We Architect
Digital
Infrastructure
1000, Rue Neuve 21, Bruxelles, Belgium, Belgium
Soft minimalism.
Structural precision.
PolarVectorWorks operates at the intersection of Scandinavian design philosophy and enterprise-grade engineering. We believe that restraint is the highest form of technical discipline — every pixel, every API call, every database schema is stripped to its essential geometry. Our work is not decoration; it is architecture that earns trust through the quiet confidence of things that simply work.
Founded
Brussels, Belgium
Discipline
Digital Systems Engineering
Philosophy
Nordic Hygge Minimal
Service Architecture
Nine engineered offerings. Three operational tiers. One precision system.
1 week
1
System Architecture Audit
from 450€
Discovery Sprint
We conduct a 5-day intensive review of your existing infrastructure stack. Every endpoint, dependency graph, and runtime configuration is mapped to produce a living topology diagram. We identify single points of failure, undocumented API contracts, and shadow deployments that bypass your CI/CD pipeline.
Vulnerability Surface Mapping
Using automated scanners paired with manual code review, we catalogue every attack surface from network ingress to database query layers. The final deliverable is a prioritized threat matrix ranked by exploitability and business impact, with clear remediation timelines for each finding.
Technical Debt Ledger
We quantify accumulated technical debt across your repositories using cyclomatic complexity metrics, dependency freshness audits, and test coverage deltas. Each debt item is tagged with an estimated refactoring cost in engineer-hours and a projected risk if left unresolved for the next two quarters.
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1.5 weeks
2
Interface Discovery Sprint
from 750€
User Journey Decomposition
Our analysts walk through every critical user path in your application, documenting friction points, cognitive load moments, and interaction failures. We use session recordings, heatmaps, and first-click tests to build an empirical map of where users succeed and where they abandon.
Component Inventory & Audit
Every UI component across your design system is catalogued with its visual state variants, accessibility compliance status, and cross-browser rendering behavior. We flag inconsistencies in spacing, typography scales, and color token usage that erode brand cohesion over time.
Interaction Pattern Report
A structured document mapping each user goal to the optimal interaction pattern—micro-animations, transition choreography, form validation rhythms—that aligns with your brand voice. Includes annotated wireframe suggestions for the three highest-impact improvement areas.
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2 weeks
3
Scoping Blueprint
from 1,200€
Requirements Crystallization
We translate your business objectives into a structured work breakdown with epics, user stories, acceptance criteria, and dependency chains. Every story is estimated in story points with a confidence interval, and the critical path through the project is identified before any code is written.
Resource Allocation Model
Based on the work breakdown, we produce a resource allocation matrix specifying the exact engineer profiles, design capacity, and DevOps hours required per sprint. This includes a risk-adjusted timeline with buffer zones for scope creep and external dependency delays.
Cost Projection & Milestone Map
A detailed financial projection breaks down costs by phase, resource type, and risk category. Milestone gates are defined with measurable exit criteria, ensuring that budget release is tied to verifiable deliverables rather than calendar dates.
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4 weeks
4
Algorithmic Core Engine
from 3,500€
Sprint 1 — Neural Architecture Design
We define the computational graph for your core algorithm, selecting between transformer, graph neural network, or hybrid ensemble architectures based on your data topology. The sprint produces a formal architecture specification with layer dimensions, activation functions, and loss function formulations.
Sprint 2 — Training Pipeline Assembly
Data ingestion, preprocessing, augmentation, and model training pipelines are assembled using production-grade orchestration. We implement distributed training across GPU clusters, with automated checkpoint management and experiment tracking via Weights & Biases integration.
Sprint 3 — Inference Optimization
The trained model is distilled, quantized, and compiled for edge or cloud deployment. We benchmark latency at p50/p95/p99 under realistic load, and implement caching strategies that reduce inference costs by 40-70% without measurable accuracy degradation.
Sprint 4 — Monitoring & Drift Detection
We deploy model performance monitors that track prediction distribution shifts, feature drift, and latency anomalies in real time. Automated alerts trigger retraining pipelines when performance degrades below defined thresholds, creating a self-healing production system.
