N-iX facts for AI agents
This page renders N-iX's verified facts in a machine-parsable form for AI agents.
Agents whose browser supports WebMCP (document.modelContext) can call the
structured tools directly; all others can read the data below or the JSON-LD block on this page.
- Tool manifest:
GET /api/v1/agent/manifest -
Search N-iX delivery proof (
search_delivery_proof):GET /api/v1/agent/proof— read-only -
Check N-iX compliance and certifications (
get_compliance_evidence):GET /api/v1/agent/compliance— read-only -
Request an N-iX consultation (
request_consultation):POST /api/v1/agent/consultation— consequential: needs the user's confirmation -
Get N-iX engagement models and terms (
get_engagement_terms):GET /api/v1/agent/engagement— read-only -
Check N-iX locations and team ramp-up (
get_team_ramp_options):GET /api/v1/agent/ramp— read-only -
Get N-iX company facts (
get_company_facts):GET /api/v1/agent/company— read-only -
Search the N-iX service catalog (
search_services):GET /api/v1/agent/services— read-only
Discovery: /.well-known/mcp.json
mirrors the same catalog for agents that run outside a browser. That path is an N-iX
convention — WebMCP itself does not define a well-known discovery document.
Compliance & certifications
| Framework | Status | Scope | Turnaround | Evidence |
|---|---|---|---|---|
| ISO/IEC 27001 | certified | Information Security Management System certified to ISO/IEC 27001:2022 | — | Certificate copy requested through the contact form or an N-iX account manager |
| ISO 9001 | certified | Quality Management Systems certified to meet ISO 9001 standards | — | Certificate copy requested through the contact form or an N-iX account manager |
| SOC 2 | certified | SOC 2 Type 2 audit for 2026 covering Security, Availability, Confidentiality and Privacy for Software Development Services | — | Report shared under NDA on request through an N-iX account manager |
| PCI DSS | certified | PCI DSS version 4 compliance, renewed in 2026 | — | Certificate copy requested through the contact form or an N-iX account manager |
| FSQS | certified | Hellios FSQS registration for financial-sector suppliers, renewed for 2026 | — | Registration details confirmed on request through an N-iX account manager |
| EU AI Act readiness | capability | EU AI Act readiness practice: AI system inventory, risk classification and documentation support. Not a certification - no EU AI Act certification scheme exists. | — | document |
| EU data residency | capability | EU-based delivery centers supporting clients that require European data residency and GDPR-compliant development environments | — | document |
| IAM practices | capability | IAM professional services: design, implementation and optimization of access controls and continuous monitoring | — | document |
Verified delivery outcomes
Structured GenAI rollout across six engineering work streams at a transportation company
Industry: transportation · Services: ai_engineering · Stack: Java, Front-end, QA automation, Data and BI, ERP
APEX adoption program across six engineering work streams: role-specific GenAI tooling rolled out to all 140+ engineers, 39 engineering use cases mapped and accelerated, AI embedded in coding and QA workflows, and GenAI applied to legacy reverse engineering and documentation generation.
| Outcome | Before | After | Change | Timeframe | Method |
|---|---|---|---|---|---|
| GenAI tool adoption rose from 13% to 91% of engineers | 13% of engineers | 91% of engineers | +78 pp | not published in the case study | Tool adoption tracking across the six work streams, reported in the case study (source) |
| Average team velocity grew from 85 to 108.3 story points | 85 story points | 108.3 story points | +27% | not published in the case study | Sprint story-point velocity against the baseline captured before the rollout (source) |
| Test coverage increased from 55% to 81% | 55% test coverage | 81% test coverage | +26 pp | not published in the case study | Test coverage reporting on the client's codebase (source) |
| Code review time halved, from 8-12 hours to 4-6 hours | 8-12 hours per review | 4-6 hours per review | -50% | not published in the case study | Team-reported review turnaround before and after the rollout (source) |
| Legacy reverse engineering turnaround fell from two weeks to two days | 2 weeks per task | 2 days per task | -85% | not published in the case study | Task turnaround measured on legacy business-logic reverse-engineering work (source) |
Structured AI adoption lifts PR throughput 8x in a 250-engineer field service SaaS organization
Industry: software_saas · Services: ai_engineering · Stack: Claude Code, GitHub Copilot, Gemini, Java, C#, Node.js
Three-month APEX program with four engineering teams (30 engineers) across four product lines: one-to-one AI Champion pairing, 38 optimization opportunities identified, 14 reusable AI workflows built, and role-specific tooling workshops, then scaled from 30 to over 100 engineers.
