Website AI assistant
answers using your services, prices, cases and FAQ
CoreLab / AI integrations
AI integration services for business: AI assistants, ChatGPT integration, RAG knowledge search, CRM summaries, content generation and workflow automation.

We integrate AI into existing business systems: websites, web apps, CRM platforms, support workflows, internal knowledge bases and mobile applications. The goal is practical automation, not a standalone chatbot with no business context.
Decision signals
answers using your services, prices, cases and FAQ
retrieves answers from documents, policies and internal notes
summarizes leads, classifies requests and drafts replies
generates drafts for listings, emails, articles and support messages
How we work
01 / Architecture
We use a backend-mediated integration so the frontend never exposes model keys or unrestricted access to private context.
OpenAI, Anthropic, Gemini or compatible APIs
retrieval from documents, pages or structured data
usage limits, logs and cost monitoring
human fallback for risky or uncertain actions
02 / Quality
The assistant should know the service scope, pricing, limitations and next steps. We prepare the knowledge source and test prompts before launch.
service knowledge and FAQ preparation
prompt and system instruction design
answer evaluation on real user questions
improvement loop based on logs
03 / Integration
A good AI assistant can collect a lead, summarize it, send it to the CRM, notify a manager and preserve the conversation context.
lead forms and CRM handoff
Telegram, email or Slack notifications
admin tools for editing knowledge
analytics for conversion and unanswered questions
Good fit
Start with one workflow where AI can save time or improve conversion: support answers, lead qualification, CRM summaries or internal knowledge search.
you have repeat questions from customers or managers
you have documents or service pages AI can use as context
you need AI connected to forms, CRM or notifications
you want cost and quality controls from day one
FAQ
Yes. We usually add a backend proxy, knowledge source, prompt controls, logs and lead handoff instead of placing a raw model call in the frontend.
Most business use cases do not require fine-tuning. Retrieval augmented generation is usually enough: the model receives relevant context from your data and answers using it.
Yes, if access is designed carefully. We can restrict what the model sees, log requests and keep sensitive actions behind explicit user confirmation.
Project brief
Tell us what data AI should use, where the answer should appear and what should happen after the answer.
Timeline
from 2 weeks
Budget
from $2,000