Make yourbusinesswork better.
- Repeated handoffs create duplicate work.
- Unclear responsibility slows decisions.
- New tools create little value when they are not part of daily work.
Resolv improves the process with a clear owner, a practical solution, and measurable results: lower operating costs, faster delivery, and fewer errors.
Documented results
A few public examples of what changes when repetitive work becomes a system.
Logistics · AI workflow
≈€48K
Reported annual savings
Eczacıbaşı reports that its MareXis AI logistics agent saved the equivalent of 16 working days per month.
Microsoft case studyOperations · AI agent
19K
Reported hours saved monthly
Capita reports 19,000 hours saved each month. Its email-triage agent also reduced response times by 60%.
Microsoft case studyCustomer support · Automation
40%
Fewer support tickets in deployed areas
Cegid reports a 17% overall reduction in support-ticket volume, reaching 40% where its AI virtual agent was deployed.
Google Cloud case studyPublicly reported results from specific implementations. Figures are not independently verified by us, are not guaranteed, and outcomes vary by workflow, data and operating context.
How we help
Practical improvements,
built for your business.
Every solution is chosen for a clear business outcome: lower cost, faster delivery, fewer errors, or more capacity. We then build it, connect it, and support your team in using it.
Improve a process
Simplify daily work.
Clarify steps, remove repeated tasks, and automate routine work where it makes sense.
Use AI practically
Apply AI with care.
Use AI for search, document work, support, and decisions—only where it creates clear value.
Build the right software
Create useful tools.
Design and deliver internal tools, customer products, and integrations around a real business need.
Connect systems and data
Make information reliable.
Connect systems, organize data, and create dependable foundations for reporting and operations.
Business benefits
Lower cost. More capacity. Better control.
The goal is not technology for its own sake. It is to remove avoidable work and help the business deliver more reliably with the people and systems it already has.
01
Lower operating costs
Cut repetitive work, duplicate effort, and avoidable corrections.
02
More team capacity
Free time for customers, decisions, and higher-value work.
03
Faster delivery
Reduce waiting, handoffs, and follow-up tasks.
04
Fewer costly errors
Reduce rework and waste with clearer, dependable processes.
Resolv business cases.
02 / 05
A clear path from need to result.
Understand
Learn how the work runs.
Prioritize
Agree on the main improvement.
Design
Choose a practical solution.
Deliver
Build and connect it.
Improve
Measure and refine.
Start with the business.
We learn the process, the people involved, and the result you want.
Define a clear plan.
We select the smallest useful change, with clear scope, responsibilities, and expected value.
Put it into daily use.
We build, connect, test, and introduce the solution with your team.
Insights
Make the next process decision with clearer evidence.
Practical guides for choosing automation, estimating value, using AI responsibly, and improving the tools your team already uses.
View all insightsWhich business process should you automate first?
Use a six-factor scorecard and a measured cost example to choose a credible first workflow.
↗Calculate the cost of a manual process.
Estimate savings, payback, and first-year ROI with a transparent calculator.
↗10 useful AI use cases—and 5 to avoid.
Separate useful assistance from risky or needlessly complex automation.
↗A senior team, working with you directly.
Nickolas Kyryliuk
Products · Web · Mobile
Builds dependable digital products and internal tools from idea through launch.
View profileVladislav Yaromiy
Applied AI · Data
Turns document, search, and knowledge work into reliable AI and data solutions.
View profileFaycal Benaissa
Systems · Cloud · AI
Connects applications, infrastructure, and AI so they work reliably in daily operations.
View profile01 · Team profile
Nickolas Kyryliuk
Full-stack Software Engineer · Team Lead
Builds web and mobile products with React, React Native, TypeScript and Node.js. Combines hands-on engineering with team leadership, backend architecture and Cloud delivery.
Download CV (PDF)
Original CV in English
Selected experience
Apex Tech
Team Lead and previously Full Stack Software Engineer. Leads a team of three developers; built an IoT medical application, native mobile modules and AWS-backed services.
Esme Learning · Riff Analytics
Built video-call management tools, browser-based recording and playback, and analytics interfaces using React, Jitsi and FFmpeg.
Freelance
Delivered ecommerce interfaces, Go backend services, Stripe payments and automated CI/CD pipelines.
Core expertise
- React
- React Native
- TypeScript
- Node.js
- GraphQL
- Go
- AWS
- Docker
- Kubernetes
- CI/CD
Selected projects
Lift OS — a personal fitness app for workout planning, recovery and nutrition, built with React Native, Django, Python and WorkOS.
Education & credentials
Nanotechnologies, Chernivtsi National State University (2019–2022). AWS Solutions Architect Associate (2025).
02 · Team profile
Vladislav Yaromiy
Data Scientist · AI Engineer
Designs and ships production ML and AI systems, from data pipelines and model training to LLM and RAG applications, evaluation and monitoring.
Download CV (PDF)
Original CV in English
Selected experience
Meilleurtaux
Built a RAG knowledge assistant, document classification and extraction systems, and ML evaluation and monitoring on GCP and Vertex AI.
Product-live
Developed a product-data centralization platform with TypeScript, Nest.js and PostgreSQL, including automated data-quality checks.
Voypost · Yva Int.
Built ERP and ecommerce applications, operational Workflows, REST API integrations and delivery-service connections.
Core expertise
- Python
- LLM
- RAG
- NLP
- Vertex AI
- GCP
- BigQuery
- MLflow
- Airflow
- Docker
Selected projects
Founder of Umbra — infrastructure for live tokenized-asset market events, with low-latency data ingestion and REST and WebSocket APIs.
Education & credentials
M.Sc. MIAGE — Business Intelligence & Decision Support, Université Paris Dauphine-PSL (2024–2026). B.Sc. MIAGE (2023–2024).
03 · Team profile
Faycal Benaissa
Data Scientist · AI Engineer
Builds AI agents, production LLM applications and large-scale data systems. Connects applied research with practical software, MLOps and end-to-end delivery.
Download CV (PDF)
Original CV in English
Selected experience
Alcatel-Lucent Enterprise
Developed multi-agent CVE assessment, integrations with CodeQL and Semgrep, and AI debugging tools grounded in code graphs and production logs.
LCL Banque
Built an internal skills and architecture-maturity platform using Go, Nuxt 3 and PostgreSQL, with CI/CD deployment through GitLab, ArgoCD and Kubernetes.
Dau’IA · Dauphine-PSL
Heads the technical division and leads applied quantitative-finance research, reproducing academic strategies and mentoring student contributors.
Core expertise
- Python
- AI agents
- LLM
- RAG
- LangChain
- PySpark
- SQL
- Docker
- Kubernetes
- MLOps
Selected projects
Projects include a distributed recommender system, a data warehouse, LLM training-data quality evaluation and an algorithmic-bias analysis platform.
Education & credentials
M.Sc. MIAGE-ID — Information Systems & Decision Engineering, Université Paris Dauphine-PSL (2024–2026). B.Sc. Computer Science, MIAGE track (2023–2024).