Trinetix

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Your trusted technology partner

Company overview Locations Delivery mix Languages Service lines Industries Technologies Vendor partnerships Case studies Indicative rates ISO/IEC certifications Leadership Partner insights Event presence Social networks

Company overview

1,200

employees

2011

founded

As a globally trusted digital partner, we solve real business challenges with technology solutions to unlock a new world of opportunity.

Trinetix is proudly celebrating 14 years of progressive consultative strategy, design, and development of innovative solutions for our multi-industry Fortune 500 clients and partners. Our 1200+ brilliant minds and 1400+ engagements that helped create business transformation for our clients have propelled us to the technology partner of choice.

Contact details

Business info

Publicly traded: No
Majority shareholders: Management & Employees

Locations

Silver Breeze, Ukraine

Delivery Center

Founded2018

Employees500

Pavla Tychyny Ave, 1v, Kyiv, Ukraine, 02000

Nashville, United States

Sales OfficeHeadquartersDelivery Center

Founded2019

Employees30

750 Old Hickory Blvd, Brentwood, TN 37027, USA

Warsaw, Poland

Delivery CenterSales Office

Founded2022

Employees500

Józefa Piusa Dziekońskiego 1, 00-728 Warszawa, Poland

Buenos Aires, Argentina

Delivery Center

Founded2023

Employees50

Suipacha 946, C1008AAT Cdad. Autónoma de Buenos Aires, Argentina

Sofia, Bulgaria

Delivery Center

Founded2024

Employees50

Промишлена зона Хладилника, ul. Atanas Dukov 1, 1407 Sofia, Bulgaria

Riyadh, Saudi Arabia

Sales Office

Founded2024

Employees1

7998 Prince Abdulaziz Ibn Thunayyan St, 4927, An Nakheel, Riyadh 12391, Saudi Arabia

Engagement & delivery mix

Projects & services60%

Commercial modelBoth T&M and Fixed-price

Managed & dedicated teams10%

Staff augmentation29%

Buy-out optionNot possible

Build-Operate-Transfer1%

Language capabilities¹

English

Dedicated client-facing

Biz Dev: 0Mgmt: 0PMs: 0BAs: 0Tech Leads: 0Devs: 0

Service lines

Diversified across multiple service lines

Industries

Telecommunications40%

Healthcare20%

Freight Transport & Logistics20%

Business Services20%

Technologies

.NETAdobe Creative SuiteAmazon Web Services (AWS)AndroidAngularAppiumAutomation AnywhereAzure Cloud ServicesAzure Data Lake StorageblueprismC#CSS3CypressFigmaFirebaseFlutterGoogle AnalyticsGoogle Cloud Platform (GCP)HiveHTML5InvisioniOSJasmineJavaJavaScriptJestMicrosoft Power BIMOCHANode.jsNumPyPandasPowerpointProtractorPythonPyTorchReact NativeReact.jsSauce LabsScikit-learnSciPySeleniumSharePointSketchSparkTableauTensorFlowTypeScriptUiPathVue.jsXamarinZeplin

Vendor partnerships

Google Cloud

Self-reported

Partner Level

Sell & Service · Google Cloud Platform

Amazon Web Services (AWS)

Self-reported

Select Tier

Services Path

Case studies

View all1 / 5

Enabling Lucrative Agribusiness Partnerships

Our client is an agriculture enterprise specializing in producing carbon credits and leveraging digital technology to facilitate grain transactions for agricultural facilities, farming businesses, and farmers.

Joi: Boosting Product Growth via Better User Experience

Helping a Texas-based, fast-growing delivery service to craft a new experience and implement a long-term mobile strategy

Driving Improved Demand Forecasting Accuracy and Adaptability with AI and ML

Our client operates a fast-growing retail supply chain with 50+ stores. To plan for future supplies, the company manually collected and analyzed historical datafrom sales and production. As operations grew, statistical analysis alonecould no longer ensure accurate planning. FORECAST ACCURACY IMPROVED BY 10% INVENTORY COSTS REDUCED BY 15% STOCKOUT EVENTS DECREASED BY 13%

Indicative rates

ISO/IEC certifications⁴

ISO 9001

Quality Management Systems

Since 2025

ISO 14001

Environmental Management Systems

Since 2025

ISO 27701

Privacy Information Management (GDPR compliance)

Since 2025

ISO 27001

Information Security Management Systems

Since 2025

Leadership

Sasha Strozhemin

CEO / Founder

Łukasz Olechnowicz

Chief Business Officer

Oleksandr Liubushyn

Executive Vice President of Technology & Chief Architect

Partner insights

View all1 / 9

Enterprise AI Adoption: Lessons from Leaders

Only a minority of enterprises move beyond AI experimentation to meaningful results; adoption leaders succeed by aligning AI with core business goals, embedding it into operational routines, and building scalable, secure, and governed AI practices. The paper breaks down what “enterprise-scale AI” truly entails — from interoperability and reliability to usability and long-term sustainability — and illustrates how leading adopters prioritize business value, realistic expectations, and focus on high-impact use cases. For technology leaders, this insight helps differentiate between superficial pilots and strategic enterprise integration that drives measurable outcomes.

AI in Enterprise: Taking a Page from Adoption Leaders’ Books

Most enterprises are past “AI curiosity,” but many are still stuck moving from pilots to production: IBM reports ~42% have deployed AI while ~40% remain in exploration, and only ~17% say AI investments exceeded expectations. This article frames enterprise AI as an operating model (not a single tool) and defines “enterprise-scale” requirements like security, reliability, interoperability, and governance. It then distills what adoption leaders do differently: start from business goals and KPIs, map core processes and pain points, prioritize a smaller set of high-value opportunities, and tie AI to cost transformation to make ROI measurable. Tech leaders can use this as a checklist to de-risk scaling and avoid KPI-free experimentation.

AI Trends 2026: Agents, Federated Learning, Small Models

AI strategy for 2026 is shifting from “AGI soon” narratives to pragmatic deployments constrained by compute, risk, and adoption realities. Trinetix argues AGI remains unlikely in the near term due to resource/energy demands, unresolved issues like hallucinations, and unclear enterprise purpose. It highlights agentic AI as workflow-level augmentation that requires significant reskilling and AI literacy across business, agent, and human skills. It also points to federated learning to train models without centralizing sensitive data (notably in healthcare and fraud detection) and to small language models as faster, cheaper, domain-focused options. For tech leaders, the takeaway is to scope use cases tightly, pair agents with governance and training, and choose data/model architectures that fi

Event presence

//SHIFT: AI Across the Enterprise

18 Sept 2026

ConferenceIn-person

United States

TransparencyWins ecosystem context

This software engineering partner profile was contributed by Trinetix, a software engineering partner represented in the TransparencyWins ecosystem. TransparencyWins connects expert contributions with provider profiles, case studies, certifications and other capability signals so that tech buyers can better understand and compare potential software engineering partners.Profile completion levels reflect how completely required profile sections have been populated — they are not a quality, capability or suitability rating.

Trinetix

Company overview

Locations

Engagement & delivery mix

Language capabilities1

Service lines

Industries

Technologies

Vendor partnerships

Case studies

Indicative rates

ISO/IEC certifications4

Leadership

Partner insights

Event presence

Social networks

Language capabilities¹

ISO/IEC certifications⁴