Xenoss

• Develop, modernize, and integrate data stacks
• Build AI products and tools
• Adopt AI to improve business functions
• Engineer high-load systems, data engines, and AI solutions

The company was founded in 2013 by AdTech veterans. Its experience includes architecting an early mobile demand-side platform and building technology for startups and enterprises handling large-scale growth. Xenoss began in AdTech and MarTech and has expanded its expertise to areas including oil and gas, gaming, and finance.

Mission and vision

Xenoss's mission is to help enterprises bring AI from theory to practice by making it accessible, reliable, and impactful at scale. Its vision is to lead enterprises in building AI-driven ecosystems that help organizations outperform and redefine how industries operate.

Experience and recognition

• More than 10 years of building data-centric solutions
• More than 50 data and AI platforms built and deployed
• Recognized among the top 100 fastest-growing American software companies on the Inc. 5000 list
• Average solution uptime stated as 99.4% on the company page
• Solutions trusted by Nestlé, Adidas, and Uber

Xenoss states that its certified partnerships provide no vendor lock-in and direct access to priority engineering resources.

• Data engineering: Custom data engineering solutions, scalable pipelines, real-time processing, DataOps, data stack integration, data migration, data quality, and data infrastructure.
• AI agents and multi-agent systems: Systems that automate decision-making, coordinate tasks, and integrate with a company's technology stack using business logic and data.
• Generative AI: Model integration and fine-tuning, custom content-generation tools, simulation, personalization, synthetic data workflows, copilots, and retrieval-augmented generation systems.
• Enterprise knowledge management: Secure, context-aware systems combining RAG, semantic search, and access governance so teams can query internal data.
• Predictive modeling: Production-grade systems for use cases such as churn risk and advertising conversion forecasting, with control, traceability, and integration.
• Fine-tuning LLMs: Domain-specific language models using parameter-efficient techniques, distributed training infrastructure, and continuous learning pipelines.
• Hyperautomation: Intelligent automation using AI agents, LLMs, and cross-system orchestration to streamline operations and reduce manual effort.

Additional engineering services

The company's listed capabilities also include computer vision, conversational AI, cloud services, AI consulting, custom datasets, ML and MLOps, CloudOps, robotic process automation, business intelligence, data analytics, data visualization, and infrastructure cost optimization.

Industry applications

Xenoss works across advertising, sales and marketing, oil and gas, gaming, finance and banking, healthcare, pharmaceuticals, CPG, retail and ecommerce, manufacturing, and IoT. Example applications include fraud detection, credit scoring, predictive maintenance, demand forecasting, supply-chain optimization, customer segmentation, real-time analytics, and healthcare data infrastructure.

AdTech engineering

Xenoss develops custom AdTech and programmatic software using data engineering and machine learning expertise. Its solutions support yield optimization, audience targeting, inventory management, campaign measurement, and ad spend optimization.

AdOps multi-agent systems

Xenoss can build coordinated AI agents for advertising operations, including:

• Strategy and campaign orchestration
• Audience segmentation using CRM, CDP, and third-party data
• Creative generation with LLMs and diffusion models
• Media buying and bidding strategy management
• Budget allocation across channels, audiences, and campaigns
• Performance analysis and reporting
• Ad fraud detection for invalid traffic, click fraud, impression fraud, and bot activity
• Campaign experimentation, including A/B and multivariate testing

These agents can be integrated into structured workflows in which they exchange tasks and information to support end-to-end campaigns.

AdTech solutions

For publishers, AdTech providers, and media agencies, Xenoss develops and supports solutions such as private marketplaces, header-bidding systems, RTB technology, SSPs, auction engines, video ad servers, yield-management applications, ad monetization SDKs, ad mediation software, CTV and OTT solutions, data management systems, CDPs, and real-time performance monitoring tools.

For advertisers and brands, offerings include white-label and self-serve DSPs, mobile DSPs, DMPs, RTB bidders, audience segmentation components, conversion predictors, programmatic anti-fraud systems, campaign tracking and reporting tools, DOOH solutions, programmatic video and audio solutions, and AdOps automation.

Technical focus

Xenoss highlights real-time data processing, high-load architectures, multi-cloud strategies, scalable AI models, privacy-preserving computation, and technology-agnostic stack selection. Its AdTech work covers display, native and social, DOOH, video, voice, CTV, and OTT advertising formats.

Contact details

• Email: hello@xenoss.io
• Phone: +1 917 398 0067
• Phone: +44 7470 934 033

The website invites prospective clients to request a consultation or talk to Xenoss engineers about AI, data engineering, and custom software solutions.

Main offices

• US headquarters: 1719 East 12th St, Brooklyn, NY 11229, USA
• Warsaw R&D, Poland: 1, Dziekońskiego st., 00-728
• Wrocław R&D, Poland: 74/320 Marsz. Józefa Piłsudskiego st., 50-020
• London office, UK: The Legacy Centre, 85 Great Titchfield Street, W1W 6RJ
• Kyiv R&D, Ukraine: 1B, Vadyma Hetmana st., 03057

Contact

• Email: hello@xenoss.io
• Phone: +1 917 398 0067
• Phone: +44 7470 934 033

Xenoss invites prospective clients to request a consultation or talk with its engineers about building AI-powered solutions.