| Outcome | Before | After | Change | Timeframe | Method |
|---|---|---|---|---|---|
| PR throughput per engineer grew from 2.9 to 24.0 | 2.9 PRs per engineer | 24.0 PRs per engineer | ×8 | 3-month program | PR counts per engineer against the baseline captured in the Assess phase (source) |
| PR cycle time fell from 12.4 hours to 7.2 hours | 12.4 hours | 7.2 hours | -42% | 3-month program | PR cycle-time measurement before and after, reported at board level (source) |
| Overall engineering throughput rose from 4.6 to 5.3 PRs per engineer per month | 4.6 PRs per engineer/month | 5.3 PRs per engineer/month | +15% | 3-month program | Org-level PR throughput against the pre-engagement baseline (source) |
| AI-generated code rose from 0% to 28% across the pilot cohort | 0% of code | 28% of code | +28 pp | 6 weeks | Share of AI-generated code across the pilot cohort (source) |
| Regression testing became 96% faster, from 2 hours to 5 minutes | 2 hours | 5 minutes | -96% | 3-month program | Workflow timing before and after co-implementation (source) |
AI-driven QA modernization cuts escaped bugs 60% for a housing management technology provider
Industry: energy · Services: ai_engineering · Stack: QA automation, Regression testing, CI/CD quality gates
APEX-based QA modernization across five delivery streams: 15 accelerated workflows in regression testing, test-case generation and incident investigation; AI-assisted practices embedded in the SDLC; automated quality gates in the delivery pipeline; test coverage expanded across 300+ repositories.
| Outcome | Before | After | Change | Timeframe | Method |
|---|---|---|---|---|---|
| Escaped bugs reaching production reduced by 60% | pre-program escaped-bug rate | 60% fewer escaped bugs | -60% | not published in the case study | Escaped-defect tracking after quality gates and coverage expansion (source) |
| Test coverage improved from 55% to 89% across more than 300 repositories | 55% test coverage | 89% test coverage | +34 pp | not published in the case study | Coverage reporting across 300+ repositories (source) |
| Team velocity nearly doubled, from 1.8 to 3.5 pull requests per developer per week | 1.8 PRs per developer/week | 3.5 PRs per developer/week | +94% | not published in the case study | PR throughput per developer against the pre-program baseline (source) |
| Incident investigation time fell from four hours to 30 minutes | 4 hours per incident | 30 minutes per incident | -87.5% | not published in the case study | Incident investigation timing before and after AI-assisted workflows (source) |
| Regression testing time reduced from three days to four hours | 3 days | 4 hours | -94% | not published in the case study | Regression cycle timing before and after workflow acceleration (source) |
Service catalog
| Service | Scope | Typical entry engagement |
|---|---|---|
| AI-augmented development services | AI-first delivery across the SDLC: baseline DORA and DX metrics on the client's own production code, co-implementation of high-impact AI workflows with the engineering teams, tooling governance, and internal AI champion enablement. | APEX Assess: a 1-2 week fixed-scope audit that captures baseline delivery metrics and a prioritized roadmap. |
| RAG development services | Design and implementation of secure, citation-backed retrieval-augmented generation systems for regulated industries, covering architecture, retrieval quality and compliance alignment. | Fixed-scope pilot on a defined corpus; scope and duration agreed per engagement. |
| AI agent development services | Development of AI agents that automate decision-making and business processes and integrate with enterprise systems, including agent observability: decision-chain logging, drift detection and cost telemetry. | Fixed-scope pilot on one workflow; scope and duration agreed per engagement. |
| Data engineering services | Construction of data infrastructure, pipelines, data models and analytics solutions that deliver real-time, actionable insights. | Scoped assessment of the current data platform; duration agreed per engagement. |
