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Meet the engineers accountable for your system.

Syntalith is a team of engineers. The conversation about your process is led by an engineer who then designs the system, builds it and is responsible for its operation.

years of team experience in software development
22+
engineers: two founders and two external auditors
4
the team builds and maintains production systems
since 2018

Who builds AI systems at Syntalith?

Short answer

The systems are designed and implemented by Syntalith founders, Artem Lisovtsov and Serhii Ivanchatenko. Artem has been building production systems for over 6 years. Serhii has over 7 years of commercial experience. In complex projects, the architecture is independently checked by Przemysław Markiewicz and Piotr Łach. The team has a total of over 22 years of experience in software development.

Where did Syntalith engineers work?

2017–2021: Artem, Przemek and Piotr study computer science together at the Lublin University of Technology.

Serhii Ivanchatenko7+ yearsLinkedIn ↗CRM and PLM systems for global companies
Artem Lisovtsov6+ yearsLinkedIn ↗from backend to AI architecture
Przemysław Markiewicz5+ yearsLinkedIn ↗GenAI team technical lead
Piotr Łach4 yearsLinkedIn ↗backend and RAG in high-traffic systems

Artem and Serhii design and build each system.

They are both co-founders and engineers. Together they are responsible for the architecture, construction and operation of each system.

Artem Lisovtsov, Co-founder · Applied AI/ML Architect

Artem Lisovtsov

Co-founder · Applied AI/ML Architect

LinkedIn ↗

More than 6 years in production systems: backend, AI/ML, FinTech, and MediaTech

Co-founder of Syntalith; designs the architecture of every deployment and owns the AI/ML layer. He has more than six years of experience spanning custom CMS and CRM systems, e-commerce, high-traffic backends, and AI/ML. At Andersen Lab, he progressed from Senior Backend Engineer to AI/ML Engineer and AI Systems Architect. His work covered the full path of production AI systems: chatbots, model training and fine-tuning, private deployments, RAG platforms, workflow orchestration, and agents that use governed sources and tools. He built semantic search on AWS Bedrock, OpenSearch, and pgvector for production load, monitoring, and maintainability. He also developed FinTech and MediaTech systems serving hundreds of thousands of users a day, including for a forex broker and a European TV broadcaster. He runs Syntalith's own conversational systems and co-builds odbierze.ai, a specialist AI voicebot implementation agency.

At Syntalith
architecture of every deployment and the AI/ML layer
Experience
more than 6 years across full-stack, backend, high-traffic systems, and AI/ML
AI/ML and GenAI
chatbots; model training and fine-tuning; private deployments; RAG and semantic search; workflow orchestration; AI agents using governed sources and tools
Systems and agency
Syntalith conversational systems running in production and odbierze.ai, an AI voicebot implementation agency
Certifications
AWS Certified Machine Learning – Specialty; Claude Certified Architect, Foundations (Anthropic)
Training
five individual AI training sessions, including Kuba Koziej
Named reference
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care: one-to-one training, a personal AI operator and team AI enablement.
  • Python
  • Golang
  • AWS
  • AI/ML
  • Voice AI
  • AI agents
Serhii Ivanchatenko, Co-founder · Voice AI & Agent Systems Engineer

Serhii Ivanchatenko

Co-founder · Voice AI & Agent Systems Engineer

LinkedIn ↗

More than 7 years of commercial .NET work across PLM, CRM, and internal systems

Co-founder of Syntalith; together with Artem he runs the company and odbierze.ai, a specialist AI voicebot implementation agency. He has more than seven years of commercial .NET experience. At Trace One, he develops PLM modules and integrations, distributed processing, and CI/CD workflows in Azure. Previously, he worked on PLM systems for global food and consumer-goods manufacturers, with high-volume data-exchange APIs, MS SQL and Oracle, and asynchronous processing. He also built an internal CRM and engineering-automation platform for more than 100 users from scratch. At Syntalith, he builds voice AI and agent systems: telephony, CRM and calendar integrations, and the backend through which agents use client tools. He defines evaluation sets, tests scenarios and edge cases, reviews execution traces, and iteratively refines prompts, tools, and exception handling.

Commercial experience
more than 7 years in .NET, since 2018
Domains
PLM for global food and CPG manufacturers, CRM, enterprise
At Syntalith
voice AI and agent systems: telephony, integrations, MCP components, workflows, and Qdrant
Voice AI
lead engineer of odbierze.ai: call handling, calendar and CRM integrations, and conversation monitoring
Evaluation and refinement
case sets, scenario and edge-case testing, trace analysis, and iterative prompt and tool refinement
  • .NET
  • Voice AI
  • AI agents
  • LLM evals
  • MSSQL/Oracle
  • Qdrant

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →

A second pair of eyes on complex audits.

They run production LLM systems in large organizations. We studied computer science together at Lublin University of Technology. For complex audits and architecture decisions, they provide an independent review under their own names.

Przemysław Markiewicz, GenAI Tech Lead · external auditor

Przemysław Markiewicz

GenAI Tech Lead · external auditor

LinkedIn ↗

He has more than five years of IT experience, including more than two years of hands-on AI and LLM work. He leads a GenAI team at PwC Poland and was previously a lead software engineer at Asseco Business Solutions. He designs and deploys RAG and multi-agent systems, runs open LLMs on-prem, and leads fine-tuning and evaluation. He builds Python microservices on Kubernetes and automates infrastructure across AWS and Azure with Terraform and Helm.

Experience
more than 5 years across testing, software engineering, solution architecture, and technical leadership
GenAI systems
RAG from conventional implementations to multi-agent architectures, LangChain, LlamaIndex, and vector databases
Models and evaluation
on-prem hosting of open LLMs, fine-tuning, and evaluation of production outcomes
Infrastructure
Python, Kubernetes, Terraform, Helm, CI/CD, AWS, and Azure
  • Python
  • RAG / multi-agent
  • LLMOps
  • Kubernetes
  • Terraform/Helm
  • AWS/Azure
Piotr Łach, Backend & AI Engineer · external auditor

Piotr Łach

Backend & AI Engineer · external auditor

LinkedIn ↗

Spent four years at Asseco Business Solutions building and operating the backends of high-traffic systems. He designed APIs with FastAPI and Pydantic, asynchronous pipelines with Celery and RabbitMQ, and a RAG chat platform with Qdrant. He integrated LangChain, LangGraph, and MCP, owned Prometheus monitoring, and automated local vLLM deployments on Kubernetes with resource-aware scheduling and error handling.

Production backend
Python, FastAPI, Pydantic, PostgreSQL, and API architecture for high-traffic systems
AI systems
RAG, Qdrant, LangChain, LangGraph, and MCP with OpenAI, Anthropic, and local models
Processing and monitoring
Celery, RabbitMQ, Prometheus, unit testing, and integration testing
Local models
automated vLLM deployment on Kubernetes with resource-aware scheduling and error handling
  • Python
  • FastAPI
  • RAG/Qdrant
  • Kubernetes
  • Celery/RabbitMQ
  • vLLM

Who books the calls.

Daria usually handles the first message, qualification and scheduling. An engineer leads the technical conversation and process review.

Daria Sandach, Business Development

Daria Sandach

Business Development

LinkedIn ↗

At Syntalith since August 2025, she has run prospecting, qualification, and scheduling, including for odbierze.ai. She talks with owners about where a team loses time and context and whether an AI agent suits a given process; her background is business psychology. If you book a review, she will usually coordinate it.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
When we roll out ChatGPT, Claude or Copilot, you buy the licences directly from OpenAI, Anthropic or Microsoft and they invoice you. We add nothing to the licence.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.