AI Integration
Custom chatbots, automations, and AI tooling wired into your stack. Built, documented, and handed off so it doesn't become a black box.
AI is most of the conversation right now, and most of it is either hype or shallow demos. We've integrated streaming Claude chatbots into production sites, built automations that triage real customer support tickets, and wired LLMs into internal tools that save real hours. We build for production, not for demo day.
Deliverables
- A working AI feature in your product (chatbot, automation, content generator, classifier, whatever fits)
- Streaming responses with proper error handling, retries, and rate limiting
- System prompts and tool definitions in source control, not buried in a vendor dashboard
- Prompt caching, cost monitoring, and an actual budget cap so it doesn't surprise-bill you
- Documentation on the prompts, the model choices, and how to update them later without our help
- Optional fine-tuning if your use case actually needs it (most don't)
Process
- 01
Scope
Decide what the AI actually needs to do and where the human still belongs in the loop.
- 02
Prototype
Build a working prototype against your real data, before committing to a full production build.
- 03
Production
Wire it into your stack with proper streaming, error handling, cost monitoring, and observability.
- 04
Handoff
Source code, prompts, eval scripts, and a session on how to keep tuning it after we're gone.
Stack & Tools
- Anthropic Claude
- OpenAI GPT
- Google Gemini
- Vercel AI SDK
- LangChain
- Pinecone
- Postgres pgvector
- Resend
- Inngest
- Trigger.dev
Common questions
Claude, GPT, or Gemini?+
Depends on the use case. Claude is our default for coding, long-context document work, and any task where tone and judgment matter. GPT and Gemini are strong for other shapes of problem. We don't lock you into one provider.
What does an AI integration cost?+
A streaming chatbot wired into an existing site typically runs $5K to $15K to build, plus the API costs for the model itself (which we cap and monitor).
Will the AI hallucinate?+
If you ask it open-ended questions with no context, yes. We architect around that by giving the model your real data through retrieval, by structuring the prompts to limit scope, and by adding a human-review layer for anything high-stakes.
Can we fine-tune our own model?+
Sometimes. Most use cases are solved better and cheaper with prompt engineering and retrieval than with fine-tuning. We'll tell you honestly if fine-tuning would actually help your case.
What people search for
- AI integration agency
- Claude API integration
- OpenAI API integration
- ChatGPT integration
- AI chatbot development
- streaming chatbot
- Anthropic API
- AI customer service automation
- AI lead qualification
- AI workflow automation
- LangChain development
- RAG implementation
- vector database
- prompt engineering
- AI cost optimization
- prompt caching
- Toronto AI agency
- Canadian AI consulting
Ready to talk about your ai integration project?
Send us a short note. We respond within 24 hours and we'll tell you honestly whether this is the right engagement for what you're trying to do.