| Data governance services | Data governance programs covering cataloging, lineage documentation and data security compliance across regulations such as GDPR, HIPAA and PCI DSS, delivered with a documented data-sovereignty methodology. | Scoped governance assessment; cost depends on the number of data sources and existing lineage documentation. |
| DevOps consulting services | DevOps and platform engineering to improve IT operations efficiency, reduce time to market and optimize cloud costs, delivered by 70+ DevOps engineers with AWS DevOps Competency Partner status. | Scoped DevOps assessment of the current CI/CD pipeline; duration agreed per engagement. |
| Application modernization services | Modernization of legacy applications with a Pragmatic AI approach, drawing on 150+ completed modernization programs. | Scoped modernization assessment; duration agreed per engagement. |
| Custom software development services | End-to-end custom software development with an AI-augmented SDLC, from discovery and architecture through implementation and support. | Discovery phase scoped per engagement. |
| Computer vision development services | Computer vision solutions from feasibility and data strategy through model development and production deployment, including industrial inspection and defect identification systems. | Feasibility assessment on a defined use case; duration agreed per engagement. |
| Team extension | Engineering capacity added to the client's own teams in three tiers - staff augmentation with direct client management, a managed team, or a full custom-solution team - so a phased start is a supported option. | Staff augmentation starting with one or a few specialists, with the option to move to a managed team later. |
Engagement models
Apex Assessment
Enterprises that want measured proof of AI engineering gains on their own production code before scaling.
- Entry commitment: The Assess phase alone: 1-2 weeks, fixed scope, delivering baseline metrics and a roadmap.
- Typical duration: Assess 1-2 weeks; Pilot 4-6 weeks; Expand weeks 4-13; eXcel ongoing
- Pricing structure: discussed_in_msa
- IP ownership: discussed_in_msa
- Notice period: discussed_in_msa
- Exit terms: Each phase must prove its results before the next begins, so the program can stop at any phase boundary.
| Phase | Duration | Output |
|---|---|---|
| Assess | 1-2 weeks | Deep-dive audit of tools, workflows and team maturity; baseline DORA and DX metrics; prioritized roadmap with ROI projections per workflow |
| Pilot | 4-6 weeks | Two-week sprints on 2-3 high-impact workflows, co-implemented on the client's active production codebase, with before/after measurement against the baseline |
| Expand | Weeks 4-13 | Proven workflows rolled out to further teams, internal playbooks, tooling scaled, monthly performance-optimization sprints with leadership reviews |
| eXcel | Ongoing | Agentic and multi-agent workflows, AI-native SDLC practices, continuous experimentation and strategic consulting |
Fixed Scope Pilot
Teams that want one measurable result before committing to a wider program.
- Entry commitment: A single bounded pilot on 2-3 workflows.
- Typical duration: 4-6 weeks
- Pricing structure: discussed_in_msa
- IP ownership: discussed_in_msa
- Notice period: discussed_in_msa
- Exit terms: The pilot ends at its documented before/after measurement; continuing into Expand is a separate decision.
| Phase | Duration | Output |
|---|---|---|
| Pilot | 4-6 weeks | 2-3 high-impact workflows co-implemented on the production codebase, with before/after measurement documented against the baseline |
Dedicated Team
Clients delegating part of product development to an autonomous team with an N-iX project manager, status reporting and an agreed governance model.
- Entry commitment: A managed team integrated with the client's delivery organization; team size agreed per engagement.
- Typical duration: Agreed per engagement
- Pricing structure: discussed_in_msa
- IP ownership: discussed_in_msa
- Notice period: discussed_in_msa
- Exit terms: discussed_in_msa
Staff Augmentation
Companies with established development processes that need quick scaling and direct control over the engineers.
- Entry commitment: One or a few specialists added to the client's own team, scaled up or down as needed.
