Find Python Projects with Vollna

I’m building an AI-powered module that takes a traveller’s basic preferences—dates, departure city, destination, budget range—and automatically secures the best-matched flights and hotels in one seamless flow. The core focus is booking and reservations, not broader trip planning, so I need the logic, data connections, and UX devoted to getting confirmed tickets and rooms with minimal user input.

Key requirements
• Flights and hotels must both be supported from day one.
• Real-time availability and pricing pulled from reliable GDS or OTA APIs (Amadeus, Sabre, Skyscanner, Booking.com, etc.).
• A conversational layer (chat or voice) that gathers trip parameters, explains options clearly, and proceeds to checkout once the traveller accepts.
• Secure payment processing and automated confirmation delivery (email + in-app).
• Scalable architecture ready to add car rentals later without rewriting core code.

Tech flexibility
I’m agnostic on stack—Python, Node, or whatever you’re fastest in—as long as the final build is well documented, containerised, and can plug into my existing React front end.

Deliverables
1. Working back-end service with documented API endpoints.
2. Simple front-end demo that shows the end-to-end booking experience (input → AI suggestions → confirmed booking).
3. Deployment guide and hand-over call to walk through code, environment variables, and third-party keys.

Acceptance criteria
• User can book a round-trip flight and hotel in under three minutes with no manual site redirects.
• Prices returned match the live rate on the provider’s site within ±1%.
• All personal and payment data handled over HTTPS and stored encrypted.

If this scope excites you and you have proven GDS or travel API experience, let’s talk timelines and milestones so we can get travellers booking effortlessly with AI.

Skills: PHP, Python, Mobile App Development, Software Architecture, Node.js, Web Development, Chatbot, API Development, User Experience Research, AI Development

I’m looking for an experienced Pine Script developer to convert my existing trading strategy into a fully functional TradingView indicator, and set up a system to send alerts from TradingView to MT5 for automated or semi-automated execution.

Project Scope:

Convert my trading strategy into a clean, efficient Pine Script indicator (v5 preferred)
Ensure accurate signal generation (Buy/Sell/Exit) as per the original logic
Implement real-time TradingView alerts based on these signals
Set up a reliable method to send alerts to MT5 (via webhook/API/bridge)
Ensure alerts trigger correctly without repainting issues
Optimize for performance and minimal lag

Requirements:

Strong experience with Pine Script (TradingView)
Experience integrating TradingView alerts with MetaTrader 5 (MT5)
Knowledge of webhook/API or third-party bridges (e.g., PineConnector, custom API, etc.)
Ability to maintain strict logic accuracy from the original strategy
Good communication and quick turnaround

Nice to Have:

Experience with automated trading systems
Familiarity with forex/crypto trading strategies
Ability to suggest improvements or optimizations

What I Will Provide:

Complete strategy logic (rules/conditions)
Examples or reference signals (if needed)

Deliverables:

Fully working Pine Script indicator
Alert system configured and tested
MT5 integration working smoothly
Documentation or brief guide for usage

Budget: Open to discussion (fixed or hourly)

If you have done similar projects before, please share examples or portfolio links.

Looking forward to working with a skilled developer!
ps : only experienced and proven traders required.

Hi,

I’m building a simple SaaS MVP for digital receipts (web-based), including a merchant dashboard, QR/NFC flow, and basic backend.

I’m looking for a full-stack developer who can deliver a clean, scalable MVP within 2–3 weeks.

If this is something you have experience with, I’d be happy to share more details and discuss the scope.

Looking forward to hearing from you.

AI Call Center Developer – Twilio, Dialogflow, CRM Integration (Outbound Loans & Credit Cards)

Responsibilities:

Set up VoIP/telephony layer (Twilio or Asterisk).
Implement Speech-to-Text (STT) for real-time transcription.
Integrate NLP engine (Dialogflow or Rasa) for intent detection.
Add Text-to-Speech (TTS) for natural voice responses.
Connect system to Zoho/HubSpot CRM for lead logging and callbacks.
Build branching conversation flows for multiple campaigns:

Personal loans.
Business loans.
Credit card offers.

Provide basic analytics dashboard for call outcomes.
Requirements:

Proven experience with Twilio, Asterisk, or similar VoIP systems.
Strong skills in Python/Node.js for API integration.
Familiarity with Dialogflow, Rasa, or NLP frameworks.
Experience with CRM integration (Zoho, HubSpot, Salesforce).
Ability to deliver a modular, scalable solution that supports multiple campaigns.


