GPT-4 & ClaudeLLM & ML

Artificial Intelligence — your competitive advantage

We integrate AI into your business processes. Smart assistants, document analysis, predictive analytics — OpenAI and Claude technologies at your service.

Discuss AI ImplementationUse Cases

Sound Familiar?

AI solves these tasks better and cheaper than people

Routine Tasks

Employees spend hours answering typical questions, processing documents, compiling reports

Expert Shortage

Expensive specialists are busy with routine instead of strategic tasks

Information Loss

Knowledge is scattered across documents, chats, employees' heads — finding what you need is impossible

Missed Opportunities

Data exists, but there's no time and tools for analysis and insight extraction

Slow Support

Customers wait hours for responses, and nights and weekends support is unavailable

No Personalization

All customers get the same experience, even though personalization data exists

What AI Gives Your Business

Specific solutions we implement

AI Assistants 24/7

Smart bots answer questions, help with choices, process requests. Instantly, without days off, in any language

Smart Document Processing

AI extracts data from contracts, invoices, resumes. Classifies, summarizes, finds anomalies

Semantic Search

Search by meaning, not words. Finds relevant content in knowledge base, documents, correspondence

Predictive Analytics

Demand forecasting, customer churn, risks. Make decisions based on data, not intuition

Content Generation

Automatic creation of product descriptions, review responses, marketing texts in your style

Computer Vision

Product, defect, face, document recognition. Visual control automation

Use Cases

Standard solutions with proven ROI

Smart Support

Chatbot that understands context, remembers history, resolves 80% of questions without human

  • 80% questions without operator
  • Response in 2 seconds
  • 24/7/365 operation
  • Any languages

Document Processing

Data extraction from PDF, scans, photos. Form filling, compliance checking

  • 95% OCR accuracy
  • -90% manual work
  • Verification in seconds
  • CRM integration

Enterprise Search

Search across all sources: documents, email, Slack, Confluence. Answers to knowledge base questions

  • Semantic search
  • Question answering
  • Relevance ranking
  • Access rights support

Business Analytics

Sales forecasts, trend analysis, anomaly detection, pricing recommendations

  • Demand forecast
  • Churn analysis
  • Customer segmentation
  • Dynamic pricing

Content & Marketing

Description generation, newsletter personalization, A/B text tests, review analysis

  • Product descriptions
  • Email personalization
  • Sentiment analysis
  • SEO optimization

Visual Control

Product quality inspection, defect recognition, security control

  • 99% accuracy
  • Real-time
  • Line integration
  • Reports & alerts

Technologies

We use the best models and frameworks

OpenAI GPT-4(LLM)
Claude(LLM)
LLaMA(Open Source)
Mistral(Open Source)
LangChain(Framework)
LlamaIndex(RAG)
Pinecone(Vector DB)
Weaviate(Vector DB)
Hugging Face(ML)
PyTorch(ML)
FastAPI(Backend)
Python(Language)

How We Implement AI

From idea to production in 2-3 months

01

Audit & Strategy

1-2 weeks

We analyze processes, find AI application points with maximum ROI. Create implementation roadmap.

Process mapROI assessmentModel selectionRoadmap
02

Proof of Concept

2-4 weeks

We create a working prototype on real data. Prove value before full-scale implementation.

Working prototypeQuality metricsCost estimateGo/No-Go decision
03

Development & Integration

4-8 weeks

We develop production solution. Integrate with your systems. Set up monitoring.

Production APIIntegrationsMonitoringDocumentation
04

Optimization

Ongoing

Model fine-tuning on your data, quality improvement, expanding use cases.

Fine-tuned modelsMetrics improvementNew scenariosTeam training

Typical Results

80%
Support automation
10x
Processing acceleration
95%
Recognition accuracy
< 2 sec
AI response time

AI Implementation Cost

Proof of Concept — from 5,000 CHF. Production solution — from 15,000 CHF. Cost depends on integration complexity and data volume. Plus model API costs (typically $100-500/month).

Get Estimate

Frequently Asked Questions

Which model to choose: GPT-4, Claude or open-source?

GPT-4 — best choice for complex tasks and multilingual communication. Claude — excellent for long document analysis. Open-source (LLaMA, Mistral) — when data privacy matters or fine-tuning is needed. We often use combinations: open-source for simple tasks, GPT-4 for complex ones.

How to ensure data security when using AI?

Multiple protection layers: using APIs with privacy guarantees (data not used for training), deploying open-source models on your infrastructure, data anonymization before sending, encryption in transit and at rest.

How much data is needed for AI training?

For RAG (document search) — your existing documents are enough. For fine-tuning you need 100-1000 quality labeled examples. For training from scratch — millions of examples. In 90% of cases RAG + prompt engineering is sufficient.

Will AI hallucinate and give wrong answers?

Risk exists, but we minimize it: RAG ties answers to your documents, we tune model temperature, add fact checks, show sources. For critical scenarios we add human in the loop.

Ready to Implement AI?

Tell us about your processes — we'll find AI application points with maximum ROI

Discuss Project