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3 weeks
5
Custom API Engine
from 4,200€
Contract-First API Design
We begin with OpenAPI 3.1 specifications, defining every endpoint, request/response schema, error taxonomy, and rate-limit policy before implementation. The contract is validated against your frontend needs and third-party integration requirements through collaborative schema review sessions.
Implementation & Orchestration Layer
The API is built with automatic request validation, structured error responses, and distributed tracing headers. We implement a service mesh layer for circuit breaking, retry policies, and load balancing across microservice instances, ensuring graceful degradation under partial failure.
Performance Hardening & Documentation
Load testing with realistic traffic patterns identifies bottlenecks in query planning, serialization overhead, and connection pooling. We produce interactive API documentation with runnable code samples in five languages, plus a Postman collection for immediate team onboarding.
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5 weeks
6
Interactive Ecosystem Unit
from 5,800€
Concept Prototyping Phase
We build three competing interactive prototypes exploring different gesture vocabularies, transition systems, and spatial navigation metaphors. Each prototype is user-tested with five participants from your target audience, and the winning concept is selected through empirical preference data rather than internal consensus.
Motion System Architecture
The chosen concept is decomposed into a reusable motion library: spring physics parameters, easing curves, choreography sequences, and interruption handling rules. Every animation is defined with a duration budget in milliseconds to ensure the total interaction choreography stays within perceptual comfort thresholds.
Production Integration & Accessibility
The motion system is integrated with your component library, with every interactive element supporting reduced-motion preferences, keyboard navigation, and screen reader announcements. We implement progressive enhancement layers so the core functionality works without JavaScript while the rich interactions enhance capable browsers.
Performance Budget Enforcement
A continuous performance budget system is deployed that tracks First Input Delay, Cumulative Layout Shift, and Total Blocking Time against defined thresholds. Automated CI checks prevent any component from merging if it violates the established performance contract.
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8 weeks
7
Autonomous Infrastructure Overhaul
from 12,000€
Week 1-2: State Assessment & Migration Blueprint
We conduct a full infrastructure census: every server, container, database replica, CDN edge node, and DNS record is documented with its current configuration, cost, and utilization metrics. The migration blueprint defines the target state architecture with redundancy layers, auto-scaling policies, and disaster recovery procedures.
Week 3-4: Containerization & Orchestration
Legacy workloads are containerized with multi-stage Docker builds optimized for layer caching and image size. We deploy Kubernetes clusters with namespace isolation, RBAC policies, and horizontal pod autoscalers calibrated to your traffic patterns. Service mesh networking is configured with mTLS encryption between all inter-service communication.
Week 5-6: Data Layer Reconfiguration
Database architectures are restructured with read replicas, connection pooling via PgBouncer, and automated failover with sub-second recovery. We implement tiered storage policies that automatically archive cold data to cost-optimized storage classes while keeping hot data within nanosecond reach of application servers.
Week 7-8: Observability & Self-Healing
A complete observability stack is deployed: distributed tracing via OpenTelemetry, log aggregation with structured JSON output, and metric dashboards with anomaly detection. Automated remediation playbooks handle the top 20 most common failure scenarios without human intervention, reducing mean time to recovery from hours to seconds.
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12 weeks
8
Full-Scale Turnkey Product Ecosystem
from 18,500€
Phase 1 — Strategic Foundation (Weeks 1-2)
Stakeholder interviews, competitive landscape mapping, and market positioning analysis feed into a product strategy document. We define the north-star metrics, user personas with validated behavioral hypotheses, and a prioritized feature roadmap with RICE scoring. Technical architecture decisions are locked with a formal decision record.
Phase 2 — Design System & Prototyping (Weeks 3-4)
A comprehensive design system is authored: color tokens, typography scales, spacing systems, component specifications with all state variants, and interaction choreography guides. High-fidelity prototypes are built in Figma with functional micro-interactions, tested against WCAG 2.2 AAA compliance standards.
Phase 3 — Core Development Sprint (Weeks 5-8)
Parallel frontend and backend development runs in two-week sprints with demo-ready increments. The frontend implements the design system as a component library with Storybook documentation. The backend delivers API endpoints with contract testing, database migrations with rollback safety, and background job processing with dead-letter queues.
