AI chatbots and LINE chatbots
Customer support, FAQ automation and appointment booking, for example a LINE chatbot that answers customer questions around the clock.
AI solutions development
AI solutions development that starts with your business problem, not a model
Vectorkub provides AI solutions development for businesses that want practical results: fewer repetitive tasks, faster answers for customers and decisions backed by data.
We start with your problem and how success will be measured, then choose the right approach. That might be a proven model such as GPT-4o or Claude connected to your own data with RAG, or a custom model trained for your specific use case.
01 / What we build
AI solutions we build
Every business can apply AI somewhere. These are the use cases where we see the clearest return.
Document processing and OCR
Extract data from invoices, receipts and forms, classify documents and send the results straight into your systems.
RAG knowledge bases
Assistants that answer from your own manuals, policies and product data using retrieval-augmented generation, with sources your team can check.
Semantic search and recommendations
Search that understands meaning rather than exact keywords, plus product recommendation engines for your store or app.
Computer vision
Image recognition, object detection and quality inspection, such as spotting defects on a manufacturing line.
Predictive analytics and custom models
Sales forecasting, demand prediction and risk analysis, or a custom-trained model for an industry-specific task.
02 / Technologies
Technologies we use
Leading language models where they fit, open-source frameworks where you need control, and vector search to ground answers in your data.
- GPT-4o
- Claude
- LangChain
- RAG
- Pinecone, Weaviate, Chroma
- Hugging Face
- PyTorch
- TensorFlow
03 / Process
Our AI development process
Four stages that keep the project tied to measurable results rather than experiments.
- 01
Understand
Define the problem, the people affected and the success metrics the solution has to hit.
- 02
Data preparation
Collect, clean and prepare your documents and data so the model has something reliable to learn from or search.
- 03
Build and train
Develop the solution, then fine-tune prompts, retrieval or model training until results meet the agreed metrics.
- 04
Deploy and monitor
Production deployment with monitoring, so accuracy and cost stay under control as usage grows.
04 / Pricing
AI pricing
AI projects start at 44,999 THB. The price depends on your requirements, data and integrations; typical timelines for each solution are below.
AI Chatbot
Customer support and FAQ automation on your website or LINE. Typical timeline: 3–6 weeks.
Custom quote
- LINE or web chat
- Answers from your FAQ and documents
- Appointment booking
- Hand-off to your team
Document Processing
OCR, data extraction and document classification. Typical timeline: 4–8 weeks.
Custom quote
- OCR for scans and photos
- Field extraction
- Document classification
- Export to your systems
Computer Vision
Image recognition and quality inspection. Typical timeline: 6–12 weeks.
Custom quote
- Image recognition
- Object detection
- Quality inspection
- Production monitoring
Custom AI Model
Prediction, analytics and custom training. Typical timeline: 8–16 weeks.
Custom quote
- Data preparation
- Model training and tuning
- Forecasting and analytics
- Deployment with monitoring
Prices exclude VAT. Every project starts with a free consultation and a fixed written quote.
FAQ
AI solutions FAQ
How much does an AI chatbot cost?
AI projects with Vectorkub start at 44,999 THB. A customer-support chatbot, including a LINE chatbot, usually takes 3–6 weeks; the final price depends on channels, data sources and integrations.
Can a chatbot answer from our own documents?
Yes. With retrieval-augmented generation (RAG), the chatbot searches your manuals, policies and product data in a vector database and answers from them, instead of relying on what the model happens to know.
Do we need a lot of data to get started?
Not always. Chatbots, OCR and semantic search can start with pre-trained models and your existing documents. Predictive analytics and custom models need historical data, which we assess during data preparation.
How do you keep our business data secure?
We agree up front which data the AI may use, encrypt data in transit, restrict access by role and choose models and hosting that fit your data policy.
How long does an AI project take?
An AI chatbot typically takes 3–6 weeks, document processing 4–8 weeks, computer vision 6–12 weeks and a custom AI model 8–16 weeks.
From the blog
Guides on this topic
7 min read
What Is RAG? A Business Guide to Retrieval-Augmented AI
RAG lets AI answer from your own documents instead of guesswork. Learn how it works, where it helps, its limits, and how to keep company data private.
Read the article7 min read
LINE Chatbot for Business: Use Cases, Costs and PDPA
A practical guide to building a LINE chatbot for business: use cases, how the Messaging API works, rule-based vs AI chatbots, rough costs and PDPA essentials.
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