Nice to Have:

Knowledge of financial services telecalling compliance (loan/credit card regulations).
Experience with sentiment analysis and advanced AI features.

Skills: Python, Software Architecture, CRM, Salesforce.com, Salesforce App Development, AI (Artificial Intelligence) HW/SW, Twilio, NLP

We are looking for an experienced AI development partner/team to build an Offline AI Learning Engine for deployment in Government school classrooms.

The system will include:
* AI Teaching Assistant (LLM-based)
* RAG (Retrieval-Augmented Generation) using curriculum content
* AI-based assessment and quiz generation
* Teacher Copilot features
* Offline-first deployment on local classroom systems
* Central sync with Data Centre

Scope of Work
* Design and develop RAG-based AI system using provided educational content
* Implement local AI model for offline usage
* Fine-tune model for:
- school-level explanations
- bilingual support (English + regional language)
- curriculum-bound responses
* Build APIs and backend for integration with classroom system
* Develop synchronization system (offline → central server)
* Provide documentation and training

Technical Requirements
* Experience with LLMs (LLaMA, Mistral, etc.)
* Experience with RAG frameworks (LangChain / LlamaIndex)
* Vector databases (FAISS / Qdrant / Chroma)
* Local AI deployment (Ollama / llama.cpp)
* Python backend (FastAPI preferred)

Deliverables
* Fully functional AI engine (offline capable)
* Documentation
* Deployment support
* Training for internal team

Preferred Experience
* EdTech AI systems
* Multilingual AI systems
* Offline AI deployments

Engagement Type
* Fixed cost / milestone-based
* Long-term engagement possible

Skills: Python, Natural Language Processing, AI Text-to-speech, AI Text-to-text, AI Chatbot Development, AI Model Development, AI Content Creation, AI Research, AI Writing, AI Development

I need a small, reliable web-based tool that can take any Facebook post I specify and automatically repost it to selected Facebook groups at regular, user-defined intervals. The key functions I care about are:

• Browser-accessible (hosted or self-hosted) so I can run it from any operating system without local installs.
• A timer/cron-style scheduler where I enter the interval—minutes, hours, or days—and the system handles the repeats until I stop it.
• The ability to load a list of groups (URLs or IDs) and have the same content pushed to all of them in one cycle.

I am not particular about the look and feel; a simple GUI, command line panel, or even a minimalist dashboard is fine as long as it’s intuitive. Future enhancements such as broader content scheduling or basic analytics would be nice to keep in mind, but the first milestone is working, repeatable reposts across multiple groups.

Please outline the tech stack you would use, any experience you have dealing with Facebook’s API or automation tools, and the estimated timeframe for a functional prototype. Access credentials, installation instructions (if self-hosted), and a quick start guide should be included in the hand-off.

Skills: PHP, JavaScript, Python, Software Architecture, Facebook API, Web Development, API, Automation

Plz read this paper: Reliability analysis of complex systems using subset simulations with
Hamiltonian Neural Networks (HNN)
Link: https://www.sciencedirect.com/science/article/pii/S0167473024000468?via%3Dihub
Now, I need to understand the full concept of subset simulations and Hamiltonian Neural Networks. and then need a excel sheet calculation and implementation of SS with HNN. The work should be performed as per my satisfaction.

We are seeking an experienced automation specialist to help automate our strategy using Python and web scraping techniques. The ideal candidate will have a strong background in data scraping and web crawling, and be able to implement efficient solutions to streamline our processes.

I want an automated process that sends me an email the moment any bank-related transaction is registered. Email is the only channel I’d like to use, so there is no need for SMS or push integrations.

Each email must contain the item I’ve specified – “فتح” – exactly as written, placed clearly within the body of the message. If you feel that adding common details such as the amount, date-time stamp, or updated balance would improve clarity, let me know and we can expand the template.

You are free to choose the most practical stack (Python with SMTP libraries, Node.js + Nodemailer, serverless functions, etc.) as long as it can:

• listen for new bank-transaction events (webhook, polling, or API, depending on what you propose)
• format the email with the required “فتح” field
• deliver reliably to my inbox and log any failures for troubleshooting

Please include a brief outline of your approach, the tools you plan to use, and an estimated turnaround. A short demonstration or test run with sample data will be part of the final hand-over.