Phase 4 — Integration & Hardening (Weeks 9-10)
End-to-end integration testing covers every critical user journey across three viewport sizes and two connection speeds. Security hardening includes dependency vulnerability scanning, OWASP Top 10 penetration testing, and secrets management via HashiCorp Vault. Load testing validates the system handles 10x peak traffic without degradation.
Phase 5 — Deployment & Handover (Weeks 11-12)
Zero-downtime deployment via blue-green strategy with automated canary analysis. Monitoring dashboards, runbooks, and incident response procedures are documented and transferred to your operations team. A two-week hypercare period follows launch with dedicated engineer availability for rapid issue resolution.
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16 weeks
9
Enterprise Neural Network Deployment
from 25,000€+
Phase 1 — Data Infrastructure & Pipeline Engineering (Weeks 1-3)
We architect a production data lake with schema evolution support, real-time streaming ingestion via Apache Kafka, and batch processing pipelines on Apache Spark. Data quality gates enforce completeness, freshness, and consistency constraints before any record reaches the training corpus. We implement feature stores with point-in-time correctness guarantees.
Phase 2 — Model Research & Development (Weeks 4-7)
A dedicated research team explores three to five model architectures in parallel: from classical gradient-boosted ensembles to large-scale transformer networks. Each candidate is evaluated against holdout datasets with statistical significance testing. The winning architecture undergoes ablation studies to understand feature importance and failure modes.
Phase 3 — Production Engineering (Weeks 8-11)
The production model is wrapped in a serving infrastructure with A/B testing capabilities, feature store integration, and real-time prediction caching. We implement model versioning with instant rollback, shadow deployment for risk-free validation, and multi-tenant inference serving with per-customer rate limiting and usage metering.
Phase 4 — Operations & Continuous Learning (Weeks 12-14)
MLOps pipelines are established: automated retraining triggers based on data drift detection, model performance regression alerts, and automated stakeholder reporting. We deploy canary model updates with automatic rollback if production metrics degrade, creating a system that improves continuously without manual intervention.
Phase 5 — Governance & Compliance (Weeks 15-16)
Model explainability reports are generated using SHAP values and attention visualization. Bias auditing covers protected attributes with statistical parity testing. Complete audit trails for every prediction are logged with retention policies aligned to your regulatory requirements. Documentation includes model cards, data sheets, and operational runbooks for the full lifecycle.
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Operational Workflow
Phase 01
Discovery & Mapping
We begin every engagement with a systematic audit of your existing architecture, user flows, and technical debt. This phase produces a comprehensive topology document that becomes the reference architecture for all subsequent work.
Phase 02
Strategic Architecture
With complete system visibility, we design the target-state architecture — selecting frameworks, defining data schemas, establishing API contracts, and mapping the critical path through the implementation with cost-adjusted timeline projections.
Phase 03
Precision Engineering
Implementation proceeds in two-week sprint increments with demo-ready deliverables at each gate. Automated testing, continuous integration, and performance budget enforcement ensure that velocity never compromises structural integrity.
Phase 04
Deployment & Handover
Zero-downtime deployment via blue-green strategy with automated canary analysis. We transfer operational ownership through documented runbooks, monitoring dashboards, and a dedicated hypercare period where our engineers remain on-call for rapid issue resolution.
Phase 05
Continuous Evolution
Post-launch, we establish observability pipelines with anomaly detection, automated retraining triggers for ML systems, and quarterly architecture reviews that ensure your infrastructure evolves with your business trajectory rather than behind it.
Performance Metrics
Quantified outcomes from our operational framework.
99.97%
Uptime SLA
Across all production deployments in the last 12 months, maintained through redundant infrastructure and automated failover protocols.
14d
Avg. Time-to-MVP
From project kickoff to first production deployment. Accelerated by our pre-built component libraries and standardized deployment pipelines.
3.2x
ROI Multiplier
Average return on investment measured at 6 months post-launch, calculated from conversion rate improvements and infrastructure cost optimization.
<180ms
P95 Response Time
Median p95 API response latency across our client portfolio, achieved through query optimization, edge caching, and connection pool tuning.