• Data engineering: Custom data engineering solutions, scalable pipelines, real-time processing, and DataOps.
• AI agents and multi-agent systems: Systems that automate decision-making, coordinate tasks, and integrate with existing technology stacks using business logic and company data.
• Generative AI: Model integration and fine-tuning, plus custom tools for content generation, simulation, personalization, and synthetic data workflows.
• Enterprise knowledge management: Secure, context-aware systems using retrieval-augmented generation, semantic search, and access governance.
• Predictive modeling: Production-grade systems for use cases such as churn risk and ad conversion forecasting, with control, traceability, and integration.
• Data migration: Custom migration architectures with incremental transfers, automated validation, and parallel processing for moving critical data while maintaining business continuity.
• LLM fine-tuning: Parameter-efficient techniques, distributed training infrastructure, and continuous learning pipelines for domain-specific language models.
• Hyperautomation: Intelligent automation using AI agents, large language models, and cross-system orchestration to streamline operations and reduce manual effort.

Additional capabilities listed by Xenoss include computer vision, conversational AI, cloud services, AI consulting, ML and MLOps, custom datasets, CloudOps, robotic process automation, and business intelligence.

• Develop, modernize, and integrate data stacks
• Build AI products and tools
• Adopt AI to improve business functions
• Engineer high-load and legacy systems

The company was founded in 2013 by AdTech veterans. AdTech and MarTech were Xenoss's starting points, and the company now works on high-load systems, data engines, and AI solutions across industries including oil and gas, gaming, and finance.

Xenoss states that its mission is to bring AI from theory to practice by making it accessible, reliable, and impactful at scale. Its vision is to lead enterprises in building AI-driven ecosystems that help organizations outperform and redefine how industries operate.

Experience and recognition

• More than 10 years of building data-centric solutions
• More than 50 data and AI platforms built and deployed
• Recognized among the top 100 fastest-growing American software companies on the Inc. 5000 list
• Average solution uptime of 99.4%
• Technology that powers millions of operations per second
• Solutions capable of processing dozens of petabytes per month

Xenoss says its certified partnerships provide no vendor lock-in and direct access to priority engineering resources.

AdOps multi-agent systems

Xenoss can build interconnected AI agents for advertising operations, including:

• Strategy and campaign orchestration
• Audience segmentation using CRM, CDP, and third-party data
• Creative generation using LLMs and diffusion models
• Media buying and real-time bidding optimization
• Dynamic budget allocation
• Campaign performance analysis
• Ad fraud detection for invalid traffic, click fraud, impression fraud, and bot activity
• A/B and multivariate campaign experimentation

These agents can be integrated into structured workflows in which they exchange tasks and information to support end-to-end campaigns.

Advertising platforms and components

For publishers, AdTech providers, and media agencies, Xenoss develops or supports private marketplaces, header-bidding solutions, RTB technology, SSPs, auction engines, video ad servers, yield-management applications, ad monetization SDKs, ad mediation software, exchanges, networks, CTV and OTT solutions, data management systems, CDPs, and real-time performance monitoring tools.

For advertisers and brands, its offerings include white-label and self-serve DSPs, mobile DSPs, DMPs, RTB bidders, audience segmentation components, smart targeting, conversion prediction, anti-fraud systems, campaign tracking and reporting, DOOH, programmatic video and audio, and AdOps automation.

Advertising formats

Xenoss supports software for display, native and social, digital out-of-home, video, voice, and addressable TV formats, including CTV and OTT.

Engineering characteristics

The company describes its AdTech solutions as capable of handling high-throughput, real-time data such as user interactions, ad impressions, clickstream data, and bid requests. It also cites multi-cloud architecture, scalable AI models, privacy-preserving techniques such as federated learning and differential privacy, pre-built development accelerators, and a technology-agnostic approach.

• Advertising: High-throughput data infrastructure and real-time ML pipelines for yield optimization, audience segmentation, dynamic pricing, and predictive targeting.
• Sales and Marketing: Segmentation engines, predictive lead scoring, attribution models, and personalized customer experiences.
• Oil and Gas: Real-time analytics for sensor data from drilling operations, refineries, and pipelines.
• Gaming: Behavioral analytics, dynamic difficulty adjustment, fraud detection for in-game economies, and A/B testing.
• Finance and Banking: Real-time fraud detection and credit risk models with regulatory compliance requirements.
• Healthcare: HIPAA-compliant infrastructure integrating EHR systems, medical devices, and claims data.
• Pharmaceuticals: Research data platforms integrating molecular data, clinical trial results, and real-world evidence.
• CPG: Data platforms connecting manufacturing, distribution, and point-of-sale data for trade promotion and supply chain operations.
• Retail and Ecommerce: Unified online and in-store data, real-time inventory visibility, and demand forecasting.
• Manufacturing: Industry 4.0 infrastructure connecting machines, sensors, and MES systems for predictive maintenance, quality control, and production optimization.
• IoT: Edge-to-cloud architectures for device fleets with varying connectivity, processing, and latency requirements.