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AI Automation

AI Automation & Integration

RAG, chat and voice agents, workflow automation and AI built into the systems you already run

I put AI to work inside real products and workflows: RAG systems that answer from your own data, chat and voice agents that talk to your customers, calling pipelines, and automations that remove repetitive work. I deploy models, connect them to the tools you already use, and when a new AI tool or API comes out, I can integrate it into your stack quickly. This is the work I do every day.

Start a projectSee related work
Typical timeline
1-8 weeks
Ideal for
Startups, SaaS Products, Customer Support, Sales Teams
  • OpenAI
  • Anthropic
  • Gemini
  • OpenRouter
  • LangChain
  • LangGraph
  • n8n
  • Pinecone
  • Qdrant
  • PGVector
  • Retell
  • LiveKit
  • Mem0
  • Langfuse
  • Supabase
  • Exa API
  • Apify
  • OpenClaw
  • Hermes Agent

What's included

AI Integration Into Your Systems
Add AI features to the app, CRM or internal tools you already have, through their APIs, without rebuilding them
RAG Systems
Assistants that answer from your documents and databases, grounded in your data with source citations, using Pinecone, Qdrant or PGVector
Chat Agents
Agents for your website, WhatsApp, Telegram or Slack that use real tools, remember context and hand over to a human when needed
Voice Agents & Calling Pipelines
Real-time voice agents that answer or make calls with Retell or LiveKit, then summarise the call and update your systems
Workflow Automation
n8n and code pipelines that connect email, calendar, documents, databases and APIs, with triggers and scheduled runs
AI Products & Wrappers
Full products built on top of LLMs: interface, auth, prompt layer, usage limits and cost control
Model Deployment
Hosted APIs or self-hosted open-source models, with model routing, fallbacks and cost optimisation
New AI Tool Integration
Evaluate and integrate new AI tools, APIs and agent platforms such as OpenClaw or Hermes Agent into your stack
Monitoring & Memory
Langfuse tracing on every run for latency, cost and debugging, plus Mem0 memory so agents remember context

What you get

  • A working AI feature, agent or pipeline in production
  • Integrations with your existing systems and APIs
  • Knowledge base and RAG setup, where needed
  • Monitoring with Langfuse, including cost and latency
  • Documentation and prompt templates
  • Handover walkthrough for your team

Process

  1. 01

    Discovery

    Which tasks and data are involved, what the AI should do, and what it should never do

  2. 02

    Design

    Architecture, model choice, data and RAG plan, integrations and a running-cost estimate

  3. 03

    Build

    Prompts, tools and integrations, tested against real examples from your business

  4. 04

    Integrate

    Connected to your app, CRM, phone system, email, databases or any third-party API

  5. 05

    Deploy & monitor

    Live in production with tracing, cost tracking and human review where it matters

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