ByteWave
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Artificial intelligence Specializations MVP for startups ERP and CRM systems API integrations and automation AI chatbots for business AI for business All services →
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Artificial intelligence

ByteWave implements AI in business: GPT/Claude chatbots serving customers 24/7, ML automation, predictive analytics, LLM integrations with RAG. Software house from Gdansk, Poland. POC in 2-3 weeks, pragmatic approach with real ROI.

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What we build

Solutions tailored to the business

01

Chatbots & AI assistants

Intelligent assistants serving customers, generating leads, and answering questions 24/7. Integration with company knowledge base, escalation to consultant when needed. GPT, Claude, custom models.

02

Process automation (ML)

Document classification, data extraction from invoices and contracts, sales predictions, anomaly detection. Machine learning tailored to specific business processes.

03

Predictive analytics

Dashboards with visualizations, predictive reports, early warning systems. Trend forecasting, customer segmentation, price optimization based on data.

04

LLM & RAG integrations

Language model deployments (GPT, Claude) with access to company knowledge base. Retrieval-Augmented Generation for precise answers. Fine-tuning for industry specifics.

Technologies

Tech stack that scales

Models & frameworks

OpenAI API (GPT)
Integration with GPT-4, GPT-4o, Whisper, DALL-E. Text generation, analysis, translations, embeddings.
Anthropic (Claude)
Safe language models with large context window. Document analysis, assistants, content moderation.
LangChain / LlamaIndex
Frameworks for building LLM applications: prompt chains, agents, RAG, conversation memory.
TensorFlow / PyTorch
Deep learning libraries for training custom models. Classification, NLP, computer vision, predictions.

AI Infrastructure

AWS / Azure AI
Managed services: SageMaker, Bedrock, Azure OpenAI. Scalable environment for training and inference.
Vector databases
Pinecone, Weaviate, pgvector. Storing embeddings for semantic search and RAG.
Docker / GPU
Model containerization, GPU acceleration for training and inference. Reproducible environments.
MLOps
CI/CD pipeline for ML models. Data versioning, drift monitoring, automatic retraining.

Data & integrations

Python / Pandas
Data processing and analysis. ETL, cleaning, transformations, feature engineering.
RAG (Retrieval-Augmented)
Combining LLM with company knowledge base. Precise answers based on current documents and data.
REST API / Webhooks
Integrating AI models with existing systems: CRM, ERP, e-commerce, helpdesk.
Monitoring & evaluation
Tracking response quality, token costs, latency. A/B testing prompts, feedback loop.
How we work

From idea to deployment

01

Discovery

Analysis of needs, business and technical requirements. We define goals and project scope.

02

Design

UX/UI design, system architecture, prototyping. We visualize the solution before coding.

03

Development

Iterative product building with regular demos. Agile, transparent process, constant contact.

04

Deployment

Testing, deployment, user training. Technical support and growth after launch.

Specializations

In-depth areas of this service

AI chatbots for business

Intelligent AI assistants serving customers 24/7 in multiple languages.

AI for business

ML and AI automation deployments delivering measurable ROI for businesses.
Frequently asked questions

Questions? We have answers

Most commonly: chatbot serving customers 24/7 (support cost reduction of 40-60%), automating repetitive tasks (invoices, documents, reports), predictive analytics (sales forecasting, churn). We start with process analysis to identify where AI gives the best ROI.

Chatbot with knowledge base integration starts from 4,000-7,000 EUR. ML automation system is 7,000-20,000 EUR. Complex predictive solutions are 12,000-35,000 EUR. Free consultation and quote within 48h.

Simple chatbot with RAG takes 3-6 weeks. ML automation system takes 2-4 months. Complex predictive solutions take 3-6 months. POC (Proof of Concept) delivered in 2-3 weeks.

Not always. Chatbots and LLM integrations work with existing knowledge bases (documents, FAQ, website). Machine learning requires historical data - we help collect, clean, and prepare it. We start with a data audit.

Yes. We use locally hosted or private cloud models when confidentiality is required. Data doesn't go to external services without consent. GDPR compliance, encryption, audit trail.

Have a project idea?

Let's talk about how we can make it happen.

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