Start with the decision or workflow.
We map the economics, users, exceptions, regulations, and operational reality before choosing models or architecture.
Success stories · custom AI delivery
Their problem.
A solution built for it.
Some challenges need a head start from Carbon. Others need a clean-sheet architecture. CROZ does both. These references show our ability to understand a specific business problem, design the right AI system, integrate it, and keep it working in production.
Custom is still
a core capability.
Carbon helps when the pattern is reusable. It does not limit the solution space. When the advantage depends on unique data, economics, decisions, or customer experience, we design around that uniqueness.
Our custom-delivery promise
We do not arrive with the answer. We arrive with the capability to build it.
Build every layer the outcome needs.
Data pipelines, ML, agents, integrations, user experience, platform, security, evaluation, and operating tooling are part of one solution.
Stay after the interesting demo.
We deploy, observe, tune, operate, and improve the system with the client because real value begins where the presentation ends.
Hard problems.
Specific answers.
Each reference is presented as a business challenge, what CROZ designed and delivered, and what changed.
Fraud & risk 
Production · live since Nov 2024
Real-time fraud detection
A custom streaming ML platform that scores every payment in under 40 ms, catching more fraud while blocking fewer legitimate customers.
+29%more fraud caught
-23%false positives
<40msp99 latency
99.9%on-time scoring
The challenge
Reactive rules, thin feature sets, slow model iteration, and too many false positives at payment-network scale.
What CROZ delivered
A distributed streaming architecture, 200+ engineered features over nine months of history, real-time scoring, and automated MLOps with decision-level monitoring.
Reliable operations 
Production
AIOps at national scale
ML-driven anomaly detection across a hybrid infrastructure serving more than three million customers.
6xfaster resolution
~50models in production
30sfeature window
3M+customers in scope
The challenge
Manual threshold tuning across many systems, reactive incident response, and subtle anomalies hidden in normal-looking trends.
What CROZ delivered
A time-series feature store, roughly 50 continuously learning anomaly models, automated MLOps, and dashboards designed for SRE investigation.
Document & knowledge 
Production
Privacy-safe data for testing and analytics
A five-stage anonymization pipeline that removes or masks personal data while preserving its analytical value.
- Safe test data for development and QA
- Lower breach blast radius
- Faster internal and partner data sharing
The challenge
GDPR and sector rules blocked the use of real data for development, QA, analytics, and partner collaboration.
What CROZ delivered
Classification and named-entity recognition, configurable masking and synthetic substitution, differential privacy where statistics must survive, and AI verification for residual leakage.
Conversational AI 
Production
Customer support grounded in policy
An AI assistant for travel-insurance claims and policy questions, connected to business APIs and designed for clean human handoff.
- Repetitive questions deflected
- Consistent policy-grounded answers
- Human agents focused on complex cases
The challenge
High volumes of repetitive questions, slow responses, and inconsistency across policy-heavy customer interactions.
What CROZ delivered
A policy-grounded assistant, claims and customer API integration, guardrails against invented policy, and escalation to people for complex cases.
Agentic solutions
Pilot
Agentic profitability optimization
A custom multi-agent system that runs merchant pricing scenarios and surfaces optimization plays at a scale account managers cannot reach manually.
+3.5%profitability on segment
€200kannualized pilot
€1.5Mprojected full scale
The challenge
Hidden margin leakage across a large merchant portfolio, manual pricing, and too little account-manager capacity for smaller segments.
What CROZ delivered
Per-merchant analytical profiles, an orchestrator with cost and scenario tools, and a conversational interface for account managers and leadership.
The pattern library
keeps growing.
Some engagements reuse Carbon capabilities. Others contribute new engineering patterns that may become tomorrow’s acceleration assets.
Document understanding at scale
A multi-tenant knowledge platform that turns regulations, contracts, manuals, and schemas into searchable, agent-ready knowledge with citations down to source and page.
Intelligent document processing
Preset-driven extraction across many document types, enriched from ERP and CRM master data, with confidence-based routing between automated export and human review.
Agentic fraud analysis assistant
An orchestrator and specialized agents bring transaction, customer, merchant, and case data together so analysts move faster from question to documented insight.
Call center analyzer and voice assistant
Multi-language transcription and LLM analysis across every call for sentiment, compliance, topics, quality scoring, and trend discovery.
One team from ambiguity
to operation.
The disciplines stay connected so the solution does not fall into the gaps between strategy, data science, software delivery, platform, and operations.
Understand the problem, process, data, economics, constraints, and people.
Shape the experience, model approach, architecture, controls, and measurement.
Build iteratively against real workflows, integrate, test, and deploy.
Observe behavior and value, retrain or tune, support users, and improve.
That is the point.
Bring the problem that does not fit a product category. We will use these references as evidence of capability, then design around the reality of your business.
Discuss a custom solution