Cases
Straight to the point: context → risk → solution → impact. NDA-safe where needed.
Auto auction platform + mobile notifications
Reliable communications and response speed: service support and notification app.
- —Platform where notification speed is critical for clients.
- —Dependence on unstable channels and communication delays.
- —Support and development of web service (Django + Next.js).
- —Cross-platform iOS/Android app (React Native) with push scenarios.
- —Reliable notifications and scenario control.
- —Improved client experience and operational speed.
Chat bot & mini-app: data collection and marketing measurability
Automation of scenarios, contact collection, transparency of sources and conversions.
- —Need to collect data from packaging (QR) and understand channel effectiveness.
- —Marketing without measurability and loss of source data.
- —Bot on n8n + notification and reminder scenarios.
- —Mini-app for extended profile.
- —UTM tracking and click proxying.
- —Automated data collection.
- —Channel transparency and controlled effectiveness.
Voice-to-spec: transcription and structuring
Concept: voice → spec draft to accelerate start and lower client barrier.
- —Client finds it easier to dictate ideas than write a document.
- —Loss of requirements and chaos in task setting.
- —Transcription + structuring and initial decomposition.
- —Fast and clear start of requirement discussion.
R&D / internal product.
Data platform: ingestion → management → metadata
Platform layer for collecting, managing, and preparing data for BI/AI.
- —Disparate sources and need for standardized data delivery.
- —‘Manual’ integrations, data inconsistency, rising change costs.
- —Connectors and primary data delivery layer.
- —Management interfaces and change control.
- —Metadata and governance layer.
- —Unified predictable data layer.
- —Higher quality, lower change cost.
BI product: visualizations from task descriptions
Product prototype: business describes a task — system suggests visual answers.
- —Need to bring analytics closer to business language.
- —High BI entry barrier and long ‘question → answer’ cycle.
- —App + metadata layer + visualization generation.
- —Faster management answers.
Concept can be shown as a direction.
Elderly care monitoring: AI event detection and alerts
System where reliability, privacy, and timely response matter.
- —Need to detect incidents and notify caregivers.
- —False positives or missed events.
- —Detection layer + alerts and scenario quality control.
- —Stable event response while preserving privacy.
BI for agency: load, actual/plan, forecast
Resource management by numbers: hours, departments, load forecast.
- —Management needs to understand current and future load.
- —Wrong hiring and sales decisions due to lack of transparency.
- —Metric model + BI layer for management questions.
- —Resource decisions became predictable and justified.
BI rollouts across different industries
Experience building management analytics in companies of various profiles.
- —Different sources, roles, and access requirements.
- —‘Raw’ dashboards without data trust.
- —Semantics, marts, quality control, governance.
- —Unified metrics and daily management value.
Phrased without revealing sensitive details.
Arbitrage engine: real-time signals and decisions
Infrastructure and calculations in real time, where latency and control matter.
- —Trading logic requires real-time and reliable calculations.
- —Calculation errors and delays — direct financial risk.
- —Streaming calculations, signaling, latency control and logging.
- —Predictable real-time decision system.
Global macro on currencies: factors and regular updates
Research layer: data collection, factor structuring, reporting.
- —Need to regularly update factor picture for FX.
- —Decisions without up-to-date factor structure and evidence.
- —Data collection, factor framework, regular updates.
- —Transparent analytical base for strategies.
R&D / internal layer.