Skills: PHP, Python, Troubleshooting, Node.js, Email Marketing, Software Development, API, Backend Development, SMTP, Automation

**Project Title:**
AI-Based 3D Design & Planning Platform (Web Application)

---

**Project Overview:**
I want to build an AI-powered web platform where users can generate complete design solutions based on their requirements. The platform should be simple, user-friendly, and accessible to everyone.

Users will input their requirements (text or image upload), and the system will generate design outputs such as 3D models, layouts, and reports.

---

**Target Users (Who will use this platform):**

This platform is for **all types of users**, including:

* **Students** (engineering, architecture, school projects)
* **Engineers & Architects** (for quick concept generation)
* **Home owners / Individuals** (house planning & ideas)
* **Business owners** (office, shop, factory layout design)
* **Startups & Product creators** (new product design concepts)
* **Government / Planning departments** (basic visualization & planning ideas)

The goal is to make design accessible to **anyone, regardless of technical background**.

---

**Purpose of the Platform:**

* To provide **quick and affordable design solutions**
* To help users visualize ideas before actual construction or production
* To reduce dependency on expensive design tools
* To speed up planning and decision-making
* To act as a **bridge between users and professional architects/engineers**

---

**Core Features Required:**

1. **User Input System**

* Text input (e.g., “500 gaj house design”, “sports car design”, etc.)
* Image upload option for reference

2. **AI Design Generation**

* Generate multiple design options (3–5)
* Focus initially on:

* House design (priority)
* Interior layout
* Future scope: mechanical/product design

3. **3D Visualization**

* Basic 3D model viewer (using Three.js or similar)
* User can rotate, zoom, and explore design

4. **Output Formats**

* Image renders (front view, interior, etc.)
* PDF report (layout, details, description)
* Excel file (room sizes, basic data)
* (Future Phase) Video walkthrough of design

5. **User System**

* Login / Signup
* User dashboard (saved designs)
* Download option for outputs

6. **Pricing System**

* Free plan (limited usage)
* Paid plans (Student, Pro, Business)
* Payment gateway integration (Razorpay/Stripe)

7. **Admin Panel**

* User management
* Plan management
* Content/control system

---

**Technology Preference:**

* Frontend: React.js
* 3D: Three.js / WebGL
* Backend: Node.js or Python (Django/FastAPI)
* AI Integration: OpenAI / Stable Diffusion APIs (or similar)

---

**Important Notes:**

* This platform will provide **conceptual designs only**, not final construction-ready or certified engineering drawings
* The system should be scalable for future features
* Clean UI/UX is very important

---

**Project Phases:**

**Phase 1 (MVP):**

* House design generation
* Basic 3D view
* Image + PDF export
* Login system

**Phase 2:**

* Excel export
* Improved 3D
* Payment system

**Phase 3:**

* Video walkthrough
* Marketplace (connect with architects/engineers)

---

**Timeline:**
MVP expected in 15–30 days

---

**Budget:**
(Open for discussion based on experience and proposal)

---

**Expectation from Developer:**

* Clean and scalable code
* Good communication
* Ability to suggest improvements
* Basic AI integration experience preferred

---

Please share:

* Your previous work (portfolio)
* Timeline for MVP
* Cost estimate
* Technologies you will use

Skills: Website Design, Graphic Design, 3D Rendering, AutoCAD, 3D Modelling, React.js, Web Development, AI Development

Job Description: Senior AI Engineer – Web Agent (Agentic Website Builder Platform)
Role Overview

We are seeking a highly skilled Senior AI Engineer / Agentic Systems Developer to build a Web Agent MVP capable of autonomously designing, generating, and deploying production-grade websites for small and medium businesses.

