AI Solutions
Scalable AI systems for business process automation — from intelligent database search to computer vision and predictive analytics.
Chat With Your Database
Semantic queries to SQL databases in any language — accurate results from MSSQL, PostgreSQL, MySQL.
SELECT p.name, SUM(o.revenue) AS total
FROM products p
JOIN orders o ON p.id = o.product_id
WHERE o.region = 'EU'
AND o.date BETWEEN '2025-10-01'
AND '2025-12-31'
GROUP BY p.name
ORDER BY total DESC
LIMIT 10;Based on Q4 2025 data, your top products in EU were: 1. ProductX ($2.4M), 2. ProductY ($1.8M)...
Show top 3 products by revenue in EU for Q4
Here are the top 3 products in EU for Q4 2025:
| # | Product | Revenue |
|---|---|---|
| 1 | Widget Pro | €2.4M |
| 2 | Sensor X | €1.8M |
| 3 | Module Z | €1.2M |
Text-to-SQL
Natural language to SQL conversion with 95%+ accuracy
Schema Context
Understanding database structure for complex queries
Optimization
Automatic query optimization and result formatting
Security
Audit trail and access control integration
Multi-platform
Support for MSSQL, PostgreSQL, MySQL, and more
How It Works
Natural Language
User sends a query in natural language.
SQLCoder / GPT-4o
AI models generate optimized SQL.
MSSQL / PostgreSQL
Query runs against your data platform.
Formatted Results
Results are returned in a readable format.
Enterprise-Grade Systems
Recommendation algorithms, semantic search in relational databases, predictive analytics based on historical data. Architecture for scalability and integration with existing infrastructure.
Fragmented Data
Business knowledge locked in databases, documents, spreadsheets — inaccessible for decision-making.
Manual Analysis
Hours on reports that AI generates in seconds.
Generic Recommendations
Suggestions without considering customer behavior and context.
Intuitive Purchasing
Ordering by gut feeling instead of demand forecasting.
Ineffective Search
Customers can't find products, employees can't find documents.
AI Capabilities
Proven solutions in production environments
Knowledge Systems & RAG
Vector databases, embeddings, and RAG for enterprise knowledge bases. Documents, wikis, databases → intelligent Q&A systems.
Recommendation Engines
Collaborative filtering, content-based algorithms, hybrid approaches, neural networks. Personalization that drives conversion.
Predictive Analytics
Sales forecasting, demand prediction, inventory optimization. ML models on your historical data with accuracy estimation.
Computer Vision
Product recognition, visual search, quality control. Photo → catalog search and recommendations.
Intelligent Automation
Auto-ordering based on logistics analytics. Inventory replenishment considering lead times, storage costs, and demand patterns.
LLM Integration
GPT-4o, Claude, Qwen, open-source models in your workflows. Prompt engineering, fine-tuning, custom solution development.
Data-Driven Personalization
E-commerce, content platforms, B2B marketplaces
Collaborative Filtering
Users who bought X also bought Y — classic but effective for large catalogs
Content-Based Filtering
Recommendations based on item attributes and user preferences
Matrix Factorization
SVD and ALS for discovering latent factors in user-item interactions
Neural Collaborative Filtering
Deep learning models that capture non-linear user-item relationships
Session-Based Recommendations
Real-time suggestions based on current browsing session
Hybrid Systems
Ensemble approaches combining multiple algorithms for optimal results
Multi-Armed Bandits
Balancing exploration and exploitation for continuous optimization
Forecasting & Analytics
Inventory, sales, logistics
Sales Forecasting
Predict revenue by product, region, and channel. Identify trends before competitors.
Demand Planning
Anticipate customer demand to optimize production and reduce stockouts.
Inventory Optimization
Automated reorder points based on lead times, storage costs, and demand forecasts.
Logistics Intelligence
Route optimization, delivery time prediction, and warehouse allocation.
Image Recognition & Analysis
Visual search, classification, quality control
Product Recognition
Customer photographs an item — system identifies it and finds matches in your catalog
Visual Search
Search by image instead of keywords. Find similar products, colors, styles.
Automated Recommendations
Based on visual similarity, suggest complementary products and alternatives
Quality Control
Automated defect detection in manufacturing
Technology Stack
Enterprise-grade AI infrastructure
Use Cases
Industries and business processes
E-commerce Personalization
Recommendation systems that boost conversion by 15-30%. Personalized offers based on user behavior patterns.
Enterprise Knowledge Bases
RAG systems for instant access to documentation, policies, and procedures. Reduce search time from hours to seconds.
Demand Forecasting
ML models for predicting sales, seasonality, and trends. 85-95% forecast accuracy on 3-6 month horizons.
Visual Search
Product search by photo. Customer takes a picture — system finds matches in your catalog in milliseconds.
Inventory Optimization
Automated reorder point management. Reduce excess inventory by 20-40%, minimize stockouts.
Support Automation
AI agents handling up to 70% of routine inquiries. CRM integration, automatic routing of complex cases.
Document Intelligence
Automatic classification, data extraction, and report generation. Process thousands of documents in minutes.
Logistics Optimization
Routing algorithms, delivery time prediction, optimal warehouse allocation. 10-25% logistics cost savings.
Implementation
Result-focused methodology
Discovery
- Data audit and quality assessment
- Use case prioritization by ROI
- Model selection and architecture
- Success metrics definition
Development
- Data pipeline construction
- Model training and fine-tuning
- API development and integration
- Accuracy validation and testing
Deployment
- Production infrastructure setup
- Monitoring and alerting
- A/B testing framework
- Continuous improvement loop
Ready to implement?
From semantic search to computer vision — production solutions in weeks
Discuss Your AI Project