Hafiz Bilal A.

I build AI agents, chatbots and automations that do real work inside a business: answering customers, qualifying leads, reading documents, updating your CRM and reporting back, with a person signing off wherever it matters. WHAT I BUILD AI agents and agentic workflows • Agents that plan, use tools and finish multi-step tasks such as research, outreach, triage, reporting and data entry • Multi-agent systems where specialised agents pass work between them, with checkpoints and human approval built in • MCP servers and custom tools so agents can work safely with your own systems Chatbots and AI assistants • Customer service and sales chatbots for your website, WhatsApp, Telegram, Slack or email • Knowledge-base assistants (RAG) that answer from your documents, policies and help centre, and hand over to a person when they're unsure • Internal assistants that help your staff find information and draft their work faster Voice AI • AI receptionists and phone agents that answer calls, qualify callers and book appointments into your calendar Automation and integrations • Workflow automation with n8n, Make, Zapier or custom code • Connecting your CRM, email, calendar, forms and spreadsheets through APIs and webhooks • Document processing: pulling data out of PDFs, invoices, contracts, forms and emails LLM engineering • Claude, OpenAI, Gemini, DeepSeek and open-source models, chosen for the right balance of cost, speed and quality • Prompt engineering, structured outputs, evaluation and testing, so answers stay accurate as you scale • Embeddings, vector databases and fine-tuning where it genuinely helps • Claude rollouts for teams: workspaces, projects, Claude Code and sensible data controls Full-stack development and deployment • AI Web apps, client portals and dashboards (React, Next.js, Node.js, Python) • AI Mobile apps • Deployment on AWS, Google Cloud, Azure or your own server, with Docker, logging and monitoring AI SYSTEMS WE RUN OURSELVES • A self-hosted multi-agent system: six specialised agents on a private server, controlled through Telegram • A nine-agent research and validation pipeline built with Claude Code, with sourcing rules and checkpoints that stop it inventing evidence • A first-party website intent-tracking system for B2B prospecting, built as a low-cost alternative to third-party data tools HOW A PROJECT RUNS 1. A short call to understand your process and agree what success looks like 2. A fixed scope with milestones, so you know the cost and timeline before we start 3. Then test with real scenarios, adding logging and human approval where it matters 4. Handover with documentation, a walkthrough for your team, and support once it's live Security isn't an afterthought. Access is kept to the minimum, API keys stay out of the code, and none of your data goes to an AI model unless it should. If there's a task your team does over and over, tell me about it. I'll give you an honest view on whether AI can take it on, how long it would take and what it would cost.