This role requires deep expertise in:

Full lifecycle website development
Agentic AI systems (multi-agent orchestration)
Modern web stack + backend integrations
Dynamic content generation and automation workflows

You will architect and build a Web Agent with specialized sub-agents that can:

Understand business requirements
Design UX/UI
Generate code
Integrate third-party services
Deploy and optimize websites
Core Objective

Build an intelligent “Website-in-a-box” AI system that can go from:

Business Idea → Requirements → Design → Code → Deployment → Optimization

Key Responsibilities
1. Architect the Web Agent (Core System)
Design and implement a multi-agent system using:
LangGraph / CrewAI / AutoGen (or similar)
Build a central orchestrator agent that coordinates sub-agents
Implement:
Task planning
Dependency handling
Iterative refinement loops
2. Build Specialized Sub-Agents
a. Requirement Agent
Interacts with user (chat or form)
Extracts:
Business type
Target audience
Features required
Converts inputs into structured specifications (JSON)
b. UX/UI Design Agent
Generates:
Wireframes
Design systems (colors, typography)
Creates:
Component-level structure (headers, hero, CTA, etc.)
c. Code Generation Agent
Generates production-ready code using:
React / Next.js
Tailwind CSS / component libraries
Ensures:
Modular architecture
Reusable components
SEO-friendly structure
d. Integration Agent

Handles integration with external services:

Email (SMTP, SendGrid)
SMS (Twilio or similar)
Social media APIs
CRM (Zoho, HubSpot)
Payment gateways (Stripe)

Also integrates:

Forms → backend → database → notifications
e. Backend & Data Agent
Designs backend using:
Supabase / Firebase / Node / FastAPI
Implements:
Database schema
Authentication
APIs
Uses:
Supabase Edge Functions for dynamic logic
f. Deployment Agent
Automates deployment to:
Vercel / Netlify / AWS
Handles:
Environment variables
Domain setup
SSL configuration
g. QA & Optimization Agent
Performs:
Performance checks
SEO audits
Accessibility validation
Suggests improvements and auto-fixes issues
3. End-to-End Workflow Orchestration

Design workflows like:

Requirement Agent gathers inputs
UX Agent creates design
Code Agent builds frontend
Backend Agent sets up APIs
Integration Agent connects services
Deployment Agent publishes site
QA Agent validates and optimizes

Implement:

Shared memory (vector DB / state store)
Versioning of generated assets
Feedback loop for continuous improvement
4. Build Dynamic Website Capabilities
Create CMS-like functionality using:
Supabase / headless CMS
Enable:
Dynamic content updates
Blog systems
Campaign landing pages
Use:
Edge Functions for real-time logic
5. Developer Experience & Tooling
Build reusable templates for:
Different industries (restaurant, healthcare, SaaS, etc.)
Enable:
Prompt-driven regeneration of sections
Component-level updates
Required Skills
Full Stack Development
Strong experience in:
React / Next.js
Node.js / Python
Experience building:
Production-grade web applications
Agentic AI Systems
Hands-on with:
LangGraph / CrewAI / AutoGen
Experience designing:
Multi-agent workflows
Tool-using agents
Integrations
Experience with:
Email APIs (SendGrid, SES)
SMS APIs (Twilio)
Payment gateways (Stripe)
CRM integrations
Backend & Data
Experience with:
Supabase (preferred)
PostgreSQL / NoSQL
Knowledge of:
Edge functions / serverless
AI/LLM
Strong experience in:
Prompt engineering
Function calling / tool usage
RAG (optional but preferred)
Nice to Have
Experience building:
Website builders (Wix, Webflow-like systems)
Knowledge of:
SEO best practices
Marketing automation
Familiarity with:
Design systems and UI frameworks
MVP Deliverables
Phase 1
Web Agent generates a fully functional website
Includes:
Contact forms
Basic integrations (email)
Deployment pipeline
Phase 2
Multi-agent orchestration
Dynamic CMS capabilities
Advanced integrations (CRM, payments, campaigns)
What “Great” Looks Like
User inputs business idea → gets a live deployed website in minutes
Website includes:
Dynamic backend
Integrated communication channels
Optimized design + SEO
Agents collaborate autonomously with minimal human intervention
Why This Role is Critical

You will be building the foundation of a fully autonomous digital business engine, where AI agents:

Replace traditional web development cycles
Reduce time-to-market from weeks → minutes
Enable SMBs to operate with enterprise-level digital capabilities

