aggregated data (yields, climate, resources) and granular control metrics and inputs — from CO₂ levels to spectral imaging.
Insurance Agent Assistant
A multi‑agent system to manage customer portfolios and sales. It analyzes conversion and loss ratios, tracks renewals, determines the next best offer, and sends alerts and guidance in chat. Scales to any sales‑management processes.
Comparative MAS
For tasks requiring documentation and regulatory analysis — compliance and conformity checks.
Examples of implemented solutions:
AI claims manager
An AI agent that receives and processes insurance claims, checks them against policies and payout limits, and autonomously decides on compensation. Humans get involved only in disputed cases.
AI data cleaner
An AI employee that standardizes and cleans data, identifying outliers and errors. Used in underwriting, scoring, pricing, and other tasks where data quality is critical.
Procurement Assistant
A platform for tender documentation and bid analysis that also determines optimal purchase volumes and deduplicates positions. Frees time for large and strategic sourcing.
Attorney Assistant
An intelligent workspace for attorneys. It structures cases, performs legal research and case‑law retrieval, cross‑checks materials, runs comparative analysis against the regulatory base, and tracks deadlines.
Sales & Communication MAS
For solutions focused on managing sales communications.
Examples of implemented solutions:
Consumer Assistant
An AI assistant embedded in an online store’s search box. It builds personalized product baskets from a single query, reduces time‑to‑purchase by ~4×, and lets retailers manage basket structure. Increases margin, loyalty, and purchase frequency.
Founders/
Miroslav Gridin / CEO
Experience: McKinsey, Yakov & Partners, AI ventures (GCC)
Geographies: CIS, GCC, Europe, USA, SEA
Geographies: CIS, GCC, Europe, USA, SEA
Focus — developing the product portfolio and ensuring business impact.
Vladimir Makarov / CTO
Experience: McKinsey, Huawei, Innopolis. PhD
Geographies: GCC, CIS, Europe
Geographies: GCC, CIS, Europe
Focus — ensuring technological leadership and product scalability.
Team & Join Us
Product & Engineering Team /
A lean team of top LLM engineers and data scientists, product owners, product managers and analysts, backend and frontend engineers, designers, and architects. Dual focus on R&D and client delivery. Knowledge from across the world.
Business Development Team /
Affiliated partners — industry experts and market leaders. They complement Agentic Lab’s technological and business capabilities and ensure our solutions are practical across industries.
VACANCIES
Product owner
What you’ll do:
- Be the CEO of your product — owning its strategy, outcomes, and growth.
- Shape the product vision and align it with shareholders, partners, and key clients.
- Manage the full product lifecycle: from idea and hypotheses to launch and scale.
- Build and coordinate a cross-functional team (engineering, UX/UI, analytics, marketing, sales).
- Define, track, and improve key product and financial metrics.
- Set up data and analytics workflows to drive decisions.
- Test hypotheses, launch MVPs, and manage the product roadmap.
- Communicate with clients and partners, representing the product as a business unit.
- Ensure delivery of goals on time, quality, and commercial performance.
We expect you to:
- Have experience as a Product Owner / Product Manager in IT, or as an Associate+ at a top consulting firm (McKinsey, BCG, Strategy&, etc.).
- Be a product leader comfortable in analytics, strategy, and technology.
- Be passionate about building products that change how companies make decisions.
- Understand corporate clients and B2B solution implementation processes.
- Be confident managing the product cycle — from discovery to release.
- Understand LLM systems, multi-agent pipelines, and API integrations.
- Build effective communication between clients and technical teams.
- Be proactive, structured, and accountable for results.
- Be fluent in English and Russian.
Would be a plus:
Experience with Agentic AI, LangGraph / LangChain, international consulting, or UX research skills.
Analyst
What you’ll do:
- Join the team building enterprise-grade multi-agent AI solutions — from first hypotheses to real-world implementation.
- Research the market and competitors, shaping product strategy and growth opportunities.
- Conduct customer development — interviews, focus groups, testing, and field studies.
- Analyze data and translate it into insights and development priorities.
- Work closely with engineers and the R&D team, bridging client needs, product logic, and technology.
- Support product rollout and customization for enterprise clients.
- Contribute to pitch decks, presentations, and analytical materials.
- Depending on seniority, lead other analysts and structure research tasks.
We expect you to:
- Be a business- and product-minded analyst.
- Be excited to see how data turns into meaningful AI products used by real companies.
- Have experience with B2B / enterprise tech products and understand corporate clients.
- Be skilled in qualitative and quantitative research, turning results into product insights.
- Use analytics tools (SQL, Python — nice to have) and be confident with PowerPoint and Excel.
- Manage priorities, structure work, and deliver results.
- Communicate easily with both engineers and business stakeholders.
- Be fluent in Russian and English.
Would be a plus:
Experience in consulting (McKinsey, BCG, Strategy&, etc.), AI or product startups, and familiarity with Agentic AI or LLM applications.
