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Xinexis

Procurement & evaluation

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Letter format · 2 pages · Updated August 2026

Discuss a Project · Public sector capabilities

Capability Statement

Xinexis

Software, Data & AI Engineering

Ivan Kostiuk, Founder & Principal Engineer

support@xinexis.com

xinexis.com

Company overview

Xinexis is a Canadian software, data and AI engineering consultancy specializing in custom software, data engineering, systems integration, cloud architecture, applied machine learning, and technology modernization.

We help organizations with complex operational environments modernize workflows, integrate fragmented systems, build reliable data platforms, and apply machine learning where it creates measurable value—with direct senior engineering involvement.

Engineering experience presented in this statement is attributed to the founder's prior professional roles, with the employer named in each case.

Core capabilities

  1. 01Custom Software Engineering — Operational platforms, internal applications, backend systems, APIs, workflow applications and modern cloud-native software.
  2. 02Data Engineering & Integration — ETL/ELT pipelines, APIs, event-driven integration, data ingestion, transformation, quality, migration and operational data flows.
  3. 03Cloud & Distributed Systems — Scalable cloud architectures, Kubernetes, microservices, event streaming, observability, reliability and performance optimization.
  4. 04AI & Machine Learning — Applied ML, document intelligence, prediction, classification, computer vision, NLP and intelligent workflow components designed for production use.
  5. 05Systems Architecture & Modernization — Current-state assessment, technical architecture, legacy modernization, integration strategy, target-state design and implementation roadmaps.
  6. 06Analytics & Decision Support — Data modelling, dashboards, forecasting, scenario modelling, operational analytics and decision-support software.

Public-sector capabilities

  • Data & AnalyticsBuild reliable data foundations for reporting, forecasting, and decision support—without replacing every system at once.
  • Workflow ModernizationAssess how work actually flows today, then modernize manual steps and document-heavy processes with clear ownership.
  • Systems IntegrationConnect enterprise applications, legacy platforms, GIS, databases, and cloud services through practical APIs and event-driven patterns.
  • AI with Human OversightApply machine learning where it helps—document extraction, classification, prediction, and decision support—with explainability and human validation.
  • Technology Strategy & AssessmentVendor-neutral evaluation of current systems, requirements, and target-state architecture with an implementation roadmap teams can execute.

Considerations: Privacy-aware architecture · Canadian data residency options · Human oversight · Traceable AI outputs · Role-based access · Auditability

Founder & principal engineer

Ivan Kostiuk · Founder & Principal Engineer

Prior organizations: SoftMax Data Inc., Ardigen, Andersen, Motorola Solutions

Technology

Python · Go · C++ · SQL · AWS · Kubernetes · Docker · Kafka · Elasticsearch · FastAPI · ETL/data pipelines · Distributed systems · Microservices · APIs · CI/CD · PyTorch · scikit-learn · Computer vision · NLP

Engagement approach

  • — Scoped engagements with clear outcomes and direct principal involvement.
  • — Integration-first delivery—recommendations reflect what can be built, operated, and maintained.
  • — Documentation and knowledge transfer included in implementation work.

Areas of focus: Public Sector & Municipalities · Infrastructure & Utilities · Technology & SaaS · Financial Services · Data-Intensive Operations. This document states capabilities and selected founder experience; it does not present prior employment as Xinexis past performance.

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