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AI Chatbots Should Do More Than Just Answer Questions 🤖
I’ve been building AI chatbot solutions that go beyond basic Q&A.
A useful business chatbot should be able to understand your company’s knowledge, answer customer questions accurately, capture and qualify leads, trigger workflows, and connect with the tools your team already uses.
Recent solutions I’ve worked on include:
→ Custom knowledge-base / RAG chatbots
→ OpenAI & LLM integrations
→ Website AI assistants
→ WhatsApp & messaging integrations
→ Lead capture and qualification
→ CRM & API integrations
→ Human handoff workflows
→ Conversation history & analytics
→ Custom admin dashboards
The goal is simple: turn AI into a practical business tool—not just another chat window.
If your business has repetitive customer questions, manual lead handling, or information scattered across documents and systems, a custom AI assistant can automate a significant part of that workflow.
Exactly, AI chatbot should sound real like human
Absolutely. The best AI chatbots should feel natural, understand context, and respond conversationally — not like a scripted bot.
This is wonderful. I fully buy into this content any day any time. Keep up the good work
Thank you so much! Really appreciate the support. I’ll keep sharing practical AI solutions and real-world development insights. 🙌
Looking forward to more from you
Super impressive work
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What if your PC could actually listen, understand, and do the work for you?
I’m building that idea into something real.
Meet AURA — my personal AI voice assistant for Windows.
Instead of building another chatbot that only answers questions, I’m experimenting with an AI agent that can actually interact with my computer and help with everyday work.
So far, AURA can:
• Have live voice conversations
• Convert speech to text and respond with voice
• Open applications like Excel, Power BI, Chrome, and Windows Settings
• Search the web and YouTube through voice
• Perform basic PC and file operations
• Understand requests through Gemini
• Execute actions through a safety-controlled automation layer
• Continue listening after completing a task
But this is only the beginning.
My long-term goal is to make AURA understand my actual workspace — including what’s happening on my screen and inside applications — so I can simply say:
“Open my Excel file, check the sales data, clean the date column, and add a formula for total revenue.”
And let AURA handle the workflow.
I also want it to become useful for my own Data Analytics work — from Excel and Power BI workflows to repetitive desktop tasks, research, and automation.
I’m building AURA with Python, AI, voice technologies, desktop automation, Excel, Power BI, and LLMs, while keeping safety and human control at the core.
It’s still far from the final vision.
But that’s exactly what makes the project interesting.
I’m not just learning how AI agents work.
I’m trying to build one that I can actually use every day.
Building in public. Learning by building. 🚀
#AI #AIAgents #Python #AIAssistant #VoiceAI #DesktopAutomation #DataAnalytics #PowerBI #Excel #Automation #BuildInPublic
The screen-reading step is where I would put the guardrail. Once AURA can read what is in the window, everything on that screen is input - and a page it opened from a voice search can hold a sentence written to be read as an instruction. I spent a while trying to rob my own...
Back in 2016 I made a lot of cinemagraphs for HBO.
They took a surprising amount of work. Masking footage, finding the right loop, freezing parts of the frame and getting everything to transition cleanly.
I’ve had an idea for a simpler cinemagraph tool kicking around in my head ever since.
About a month ago I built another small tool using Toolcraft as the starting point, so yesterday I wanted to see if it could handle this idea too.
A few hours later I had a working cinemagraph editor.
Drop in a video → find your loop → choose how it loops → paint the areas you want to keep still → export.
Basically the workflow I used 10 years ago, condensed into a few controls.
Still rough around the edges, but kind of wild to finally build a tool I’ve been thinking about for a decade.
The masking-and-looping history is exactly why a simpler cinemagraph workflow feels valuable; the tricky part is preserving a seamless transition without making the tool feel like a timeline editor. Curious direction for an AI-assisted app.
Here’s how the system actually works.
A stranger sees your offer.
They click.
They become a lead.
But getting the lead is only the beginning.
The system now needs to know:
Who are they?
Where did they come from?
What are they interested in?
What have they done so far?
Then things start to branch.
If they respond → someone follows up.
If they book → the conversation changes.
If they don't respond → they enter another follow-up.
If they show buying intent → sales gets involved.
If they buy → they leave the sales journey and enter another one.
And all of this can happen without someone manually checking every lead.
That's the part of automation I find interesting.
It's not really about sending emails or SMS.
It's about building a system that reacts to what people do.
Traffic comes in.
Data gets collected.
Behaviour creates signals.
Signals trigger decisions.
Decisions create actions.
That's the dynamic behind a well-built CRM and automation system.
Hey, I built the entire application end to end. The real challenge inside the CRM automation is the perfect stages tagging along each stage if & else coordinations.
I built the entire wireframe. I can share with you.