Scalable AI systems for business process automation — from intelligent database search to computer vision and predictive analytics.
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 |
Natural language to SQL conversion with 95%+ accuracy
Understanding database structure for complex queries
Automatic query optimization and result formatting
Audit trail and access control integration
Support for MSSQL, PostgreSQL, MySQL, and more
User sends a query in natural language.
AI models generate optimized SQL.
Query runs against your data platform.
Results are returned in a readable format.
Recommendation algorithms, semantic search in relational databases, predictive analytics based on historical data. Architecture for scalability and integration with existing infrastructure.
Business knowledge locked in databases, documents, spreadsheets — inaccessible for decision-making.
Hours on reports that AI generates in seconds.
Suggestions without considering customer behavior and context.
Ordering by gut feeling instead of demand forecasting.
Customers can't find products, employees can't find documents.
Proven solutions in production environments
Vector databases, embeddings, and RAG for enterprise knowledge bases. Documents, wikis, databases → intelligent Q&A systems.
Collaborative filtering, content-based algorithms, hybrid approaches, neural networks. Personalization that drives conversion.
Sales forecasting, demand prediction, inventory optimization. ML models on your historical data with accuracy estimation.
Product recognition, visual search, quality control. Photo → catalog search and recommendations.
Auto-ordering based on logistics analytics. Inventory replenishment considering lead times, storage costs, and demand patterns.
GPT-4o, Claude, Qwen, open-source models in your workflows. Prompt engineering, fine-tuning, custom solution development.
E-commerce, content platforms, B2B marketplaces
Users who bought X also bought Y — classic but effective for large catalogs
Recommendations based on item attributes and user preferences
SVD and ALS for discovering latent factors in user-item interactions
Deep learning models that capture non-linear user-item relationships
Real-time suggestions based on current browsing session
Ensemble approaches combining multiple algorithms for optimal results
Balancing exploration and exploitation for continuous optimization
Inventory, sales, logistics
Predict revenue by product, region, and channel. Identify trends before competitors.
Anticipate customer demand to optimize production and reduce stockouts.
Automated reorder points based on lead times, storage costs, and demand forecasts.
Route optimization, delivery time prediction, and warehouse allocation.
Visual search, classification, quality control
Customer photographs an item — system identifies it and finds matches in your catalog
Search by image instead of keywords. Find similar products, colors, styles.
Based on visual similarity, suggest complementary products and alternatives
Automated defect detection in manufacturing
Enterprise-grade AI infrastructure
Industries and business processes
Recommendation systems that boost conversion by 15-30%. Personalized offers based on user behavior patterns.
RAG systems for instant access to documentation, policies, and procedures. Reduce search time from hours to seconds.
ML models for predicting sales, seasonality, and trends. 85-95% forecast accuracy on 3-6 month horizons.
Product search by photo. Customer takes a picture — system finds matches in your catalog in milliseconds.
Automated reorder point management. Reduce excess inventory by 20-40%, minimize stockouts.
AI agents handling up to 70% of routine inquiries. CRM integration, automatic routing of complex cases.
Automatic classification, data extraction, and report generation. Process thousands of documents in minutes.
Routing algorithms, delivery time prediction, optimal warehouse allocation. 10-25% logistics cost savings.
Result-focused methodology
From semantic search to computer vision — production solutions in weeks
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