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Michael Gould's avatar
Michael Gould
Lorton, USA
Workflow automation for forms, CRMs, Zapier, Make, n8n.
New to Contra
Workflow automation for forms, CRMs, Zapier, Make, n8n.
Cover image for Self-initiated internal product. Odds Desk
Self-initiated internal product. Odds Desk uses public data only. It is not client work, a trading tool, or financial advice. I built this because a research brief is only as trustworthy as the source snapshot behind it. Catalog freshness, derived summaries, file identity, and editorial status need to stay consistent across every generated artifact. The workflow synchronizes a public catalog, exports one canonical bundle, generates and validates a summary, regenerates a manifest, checks declared SHA-256 values against disk, and produces a dashboard and Markdown brief from the same saved files. The workflow fails closed. If a required validation fails, the bundle stops, the evidence is preserved, and no buyer-ready issue is produced. The gallery shows a July 30, 2026 snapshot with 675 saved markets, 36 unverified research leads, zero verified cards, and four of four declared hashes matching disk. The state remains RESEARCH_PREVIEW. Best fit: public API ingestion, reproducible research bundles, validation pipelines, provenance checks, fail-closed editorial workflows, and automated briefing systems.
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60
Cover image for HVAC Lead Handoff Rescue Case Study
HVAC Lead Handoff Rescue Case Study
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8
Cover image for A self-initiated workflow automation demo
A self-initiated workflow automation demo showing a simple lead handoff: intake, routing, CRM or sheet logging, owner notification, and test-ready review output.
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62
Cover image for A self-initiated Brief Factory internal
A self-initiated Brief Factory internal system. The gallery shows public post titles only. No names, handles, contact details, or private messages are shown. I built this to make public automation research more consistent. Instead of manually checking communities for scattered requests, the monitor reads selected RSS and Atom feeds, normalizes source URLs, rejects stale or generic items, scores observable workflow pain, deduplicates accepted rows, and records source health. The output is a structured review queue, not permission to contact anyone. The system does not post, bid, message, or send. The gallery shows a dated run from July 30, 2026: seven configured feeds, seven review rows, two HTTP 429 rate limits, zero high-intent rows, and zero external actions authorized. Best fit: public-source monitoring, qualification queues, source-health reporting, research triage, and review-first opportunity workflows.
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56
JSON PowerDB(1)
Siddiq Tashfeen's avatar
Siddiq Tashfeen
St. John's, Canada
Full-Stack Engineer | AI Automation & Workflow Systems
31
Followers
Full-Stack Engineer | AI Automation & Workflow Systems
Cover image for Built an AI-powered news automation
Built an AI-powered news automation system using n8n and Google Sheets that collects articles, filters data, processes content with AI, and automatically updates structured records for marketing insights and content tracking.
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488
Cover image for Outbound Lead Generation & Automation
Outbound Lead Generation & Automation System (Email + LinkedIn) I built a complete outbound system to generate and convert high-quality B2B leads using email and LinkedIn automation. The system starts with ICP-based lead sourcing, targeting companies by size, revenue, industry, and C-level roles. Leads are enriched, segmented, and automatically routed into a structured outreach flow. I designed a 6-step email sequence where messaging evolves at each step to increase reply rates. LinkedIn actions are timed between email touches to create a natural multi-channel outreach without overlap. The main challenge was coordinating multiple tools while maintaining deliverability and clean data flow. I solved this by building a centralized automation layer that handles sequencing logic, delays, and real-time updates across systems. A lightweight CRM tracks every lead from first contact to final outcome, including replied, interested, and not interested. This provides clear visibility and allows continuous optimization. The system is structured for scalability and simple handoff, so it can be managed without technical dependency.
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162
Cover image for Built a feedback and workflow
Built a feedback and workflow management system focused on collecting, organizing, and prioritizing user-driven inputs across multiple channels. The platform provides a structured interface where feedback items move through defined stages, enabling teams to track status, engagement, and impact in a clear and scalable way. On the backend, I designed data models and filtering logic to support advanced querying, segmentation, and lifecycle management of feedback items. Implemented role-based access control and admin-level configurations to manage permissions, visibility, and workflow transitions. This ensures that internal teams can efficiently manage large volumes of data while maintaining consistency and control. On the frontend, I focused on building clean dashboards and interactive views that surface key metrics such as user reach, engagement, and revenue impact. I also implemented public-facing and read-only views, allowing external users to submit feedback and track updates without direct system access. This improves transparency while keeping the system secure and well-structured.
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228
Cover image for I built a workflow management
I built a workflow management system focused on tracking projects from start to completion with clear visibility and control at every stage. The core of the system is a multi-role dashboard that presents real-time data in a structured way, allowing different users to quickly understand project status, performance metrics, and operational health without digging through raw data. On the backend side, I designed structured data models and lifecycle flows to manage how tasks move through different stages (creation → in-progress → completed). I implemented role-based access control and admin-managed configurations so the system can handle multiple users, permissions, and dynamic updates reliably. The goal was to make the system scalable and maintainable while keeping the logic clean and predictable. For the frontend, I focused on building intuitive dashboards and reporting layers that translate complex data into simple, actionable insights. I also implemented shareable, read-only views so external users can track progress through a secure link without needing full access. This improves transparency while maintaining control over the system, which is critical for B2B workflow tools.
