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Al Kaizar Sappayani's avatar
Al Kaizar Sappayani
Houston, USA
AI Engineer(AI Agents, LLM Apps, Chatbots, RAG)
New to Contra
AI Engineer(AI Agents, LLM Apps, Chatbots, RAG)
Cover image for AI - powered insurance Agent Problem: Prior auth was manual—...
AI - powered insurance Agent Problem: Prior auth was manual—staff reviewed patient docs to predict approvals, making the process slow and resource-heavy. Solution: Built a HIPAA-compliant AI auth system: extract clinical data (OCR + clinical NLP), form a structured EHR-like record, evaluate insurer rules, and generate approval suggestions; added voice input workflows via STT/TTS plus secure storage and audit logging. Metrics: Reduced turnaround time and improved SLA adherence (similar projects reached ~98%). Result: Automated major parts of auth decisioning while staying compliant and auditable. Skills: AI Speech-to-Text AI Agent Development AI Builder AI Audio Generation AI Security
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Cover image for Marketing Assistant Bot As part of
Marketing Assistant Bot As part of my work in AI-driven automation, I built a Marketing Assistant Bot using Relevance AI to address a major challenge in customer engagement: inefficient lead handling and inconsistent follow-ups. Businesses often struggle with manually qualifying leads, responding to competitor comparisons, and guiding potential customers through the sales funnel. The lack of automation resulted in lost opportunities, delayed responses, and high drop-off rates. To solve this, I developed an assistant on Relevance AI
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Cover image for AI Sales Agent Problem: Customers needed fast, accurate answ...
AI Sales Agent Problem: Customers needed fast, accurate answers on courses/licensing/policies from a huge, changing catalog; support handled repetitive questions and compliance is state-specific. Solution: Built RUBI, an embedded RAG purchase advisor in using ETL + multimodal indexing and hybrid retrieval (metadata + vector + structured lookups) with cited, grounded answers, purchase flows, analytics, and tuning loops. Metrics: 695,042 conversations; 2.6 Qs/convo; feedback 6% up / 94% down; ~10s to first token, ~11s complete; KB >100k structured rows.
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Cover image for AI Generated Data Analysis Problem: Weekly call-center ops d...
AI Generated Data Analysis Problem: Weekly call-center ops data needed actionable synthesis; manual analysis was slow and inconsistent. Solution: Built an LLM data analysis agent: ingest call data, run NLP + aggregations, detect anomalies, and generate a weekly executive PDF with insights, metrics, and recommended actions Metrics Automated weekly PDF; similar setups cut analysis time ~90% and improved decision turnaround (one related client saw 17% revenue lift over 7 months) Tech: Python ETL, Pandas, NLP, GPT-4o, Airflow Result: Consistent reports that surface issues fast and drive quicker corrective action.
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Usman Haider's avatar
Usman Haider
Lahore, Pakistan
AI/ML & Data Solutions Engineer
New to Contra
AI/ML & Data Solutions Engineer
Cover image for Fine-tuned OpenAI Whisper model on
Fine-tuned OpenAI Whisper model on domain-specific medical audio data to improve transcription accuracy for clinical and healthcare use cases. The project involved preprocessing medical speech datasets, handling noise and terminology challenges, and optimizing the model for improved recognition of medical vocabulary, accents, and context-heavy conversations. Delivered a robust speech-to-text system capable of producing highly accurate, structured transcriptions suitable for documentation, reporting, and downstream healthcare applications.
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Cover image for Retail Knowledge Graph In this project,
Retail Knowledge Graph In this project, we built a semantic knowledge graph tailored to the retail industry. The pipeline involved developing AI agents to transform heterogeneous data into standardized formats. Ontologies were created to represent domain knowledge accurately. Using Gemini models and LangChain, user queries were converted into Cypher queries to retrieve insights from a Neo4j database. We utilized an MCP server for orchestration and LangSmith for secure login and audit trails. This system enhances complex data exploration for non-technical users.
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Cover image for Student Medical Chatbot Built a chatbot
Student Medical Chatbot Built a chatbot to assist MBBS students in navigating medical literature. Leveraged Llama Index and fine-tuned language models to ensure accuracy. Embeddings were stored in OpenSearch, hosted on AWS. The Django backend included secure authentication and session management for a robust user experience.
