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Hey Contra,
Recently worked on an AI-powered Speech Coaching platform that analyzes speeches, presentations, and audio recordings using custom AI evaluation frameworks.
Built an AI-powered Speech Coaching platform that analyzes speeches, presentations, and audio recordings using custom AI evaluation frameworks.
The platform supports multiple speech types including Architectural Reviews, Academic Presentations, Environmental Research, Public Speaking, and Pitch Analysis — each with different coaching metrics, analysis logic, and structured feedback pipelines.
Key features included:
AI-generated speech analysis
Real-time audio recording & uploads
Prompt-engineered coaching frameworks
PDF export for downloadable reports
Context-aware evaluation pipelines
Structured output formatting for professional coaching feedback
Multiple coaching styles and speech goals
Tech Stack:
Next.js, Python, OpenAI APIs, AWS SAM, Serverless Architecture
One of the biggest challenges in this project was improving AI consistency and making the generated feedback feel more human-like, professional, and context-aware instead of generic AI responses.
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This is my ultimate solution for global UI/UX pitches. It is an automated video template that starts with just a single static Figma screen and a rough text idea — no microphones, no video editing, no manual syncing — and transforms them into a perfectly timed, fully-voiced, multilingual promo video.
It shows how the same pipeline can take a clean SaaS dashboard or a dark-mode Web3 design, preserve the crisp typography, and instantly generate an agency-grade asset ready for international markets.
Create once. Pitch globally.
Template link: https://elevenlabs.io/app/flows/seAf30BRE2nsBfY4dh1q
X post: https://x.com/KrisAnfalova/status/2054240705019613627?s=20
@ElevenCreative x @Contra HQ
Hi Kris! Really loved the idea - definitely planning to use it. Quick question though: the presentation video you shared, was it created entirely using the same template you mentioned, including the visuals, speech, animations, and everything else? Even if most of it was, that’s...
This is why your AI captions sound robotic 👇
Left side: what most creators type into ChatGPT
Right side: what happens when you use a structured prompt
Same AI. Completely different output.
The secret isn't a better tool.
It's knowing exactly HOW to ask.
I built 100 prompts in the "After" format —
for Reels, captions, Stories, content planning, and growth.
$15. Instant download. Checkout My Profile Products to Get this now..
Save this so you remember it next time ChatGPT disappoints you 💾
#chatgptprompts #instagramtips #contentcreator #aitools #instagramgrowth #chatgpt #socialmediatips #reelsideas #contentcreation #digitalproduct
Prompts really does matter
Building an AI-Powered WhatsApp Sales & Support Platform for Businesses
Overview
Wabrix is a WhatsApp automation platform designed to help businesses handle customer conversations at scale using AI. The platform enables brands to automate support, qualify leads, answer FAQs, recover abandoned customers, and manage conversations directly through WhatsApp with a fast, human-like AI assistant.
I led the end-to-end development of the platform, including the AI chat infrastructure, WhatsApp integration system, onboarding flow, automation builder, analytics dashboard, and real-time conversation management tools.
Goal
The main goal was to turn WhatsApp from a manual support channel into an AI-powered operational workflow that could increase response speed, reduce support workload, and improve customer conversion.
From a business perspective, the platform needed to do more than simply auto-reply messages. It had to function as an intelligent sales and support assistant that could:
- qualify leads automatically
- guide customers through buying decisions
- handle repetitive support requests
- recover potential lost sales
- escalate conversations to human agents when needed
The product was designed to help businesses respond instantly while maintaining a natural and branded customer experience.
What I Did
I built the platform from the ground up with a strong focus on scalability, automation, and real-world business usability.
My work included:
- Building the WhatsApp AI chat infrastructure and messaging workflows
- Developing the admin dashboard and conversation management system
- Creating automation flows for support, lead qualification, and customer follow-up
- Integrating WhatsApp Cloud API for real-time messaging
- Designing AI context handling for better response accuracy and brand consistency
- Implementing multilingual support for broader business adoption
- Building analytics and reporting systems for tracking engagement and response performance
- Creating human handoff systems for support escalation
- Developing onboarding flows to simplify setup and adoption for businesses
Workflow / System Design
One of the most important parts of the project was designing the platform as a business workflow system rather than a simple chatbot.
The AI layer needed structured access to:
- customer conversations and message history
- business knowledge and FAQs
- sales and support workflows
- lead qualification logic
- human escalation rules
- response behavior and brand tone
This allowed the AI to operate more like a real support and sales team member instead of a generic assistant.
The platform was designed around operational efficiency: automated responses, structured customer flows, measurable outcomes, and smooth human collaboration when needed.
Implementation
The platform was built using modern full-stack architecture and real-time messaging systems:
- React-based admin dashboard
- WhatsApp Cloud API integration
- AI-powered conversational workflows
- real-time messaging infrastructure
- automation and escalation systems
- analytics and conversation tracking
- multilingual AI response handling
- role-based workspace management
- performance monitoring and reporting tools
Result
The platform successfully helped businesses automate customer communication while improving operational efficiency and response speed.
Businesses were able to:
- reduce manual support workload
- respond to customers instantly
- increase lead engagement
- improve conversion opportunities
- manage conversations more efficiently through centralized workflows
The system achieved extremely fast AI response times, averaging around 17 seconds for automated support interactions.
Outcome
This project demonstrated how AI can be applied to WhatsApp in a practical, business-focused way. not as a gimmick, but as a scalable communication workflow that supports sales, support, and customer experience simultaneously.
The result was a platform that helped businesses operate faster, respond smarter, and create a more seamless customer journey directly inside WhatsApp.
Good work!
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