I will setup ai voice agent ai chatbot on langchain langflow vertex ai flowish


Over deze dienst
You've got data and a clear use case, but stitching models, vector stores, tools, memory, and UI into a reliable agent is messy. Prototypes break, prompts drift, and latency/quality trade-offs kill adoption.
I design robust AI agents and chat apps using LangChain / LangFlow / Flowise with Llama 3 or Vertex AI models, plus retrieval, tools, and guardrails. You'll get a clear architecture, reproducible configs, and a deployment that your team can operate.
What I'll Do
- Use-case design & architecture (diagrams + data flow)
- RAG pipeline (chunking strategy, embeddings, vector DB: Pinecone/FAISS/Qdrant)
- Tool-using agents (web/search APIs, Zapier/tools, function/Tool calls)
- Voice agent (Twilio/WebRTC, barge-in; call flows)
- LangFlow / Flowise graphs (visual chains, versioned nodes, prompt management)
- Model selection & prompting (Llama 3, Vertex AI/Gemini, OpenAIper your infra)
- Memory & safety
- Eval & metrics
- Deployments + docs & handover Loom
Tell me your use case (support agent, internal search, data copilot, voice IVR) + data sources. I'll reply with a brief plan and the right package.
Maak kennis met Mike M
- Afkomstig uitVerenigd Koninkrijk
- Lid sindsaug 2025
Talen
Engels, Frans
Veelgestelde vragen
Can you work with our existing data stack?
Yes—CSV/JSON, Google Drive, Notion/Confluence, Postgres, BigQuery, S3, etc.
Which model do you recommend?
Depends on constraints (cost, latency, tone, safety). I commonly use Llama 3 or Vertex AI (Gemini) and can switch behind the same interface.