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229
JSON PowerDB(1)
Kelechi Asonye's avatar
Kelechi Asonye
Ikeja, Nigeria
Professional API Documentation & README Writing
5.0
Rating
8
Followers
Professional API Documentation & README Writing
Cover image for Step-by-step user guide covering onboarding,
Step-by-step user guide covering onboarding, core features, configuration, and FAQ for a SaaS analytics product. https://keen-sunshine-484608.netlify.app/
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100
Cover image for Wrote complete API documentation for
Wrote complete API documentation for a task management platform including authentication guides, endpoint references, request/response examples, and error code tables. Formatted for developer readability with cURL examples throughout.
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153
Cover image for Most developers ship great products
Most developers ship great products and then write documentation that drives users away. No clear setup guide. No code examples. No API reference. Just confusion and users move on before they even give your product a chance. I'm Kelechi a Technical Writer and Cybersecurity Analyst based in Lagos. I help SaaS founders and developers turn incomplete, messy docs into clean professional references that actually help users succeed. What I deliver: 📡 REST API Documentation 🔐 SDK & Library Guides 📄 GitHub READMEs 📊 Product User Guides 🛡️ Security SOPs & Process Docs What makes me different I actually understand the technology I write about. With a background in cybersecurity and system administration, I don't just write about your product. I understand it deeply. Fast turnaround. Flat rate pricing. Free sample on every first project zero risk on your end. 🌐 bishopasonye.vercel.app (http://bishopasonye.vercel.app)📁 bishopasonye.github.io/Portfolio DM me and let's get your documentation sorted.
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Cover image for Professional open-source README with feature
Professional open-source README with feature overview, installation guide, usage examples, and contribution guidelines
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116
JSON PowerDB(2)
Chidi Chukwu's avatar
Chidi Chukwu
Madrid, Spain
Virtual Assistant/Web Development/AI Content Creator
New to Contra
Virtual Assistant/Web Development/AI Content Creator
Cover image for Travel Blog Animated Website
Travel Blog Animated Website
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60
Cover image for Georgian Restaurant Website
Georgian Restaurant Website
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36
Cover image for Restaurant Website Development
Restaurant Website Development
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2
166
Cover image for Wellness Mobile IOS App Design
Wellness Mobile IOS App Design
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5
195
JSON PowerDB(1)
Edgaras Kamandulis's avatar
Edgaras Kamandulis
Salò, Italy
High-Frequency Decision Architect for Zero-Latency Business
High-Frequency Decision Architect for Zero-Latency Business
Cover image for Huntsman: Real-Time Crypto Data Aggregator Engineered a high...
Huntsman: Real-Time Crypto Data Aggregator Engineered a high-performance asynchronous data aggregator using Python asyncio and ccxt.
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Cover image for This isn't Finance. It's Physics. Markets are fluids. Price ...
This isn't Finance. It's Physics. Markets are fluids. Price is velocity. Crash is turbulence. While you stare at RSI, I am calculating the Laminar Flow. My S.C.A. Protocol applies Navier-Stokes equations to capital. If you understand this graph, you know why we need to talk. ​The Second Quantum Revolution is here.
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Cover image for LIBRARIAN CORE: Architecting Intelligence beyond the "0=0" A...
LIBRARIAN CORE: Architecting Intelligence beyond the "0=0" Axiom Most people use AI to write emails. I built the Librarian to navigate reality. The screenshots below show the result of a single afternoon of intense development. It’s not 'pretty' yet, and it’s not finished—it is raw Backend Logic manifesting as an interface. I spent my time stabilizing the architecture and the core consistency of the system. The Philosophy behind the Code: Everything I build starts with a fundamental pact: 0=0. Absolute coherence. Truth. Input must equal Output. This is the mathematical baseline required to find truth within data. However, the Librarian knows that stasis is death. In his core, 0=0 is a fatal termination error. Why? Because if a system only confirms what it already knows, it isn’t evolving. It is just waiting to become dust. 🌌
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Cover image for Evolutionary Parameter Tuning Engine (Python) To solve the p...
Evolutionary Parameter Tuning Engine (Python) To solve the problem of market stagnation in HFT (High-Frequency Trading), I architected a Genetic Algorithm that evolves the bot's configuration in real-time. Instead of static settings, the system spawns a population of 40 different trading 'personalities'. It forces them to compete in a stochastic simulation based on recent market data. The Process: Selection: The top 10% performing configurations are isolated. Crossover: Their traits (RSI thresholds, Risk multipliers) are spliced together. Mutation: Random variations are introduced to discover new local optima. As shown in the terminal log, the system automatically evolved a strategy that increased efficiency from 263.3 to 492.8 in 15 generations, injecting a high-frequency aggressive configuration into the live bot.
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JSON PowerDB(1)