Artificial Intelligence
AI Integrations for Your Business
Web Systems integrates artificial intelligence directly into your company's real business processes — not as a standalone demo, but as part of your daily operation. We work with OpenAI and Anthropic models, as well as custom models trained on your own data, connected to your existing systems through autonomous agents and machine learning pipelines.
Why Choose This Solution
Custom autonomous agents
AI agents that execute complete tasks (answering inquiries, generating reports, classifying data) without constant supervision.
Integration with your systems
We connect AI to your CRM, ERP, ecommerce platform, or existing database — without replacing what already works.
In-house or third-party models
We use OpenAI/Anthropic when it makes sense, or train custom models on open weights to reduce cost and dependency.
ML pipelines in production
From text classification to predictive scoring, we take ML models into production with real monitoring.
Measurable ROI
Every AI integration is designed with clear metrics: hours saved, tickets resolved, conversions generated.
Frequently Asked Questions
What types of businesses can benefit from integrating AI?
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Any company with repetitive processes around support, data analysis, or content generation. We've implemented AI in ecommerce, CRM, technical support, and manufacturing.
Do you use ChatGPT or build your own models?
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Both. We use OpenAI and Anthropic APIs when that's the fastest, most cost-effective option, and we train custom models from open weights (Llama, Mistral, Qwen) when full control over data or long-term costs is needed.
How long does it take to implement an AI integration?
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It depends on the scope: a basic conversational agent can be in production in 2-4 weeks; a complex ML pipeline with custom training can take 2-3 months.
Does AI replace my team?
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No. We design it to eliminate repetitive, low-value tasks, freeing your team for strategic work. Human oversight remains in place for critical decisions.
What about the security of my data when using AI?
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We work with providers that don't train their models on your data (OpenAI/Anthropic enterprise mode), or with custom models hosted on your own infrastructure when confidentiality is critical.
What AI providers do you use besides OpenAI and Anthropic?
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We also work with open-weight models (Llama, Mistral, Qwen) and, depending on the case, Google Gemini or AWS Bedrock when the client already has infrastructure on that cloud.
How do you evaluate which model to use for each case?
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We evaluate cost per use, required latency, data sensitivity, and response quality on a benchmark built from your actual business data before selecting the final model.
What happens if the AI model makes a mistake?
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We design every integration with uncertainty handling: confidence thresholds, human validation for edge cases, and full logging to audit and correct errors.
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