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Cover image for Prompt Engineering Mini-Academy is a
Prompt Engineering Mini-Academy is a digital learning product built using Kajabi. It helps users learn how to write better AI prompts and use AI tools for daily tasks such as writing, research, summarization, and productivity. The problem it solves is that many people use AI tools without a proper structure, which leads to weak or generic results. This product gives users a clear learning path, practical prompt templates, and workflow examples to improve the quality of their AI outputs. I used Kajabi to create the landing page, email capture form, downloadable prompt resource, product offer, checkout page, and course structure. A sample video is attached to demonstrate the product flow and user experience.
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Superwhisper(1)
Ali Beheshti's avatar
Ali Beheshti
Herndon, USA
AI Engineer | Document AI, Voice & Vision Systems
New to Contra
AI Engineer | Document AI, Voice & Vision Systems
Cover image for Designed a multimodal AI system
Designed a multimodal AI system combining voice input, document understanding, and structured data extraction. The system processes full-page documents and spoken input together, allowing flexible and efficient data capture. Key capabilities: AI-based document interpretation (beyond OCR) Voice-driven interaction and data entry Structured JSON outputs for downstream systems Support for multi-record extraction and validation This approach enables fully automated workflows in data-heavy environments and field operations.
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Cover image for Built a voice-enabled system that
Built a voice-enabled system that allows users to input structured data through natural conversation. The system captures spoken input and uses AI to map responses into structured fields in real time. Features include: Speech-to-text integration AI-assisted field mapping Multilingual support Real-time validation of inputs Designed for field environments where manual data entry is inefficient or impractical.
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Cover image for ARJAN — My Personal AI
ARJAN — My Personal AI Consulting Platform, Built on Zo Computer I'm Ali Beheshti — AI consultant, founder of iTAB, and professor of Data Science Ethics at George Washington University. ARJAN is where those three identities meet. 🔗 Live site: https://arjan-site-ab.zocomputer.io/ What I built on Zo: → Mission Readiness Score — visitors adjust 4 live sliders across Quality Engineering, Section 508, AI Governance, and Mission Security. An animated ring scores them in real time, identifies their top gap and strongest area, and one click sends the full assessment into my contact flow → Live TTS narration on every capability card with synced ASL overlay — Section 508 compliant, built for everyone → Gmail-powered contact workflow via Zo's native integration — 4 simultaneous email paths on every submission. No third-party tools. Just Zo. → Capability cards reshuffle on every visit — no two visits are identical → Pixel-aware logo hover animation with inline sound toggle My philosophy: AI should free people to focus on what matters — not replace them. Every feature on this site exists to serve the visitor. That is the only reason to build anything. #zocomputerchallenge
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Cover image for Developed an AI-powered platform for
Developed an AI-powered platform for automating field data collection, analysis, and reporting. The system integrates multiple input methods, including handwritten sheets, voice input, and direct data entry. Key capabilities: Automated data extraction and validation AI-assisted report generation Workflow tracking and project management Customizable outputs for engineering and technical teams Designed to reduce manual work and improve accuracy in field operations.
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Superwhisper(2)
Bilal Aleem's avatar
Bilal Aleem
Islamabad, Pakistan
AI Automation Expert | n8n | Make .com | LLM Integration
AI Automation Expert | n8n | Make .com | LLM Integration
Cover image for Built ZetAI — a fully
Built ZetAI — a fully functional AI-powered voice agent that listens to spoken commands and executes real business tasks autonomously. Unlike basic voice assistants that just answer questions, ZetAI takes action: scheduling meetings in Google Calendar, sending emails with AI-drafted content, creating tasks in Notion or Airtable, pulling live data from CRMs, and triggering n8n automation workflows — all from a single voice command. The agent uses a speech-to-intent pipeline: voice input is transcribed, the intent is classified by an LLM, the appropriate tool or workflow is selected, executed, and a voice confirmation is sent back to the user. Supports multi-step commands like "Find my last 3 unpaid invoices, draft a follow-up email for each, and schedule reminders for Friday." Designed as a personal business operating system for founders and executives who want to run their entire operation hands-free.
