Embed intelligent AI assistants and automation into your existing product
LLM API Integration
Connect your application to Claude (Anthropic), GPT-4 (OpenAI), or Gemini via their official SDKs — with streaming responses, tool use, and structured outputs.
- Anthropic Claude API (claude-sonnet-4-6)
- OpenAI GPT-4o & Codex
- Streaming chat responses
- Function calling & tool use
Chatbots & AI Copilots
Custom AI assistants embedded in your website or app — trained on your content, answering user questions, and guiding them through your product.
- Context-aware multi-turn chat
- System prompt engineering
- Persona & tone customisation
- Fallback & escalation handling
RAG — Knowledge-Based AI
Retrieval-Augmented Generation systems that let the AI answer questions grounded in your own documents, knowledge base, or database.
- Document ingestion & chunking
- Vector embeddings (OpenAI / local)
- Semantic search with pgvector / Pinecone
- Grounded, citation-backed answers
Workflow Automation with AI
Automate repetitive tasks by chaining AI calls with business logic — email triage, content generation, data extraction, and more.
- Multi-step AI agent pipelines
- Structured data extraction
- Automated content generation
- Integration with n8n / Zapier / custom
FAQ
Frequently Asked Questions
Primarily Claude (Anthropic) and GPT-4 (OpenAI). I choose the model based on cost, capability, and the task — Claude excels at long context and reasoning, GPT-4o at multimodal tasks.
Yes — I can embed a fully customised AI chatbot into any web application via a React widget or server-rendered component, connecting to whichever LLM best fits your needs.
RAG (Retrieval-Augmented Generation) lets the AI answer questions based on your own documents rather than just its training data. You need it if your chatbot must be accurate about your specific products, policies, or knowledge base.
I implement prompt caching, select the right model tier for each task, stream responses to avoid timeouts, and set token limits — reducing cost without sacrificing quality.
Yes — using function calling / tool use, the AI can search your database, create records, send emails, or trigger any back-end action you define.
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