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N-iX

London, United Kingdom

1000+€45-85/hrFounded 2002
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About

Engineering services group with a dedicated data, AI and machine-learning practice covering generative AI consulting and implementation, AI agents and MLOps. London office; registered in Malta with delivery centers across Ukraine, Poland, Bulgaria, Romania, Sweden, India and Colombia.

Who They Work With

Enterprises with large in-house engineering teams that want AI adoption or ML work measured against an agreed baseline.

Based on 4 client engagements with a source URL · researched 23 Sept 2026

Our Take

N-iX publishes client ML work with stack and outcome detail: two fine-tuned LLMs that summarize, filter and classify multilingual support logs for a satellite-connectivity operator, run as SageMaker batch jobs under Airflow and credited with up to 40% faster troubleshooting, and a computer-vision system that identifies laptop motherboards across 2,000+ models and cut diagnosis from 30 to under 10 minutes.

Nearly every such study anonymizes the client; the named exception, Redflex, is labeled plainly as two computer-vision proofs of concept at 88% and 91% detection accuracy, and the largest logistics engagement is still described as in development.

The homepage now leads with APEX, a program for rolling AI coding tools into a client's engineering organization, where executives at WorkWave and First Student are quoted by name and the case studies publish baselines such as test coverage rising from 55% to 81%.

The weaker fit is buyers who need a named reference for a production model before signing, or a small team buying one contained build rather than engineering capacity.

Key strengths

  • The satellite-support study lays out the architecture step by step—Airflow, EMR, SageMaker batch transform, ECR, CloudWatch—instead of hiding it behind 'proprietary AI'
  • APEX case studies publish before-and-after numbers: AI tool adoption from 13% to 91%, test coverage from 55% to 81%, PR cycle time from 12.4 to 7.2 hours
  • The Redflex study reports proof-of-concept accuracy (88% seat-belt detection, 91% person detection) and calls the work PoCs rather than dressing it as a deployment

Good to know

  • Almost every AI case study anonymizes the client—ask for a named reference whose production model N-iX built and still supports
  • The homepage pairs 250 engineers with 28% AI-generated code, but the study measured 28% in a 30-engineer pilot cohort—ask for organization-wide figures
  • Headquarters is in Malta and the London address is an office at 6 Bevis Marks, with delivery centers across Ukraine, Poland, India and elsewhere—ask where your team sits
Gabor Kiss

Reviewed by Gabor Kiss

Founder & Curator, AIAgencies.eu · 23 Sept 2026

Based on the agency's publicly available portfolio. Own this agency? Claim your profile to provide additional context or request a review update.


How we evaluate agencies

Notable Clients

Every engagement documented in a published case study

Documented engagements: Redflex, Gogo, WorkWave, and First Student. All 4 carry a source URL on file.

RedflexTwo computer-vision proofs of concept (July 2020 to September 2021) for seat-belt and distracted-driving detection, trained with TensorFlow and the NVIDIA Transfer Learning Toolkit; 88% seat-belt detection and 91% person-detection accuracy on a 30 FPS streamSource
GogoDedicated data team since January 2017 covering big data, data science, BI operations and reporting on AWS, Spark, Hadoop and Tableau for the in-flight connectivity providerSource
WorkWaveNamed testimonial from Chief Software Architect Greg Svitak on the APEX AI-adoption program reaching business analysts, QA and developers
First StudentNamed testimonial from CIO Sean McCormack on an APEX fleet-cascading pilot

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