AI Agents
AI agents designed around defined responsibilities, business rules, approval gates and measurable outcomes — not generic chat interfaces.
- Agent workflows
- Human approval gates
- Model routing
- Knowledge systems
Independent AI product studio Denmark
AI systems built for real operations.
NorthScope AI designs and builds applied AI products, automation platforms and digital systems that connect business logic, data and measurable outcomes.
AI Engineering · Product Development ·Automation · Business Intelligence
What NorthScope does
We turn complex business operations into clear, intelligent systems.
From early product architecture to working integrations, NorthScope combines domain knowledge, software engineering and applied AI to build systems that can be tested, measured and improved.
Capabilities
From operational problem to working product.
Automation Platforms
Operational workflows that connect channels, APIs, databases and human decisions into one reliable execution layer.
- Workflow orchestration
- API integrations
- Event processing
- Notifications and follow-up
Data & Business Intelligence
Attribution, performance visibility and learning loops that show what happened, why it happened and what should happen next.
- Source attribution
- Operational dashboards
- Experiment tracking
- Profit and loss visibility
Digital Products
Focused web products, internal tools and customer experiences designed from business logic through production implementation.
- Product architecture
- UX and interaction
- Full-stack development
- Production foundations
Selected systems
Built around real domains, constraints and integrations.
A focused portfolio of operational products, platform foundations and ongoing research. Select a system to examine its context and technical direction.
01Applied AI · Gmail · AutomationInbox PilotWorking prototype · Real Gmail tested
A read-only AI attention layer for Gmail that identifies the few emails requiring decisions or action while filtering routine inbox noise.
Initial proof43 real inbox emails · 3 surfaced for attention · 93% removed from the primary attention queueInitial live AI triage result · human validation in progress
Operational intent
Inbox Pilot reduces the volume competing for attention without letting AI make commitments, send messages or change the mailbox.
Founder contribution
- Product principle and decision boundary
- Read-only Gmail and Calendar integration
- Structured AI triage pipeline
- Deterministic safety validation
- Privacy-safe observability
- Live integration and regression testing
Technical foundation
- Next.js
- Gemini
- Google AI Studio
- Gmail API · read-only
- Calendar API · read-only
- Codex
- Runtime schema validation
- Human review
02Insurance · AI agents · AutomationInsurance Distribution AIActive pilot
An AI-assisted insurance acquisition and servicing system connecting customer journeys, insurer integrations, operational workflows and post-purchase retention.
Operational intent
The system is designed to reduce fragmented manual handling across lead capture, quotation, purchase support, payment-status follow-up and customer retention.
Founder contribution
- Product strategy and system architecture
- Insurance domain logic
- Customer journey design
- AI agent workflow design
- API integration planning
- Attribution and retention model
Technical foundation
- Next.js
- NestJS
- PostgreSQL
- Prisma
- n8n
- Telegram Mini Apps
- External insurance APIs
- AI provider routing
03Insurance · Marketplace · Partner integrationMulti-Carrier Insurance MarketplacePartner integration
A multi-brand insurance comparison and assisted-purchase environment developed around integration with an established Ukrainian insurance marketplace.
Operational intent
The product extends a single customer journey across multiple insurance brands while preserving structured comparison, assistance and operational automation.
Founder contribution
- Marketplace product concept
- Insurance distribution architecture
- Multi-carrier journey design
- Partner API integration planning
- Automated assistance model
- Reuse of the core insurance platform
Technical foundation
- Reusable insurance core
- Partner APIs
- Telegram Mini App
- Product comparison flows
- Workflow automation
- Customer event tracking
04Growth infrastructure · Attribution · AI operationsMarketCore AICore platform in development
An AI-native operating layer for campaigns, sources, leads, experiments, commercial outcomes and continuous learning.
Operational intent
MarketCore is designed to connect acquisition activity with real operational and financial outcomes, allowing evidence — rather than isolated metrics — to guide the next action.
Founder contribution
- Product vision
- Core Sales Loop design
- Attribution architecture
- Agent responsibility model
- Approval-gate design
- Multi-provider AI evaluation concept
- Owner operating model
Technical foundation
- Web administration
- Backend APIs
- PostgreSQL
- Event model
- Workflow orchestration
- AI model routing
- Channel connectors
- Experiment tracking
05Research · Autonomy · SimulationAutonomous Systems LabExploratory R&D
Research and prototyping for reusable autonomy software, simulation workflows and task-oriented control interfaces.
Operational intent
The research explores how autonomous capabilities can be separated from a single hardware platform and applied to practical, repeatable field tasks.
Founder contribution
- Product and platform concept
- Use-case definition
- Modular autonomy strategy
- Simulation-first development direction
- End-user control concept
- Partnership exploration
Technical foundation
- PX4
- ROS 2
- Simulation environments
- Modular SDK concepts
- Mission workflows
- Operator interfaces
Approach
Start with the operation. Build only what can become real.
- 01
Discover
Understand the business process, economic objective, users, constraints and existing systems.
- 02
Design
Translate the operation into journeys, responsibilities, data, decisions and system boundaries.
- 03
Build
Create the smallest production-compatible vertical slice that proves the complete flow.
- 04
Measure
Capture operational events, attribution, quality signals and commercial outcomes from the beginning.
- 05
Improve
Use measured evidence to refine workflows, agent behaviour, product decisions and model selection.
Principles
Built for trust, not theatre.
Practical intelligence
AI must improve a real decision, action or outcome.
Production-compatible foundations
Early versions should evolve into the real system instead of becoming disposable prototypes.
Human control where it matters
Owners approve financial, public and high-impact decisions.
Evidence before automation at scale
The system should learn from measured results, not assumptions.
Domain knowledge as infrastructure
Industry rules and operational experience are part of the product architecture.
Founder
Business experience translated into working systems.
DENMARKPRODUCT / SYSTEMS
NorthScope AI was founded by Demyd Sudarenko, a product builder with more than fifteen years of experience across insurance, banking, operations and business development.
His work focuses on translating complex commercial rules and operational processes into practical digital products — combining domain expertise, product thinking, automation and software architecture.
Based in Denmark, Demyd is currently building applied AI systems for insurance distribution, growth operations and autonomous workflows while continuing to deepen his full-stack engineering practice.
- Insurance distribution and operations
- Product and business architecture
- AI agent and workflow design
- API-based automation
- Attribution and growth systems
- Full-stack product development
Demyd Sudarenko · Founder and Product Builder
Start a conversation
Have an operation that should work better?
NorthScope AI is open to selected product work, implementation partnerships, technical collaboration and relevant professional opportunities.
[email protected]