Backend Engineer
What you’ll do:
- Build the technological core for our AI platform and a stable backend infrastructure — with no legacy code and full influence on technical decisions.
- Work with a modern tech stack, clean code, and high engineering standards.
- Develop and scale asynchronous backend services in Python (FastAPI / Django).
- Design and integrate RESTful APIs with frontend and external systems.
- Work with PostgreSQL / MySQL, optimizing queries and database structure.
- Configure Docker environments and CI/CD pipelines.
- Implement caching, queues, and background tasks (Redis, Celery, Kafka).
- Set up monitoring and logging with Prometheus / ELK.
- Collaborate closely with product, frontend, and DevOps teams.
- (Optionally) mentor others, perform code reviews, and take technical leadership.
We expect you to:
- Be an engineer who values clean architecture and rational solutions.
- Enjoy a startup spirit — where you build the foundation of the future product.
- Have 3+ years of Python experience and knowledge of modern backend frameworks.
- Be confident designing microservice architectures and understanding async processes.
- Be skilled with containerization and deployment tools (Docker, Nginx, Gunicorn).
- Have experience with CI/CD setup and Linux environments.
- Be proficient in PostgreSQL / MySQL, optimizing queries and data schemas.
- Communicate clearly, take responsibility, and work well in a team.
- Bonus: experience with web scraping, startups, or AI/big data projects.
Tech stack:
- Backend: Python, FastAPI, Django, Django Rest Framework (DRF)
- Databases: PostgreSQL, MySQL
- DevOps: Docker, Nginx, Gunicorn, CI/CD (YAML)
- Queues: Redis, Celery, Kafka
- Monitoring: Prometheus, ELK
Data Scientist
What you’ll do:
- Create multi-agent AI platforms and connect science with real business.
- Design multi-agent pipelines in LangGraph — with memory, logic, and agent interactions.
- Work with cutting-edge LLM families (LLaMA, Qwen, GPT, Claude, DeepSeek, Gemini, GigaChat).
- Deploy and scale models via vLLM / Ollama on A100/H100 clusters.
- Build secure, reliable tool-calling architectures (Trustcall).
- Evaluate and optimize pipeline quality with LangSmith and custom metrics.
- Integrate with FastAPI, enterprise data, and external systems.
- Depending on focus, work on mass-distribution products or deep client engagements in specific industries.
We expect you to:
- Be a Data Scientist confident in both research and production.
- Be passionate about multi-agent system architecture, LLM scaling, and elegant solutions that make business smarter.
- Have experience deploying and optimizing LLMs (open-weight or API-based).
- Have experience designing or tuning LangGraph / multi-agent pipelines.
- Be able to evaluate and debug complex LLM systems.
- Move quickly from prototype to production-ready solutions.
- Have English proficiency sufficient for reading papers and working with partners.
Tech stack:
- LLM: LLaMA, Qwen, GPT, Claude, DeepSeek, Gemini, GigaChat
- Architectures: LangGraph, CrewAI, AgentZero
- Infrastructure: vLLM, Ollama, Docker, A100/H100 clusters
- Backend: FastAPI, Alembic, PostgreSQL
- Security: Trustcall (secure tool calling)
- Evaluation: LangSmith, custom metrics
- Optimization: Unsloth, LoRA, PEFT
Would be a plus:
Experience with CrewAI / AgentZero, LoRA / PEFT, FastAPI, PostgreSQL, Docker, or building secure AI architectures.
Frontend Engineer
What you’ll do:
- Build thoughtful and visually strong interfaces that make complex AI solutions intuitive and clear for users.
- Go beyond coding — shape user experience every day.
- Develop modern web applications using React + TypeScript.
- Work with the design system and components in Storybook.
- Integrate APIs and configure backend interactions.
- Create adaptive and intuitive interfaces that feel effortless to use.
- Collaborate closely with designers and the AI/ML team — from idea to release.
- Discuss architecture decisions and improve UI experience.
- Continuously evolve the product: experiment, add new features, and optimize.
We expect you to:
- Have at least 3 years of experience with React and TypeScript.
- Understand how ideas turn into real products.
- Be skilled in designing adaptive, clean interfaces.
- Know Zustand / MobX / Effector and REST API principles.
- Speak the same language with designers and backend developers.
- Be fluent in English and Russian for confident communication.
- Feel comfortable in a startup environment — where a lot depends on you.
- Help evolve our products and bring measurable value to our clients.
Tech stack:
- Frontend: React, TypeScript, Next.js, Tailwind, Zustand, Storybook
- Integrations: REST API, WebSocket
- UI/UX: component-based design, responsive layouts, design system integration
Legal
© 2025, Agentic Lab LLC. Trademark registered — Registration decision No. 1159553.
© 2025, Registered Software: Analytical AI Assistant based on the Agentic Lab Agentic Orchestrator.
© 2025, Registered Software: Analytical AI Assistant based on the Agentic Lab Agentic Orchestrator.