Selected Works

Case
Studies

Real-world AI + Data solutions. From concept to production — we transform complex challenges into intelligent systems.

01

Reputation Manager

ClientHospitality

01_The Challenge

Client needed to process thousands of user reviews across multiple platforms daily. Manual review analysis was slow, inconsistent, and failed to identify actionable patterns for product improvement.

02_Key Outcomes

  • 70% reduction in review processing time
  • 35% increase in customer satisfaction
  • Real-time sentiment analysis across platforms
TypeScriptNext.jsPythonOpenAISupabasePostgreSQL

Technical_Architecture_V.04

We developed an intelligent system that collects user reviews from various platforms in real-time, analyzes sentiment and key themes using advanced NLP algorithms, automatically classifies reviews by priority, generates personalized responses using RAG technologies, and provides analytical reports for product improvement.
02

CoFinance AI Platform

ClientCOFINANCE_LEGAL

01_The Challenge

Legal and compliance professionals spent excessive time on manual document analysis and legal research, often missing critical details in complex documentation and struggling to keep up with regulatory changes.

02_Key Outcomes

  • 60% faster legal research processes
  • 45% improvement in compliance analysis accuracy
  • Real-time regulatory updates integration
TypeScriptNext.jsLangChainPineconeClaude APIPostgreSQL

Technical_Architecture_V.04

We built an AI-powered research and document analysis platform featuring semantic search tailored for legal language, automatic extraction of key definitions and entities, real-time highlighting of legal terms, document structure visualization, intelligent legal notepad with case law suggestions, and comparative analysis tools across jurisdictions.
03

Sensey AI Platform

ClientSENSEY

01_The Challenge

Businesses lacked visibility into competitor activities and market trends, resulting in slow response to market changes and missed strategic opportunities. Data was scattered across 90+ sources with no unified intelligence layer.

02_Key Outcomes

  • 65% faster response to market changes
  • 50% more effective competitive positioning
  • Predictive analytics for trend forecasting
TypeScriptNext.jsPythonTipTapSupabaseRedis

Technical_Architecture_V.04

We delivered an AI-powered competitive intelligence platform with multi-layered data collection from 90+ sources, ML-powered data processing with NLP and predictive analytics, real-time competitor tracking and alerts, PESTLE framework market analysis, custom report generation, and seamless integration with existing CRM and analytics tools.
04

Sync Hub

ClientTravel Tech

01_The Challenge

Hotels managing multiple OTA channels faced critical synchronization challenges — manual updates led to overbookings, rate inconsistencies, and missed reservations. Data scattered across systems with no unified translation layer between PMS (UUID-based) and OTAs (integer ID-based) created operational chaos.

02_Key Outcomes

  • Real-time bidirectional sync with multiple OTAs
  • 90-95% reduction in database load via caching
  • Zero duplicate bookings with idempotent processing
GoEncore.devPostgreSQLRedisKafkaREST APIs

Technical_Architecture_V.04

We built an event-driven integration hub connecting Property Management Systems with multiple OTAs (Ostrovok, Yandex Travel). The modular monolith on Encore.dev (Go) handles bidirectional sync: OTA→PMS booking webhooks and PMS→OTA availability/rates via Kafka. Features multi-tier Redis caching (90-95% DB load reduction), circuit breakers for resilient API communication, and idempotent event processing with SHA-256 deduplication.
05

Fraud Shield

ClientFinTech

01_The Challenge

Financial institutions faced growing fraud risks with manual document verification — slow processing, human errors, and inconsistent validation of receipts and bank transfers. Fraudulent documents slipped through traditional checks, causing significant financial losses and compliance violations.

02_Key Outcomes

  • Sub-second document verification and data extraction
  • 99.2% accuracy in payment detail recognition
  • Automated fraud pattern detection across transactions
TypeScriptTrigger.devSupabaseMistral AILlamaParseREST API

Technical_Architecture_V.04

We developed an automated document verification API with multi-provider OCR and intelligent fallback system for fraud prevention. The pipeline processes receipts and bank transfers in real-time: validates image quality (DPI, format, size), extracts structured data (amounts, card numbers, phone numbers, account details) using Mistral AI Vision with regex pattern matching fallback, and flags suspicious anomalies. Webhook notifications enable instant fraud alerts integration.

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