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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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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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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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