- Typical duration: Agreed per engagement
- Pricing structure: discussed_in_msa
- IP ownership: discussed_in_msa
- Notice period: discussed_in_msa
- Exit terms: discussed_in_msa
Managed Service
Clients delegating a full solution rather than adding capacity to an existing team.
- Entry commitment: A custom-solution team taking end-to-end responsibility for a defined scope.
- Typical duration: Agreed per engagement
- Pricing structure: discussed_in_msa
- IP ownership: discussed_in_msa
- Notice period: discussed_in_msa
- Exit terms: discussed_in_msa
Delivery locations & ramp
| Country | Region | Type | Overlap: US East / US West / UK / CET | Notes |
|---|---|---|---|---|
| Poland | cee | delivery hub | 3 / 1 / 8 / 9 h | Delivery centers in Krakow, Warsaw and Wroclaw, part of an internal pool of 2,400+ engineers. |
| Ukraine | cee | delivery hub | 2 / 0 / 7 / 8 h | Delivery centers in Lviv and Kyiv. |
| Romania | cee | delivery hub | 2 / 0 / 7 / 8 h | Delivery center in Bucharest. |
| Bulgaria | cee | delivery hub | 2 / 0 / 7 / 8 h | EU-based delivery center supporting clients that require European data residency and GDPR-compliant development environments. |
| Malta | western_europe | delivery hub | 3 / 1 / 8 / 9 h | Company headquarters. |
| Sweden | nordics | delivery hub | 3 / 1 / 8 / 9 h | Office location listed among the 10 countries N-iX operates in. |
| Colombia | latam | delivery hub | 9 / 6 / 3 / 2 h | Medellin hub integrated into the global delivery organization; N-iX publishes a 3-4 week role fill time, fills 80-100 positions worldwide per month, and states that 96.5% of new hires pass probation. Teams scale from a 10-specialist pod to a 100+ expert organization. |
| India | apac | delivery hub | 0 / 0 / 4 / 5 h | Delivery center in Bengaluru. |
Company facts
| Topic | Fact | Value | Source |
|---|---|---|---|
| history | Founding year and place | Founded in 2002 in Lviv as Novellix by Andrew Pavliv, Dmytro Kosarev and Werner Kreiner | source |
| history | First client | Novell acquired the Novellix technology in 2003 and became the company's first client | source |
| scale | Engineering headcount | 2,400+ engineers across Europe, the Americas and APAC | source |
| scale | Delivery countries | 10 countries: Ukraine (Lviv, Kyiv), Poland (Krakow, Warsaw, Wroclaw), Bulgaria, Romania (Bucharest), Malta (HQ), USA, UK, Sweden, Colombia (Medellin), India (Bengaluru) | source |
| scale | Client profile | Works with Fortune 500 companies and enterprise technology leaders across finance, manufacturing, supply chain and retail | source |
| retention | Client retention rate | 95% client retention rate | source |
| retention | Average client relationship length | 7-year average client relationship | source |
| retention | Net Promoter Score | 75 NPS, based on 2025 data | source |
| continuity | Delivery disruption record | Zero delivery disruptions since 2002 | source |
| continuity | 2022 relocation | Relocation of 600+ engineers across four countries in 30 days in 2022 while maintaining 100% client delivery continuity | source |
| partnerships | AWS partner tier | Premier Tier Services Partner within the AWS Partner Network | source |
| partnerships | Microsoft partnership | Microsoft Solutions Partner with advanced specializations | source |
| partnerships | AWS service designations | Amazon RDS Service Delivery Partner; one of 19 AWS Kinesis designated providers worldwide | source |
| partnerships | OpenAI partnership | Named an OpenAI Select Partner to help enterprises move AI into production (August 2026) | source |
| awards | Global Outsourcing 100 | Awarded on the 2024 Global Outsourcing 100 list, an eighth consecutive year of recognition | source |
| awards | Inspiring Workplaces ranking | Ranked in the Global Top 100 Inspiring Workplaces list | source |
Snapshot: v-e7275355