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Cover image for Built ZetaFin — an intelligent
Built ZetaFin — an intelligent financial tracking and reporting system that gives business owners a real-time view of their Profit & Loss without touching a spreadsheet. The system connects to the client's revenue sources (Stripe, PayPal, bank feeds), expense trackers, and invoicing tools, then automatically categorizes every transaction using AI, calculates live margins, flags anomalies, and generates a clean P&L report delivered to the client's inbox every Monday morning. An AI analysis layer adds context to every report — explaining why revenue increased or dropped, which expense categories are trending up, and what actions the owner should consider. Built entirely on n8n with OpenAI for financial analysis and Google Sheets as the live dashboard. The client — an e-commerce founder — went from spending 3 hours every week manually reconciling finances to receiving a fully analyzed, actionable report automatically.
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Cover image for Designed and built Aixen AI
Designed and built Aixen AI a unified communication and lead management platform powered by multiple LLMs working in coordination. The system monitors and manages inbound leads across email, Instagram DM, WhatsApp, and Telegram simultaneously. Each channel has a dedicated AI agent that reads incoming messages, understands context and intent, generates appropriate responses, and escalates or routes leads based on qualification criteria. A central Lead Manager Agent maintains a live unified inbox view deduplicating contacts across channels, tracking conversation history, and scoring lead quality in real-time. Sales-ready leads are pushed to the CRM with a full conversation summary automatically. The client — a digital marketing agency — replaced a 4-person response team with this system, achieving sub-2-minute response times across all channels 24/7. Built on n8n with GPT-4o, Claude, and WhatsApp Business API.
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Cover image for Built a production AI voice
Built a production AI voice calling agent that autonomously pre-qualifies leads over the phone — no human needed on the line. The agent calls prospects from an enriched list, conducts a natural qualification conversation using a fine-tuned voice AI model, extracts key intent signals from the call, scores each lead as Hot / Warm / Cold, and instantly routes qualified leads to the sales team via CRM update and Slack notification. The entire workflow from list upload to qualified lead delivery — runs inside n8n. The client's sales team went from spending 6 hours per day on cold pre-qualification calls to receiving only pre-scored, context-rich leads ready to close. Call transcripts and scores are logged automatically for every single dial. Integrated with: Vapi (voice AI), n8n (workflow), HubSpot (CRM), Slack (alerts).
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Superwhisper(1)
Manuel Ayala's avatar
Manuel Ayala
Buenos Aires, Argentina
I ship AI tools, CRMs & landing pages in 48 hours
New to Contra
I ship AI tools, CRMs & landing pages in 48 hours
Cover image for AI visibility audit and content
AI visibility audit and content optimization dashboard for a criminal defense law firm. Tracked 1,279 videos, optimized 50 in the first sprint. 120K+ total views, 635K impressions, 3.7% CTR. Interactive dashboard with progress tracking, optimization status, and performance metrics.
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Cover image for Premium booking-led website for a
Premium booking-led website for a padel sports club in Vicente López, Buenos Aires. Dark editorial design, conversion-focused hero with embedded reservation widget, membership experience pages, and gallery. Built for speed and booking conversion: visitors can pick a date and time slot without leaving the homepage. Mobile responsive, optimized for the quick-decision booking flow typical of sports and wellness businesses. Stack: Next.js, Vercel.
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Cover image for Conversion-focused landing page for a
Conversion-focused landing page for a digital agency in Argentina. Dark theme, mobile-responsive, built-in diagnostic tool, WhatsApp integration, and SEO-optimized copy. Designed, built, and deployed in under a week. Plus I created over 400 articles and the site is already getting organic traffic via Google/Bing/Yahoo and AI models, first visitors came after just 3 days.
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Cover image for AI-powered court case tracker for
AI-powered court case tracker for a US law firm. Tracks NJ Supreme Court decisions, generates brief citations, transcribes oral arguments, and analyzes webcast video. Users can search, save, and export cases. They can also talk about cases, transcripts and such, powered by Gemini API. Built on Next.js with AI API integrations. Fully responsive.
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