The Mission (Overview)
​We aren't just looking for a service provider; we are looking for a collaborator. Our goal is to [insert what you are trying to achieve, e.g., launch a disruptive fintech app / overhaul our brand identity]. This project is critical because [insert impact].
​2. Your Role & Deliverables
​We believe in clarity. Your success in this project will be defined by the following:
​Deliverable A: [e.g., High-fidelity wireframes for 12 screens]
​Deliverable B: [e.g., A fully documented API integration]
​Deliverable C: [e.g., Weekly progress reports and a final handover loom video]
​3. The Skill Set We Value
​To excel in this role, you should have mastered:
​Core Technicals: [e.g., React, Python, Adobe Suite]
​Problem Solving: The ability to find workarounds when "Plan A" fails.
​Attention to Detail: You’re the type of person who catches the double space in a paragraph or the missing semicolon in code.
​4. How We Work (Our Culture)
​Communication is our oxygen. Here is what to expect from us:
​Asynchronous First: We use [Slack/Trello/Notion] to stay organized. We don't believe in unnecessary meetings.
​The "No-Guessing" Policy: If you are stuck for more than 30 minutes, reach out. We value speed over "figuring it out alone" in a vacuum.
​Feedback Loop: We provide honest, constructive feedback within [24-48] hours of submission.
​5. Logistics & Timeline
​Duration: This is a [fixed-term/ongoing] project.
​Milestones: We operate on a milestone-based payment schedule:
​Phase 1: Research & Discovery (20%)
​Phase 2: Development/Drafting (50%)
​Phase 3: Final Review & Launch (30%)
​How to Apply
​Don't just send a generic cover letter. Tell us:
​One project you’ve done that is similar to this.
​What is your favorite tool for [insert specific task] and why?
​Include the word "[Blueberry]" at the top of your proposal so we know you read this entire description!
​Pro-Tip: If you actually tried to write 50,000 words, most talent would stop reading after the first 500. Quality and clarity always beat quantity when you're trying to hire the best.

We are seeking an experienced data analyst or developer to create a comprehensive port-to-port distance database focusing on key maritime routes, including Suez, Panama, Kiel, ECA, and piracy-affected areas. The goal is to produce accurate measurements and analytics similar to NETPAS and SignalOcean. The ideal candidate will have experience in maritime data, geographic information systems (GIS), and distance calculation algorithms. We need someone who can deliver reliable and precise distance information efficiently.

I want to calculate natural settlement/subsidence of road sections over a period of time such as 10 years. The methodology should follow such as EGMS data. I also prepare a workflow using chat GPT and attached for your reference. Though it is not 100% accurate, however, one can refer it for reference. Also, some GPT generated illustrations are attached for your reference. Results should be generated in combinations of these formats. Plz check and apply. Also see the EGMS data for understanding: https://egms.land.copernicus.eu/
The work includes the following:
1. Determination of settlement/subsidence of three road sections from India and Singapore each over a period of 10 years.
2. Perform all analysis and visualization to represent it better.
3. Handover all source codes and demonstration of the whole work.
The work should be done as per my satisfaction, The work will only be allotted after successful demonstration your ability in handling the work satisfactorily. Payment will only be released after completion of full work. No part payment of part work allotment. Apply only if you are confident.
The budget is 100 USD. Apply only if you can do this work properly. Successful completion of this work will allotment of such work directly in the coming future.

Discussed about my new ideas about my brand and application

We are exploring onboarding a data scientist to support ongoing AI/ML chat development efforts.

I’m looking for a freelancer to complete a small and straightforward machine learning task using Python.

The task includes:

Working with a provided dataset
Performing basic data cleaning and preprocessing
Applying a simple machine learning model (e.g., classification or regression using scikit-learn)
Evaluating the model (accuracy or similar metric)
Providing clean, well-commented code
Writing a short explanation of the approach and results

Requirements:

Experience with Python, pandas, and scikit-learn
Ability to deliver clean and understandable code
Quick turnaround (within 1–2 days)

I’m looking for a freelancer to complete a small and straightforward machine learning task using Python.

The task includes:

Working with a provided dataset
Performing basic data cleaning and preprocessing
Applying a simple machine learning model (e.g., classification or regression using scikit-learn)
Evaluating the model (accuracy or similar metric)
Providing clean, well-commented code
Writing a short explanation of the approach and results

Requirements:

Experience with Python, pandas, and scikit-learn
Ability to deliver clean and understandable code
Quick turnaround (within 1–2 days)

I’m setting up a smart gate barrier that runs on a Raspberry Pi and reports to a self-hosted ThingsBoard instance on my own virtual server. The job covers everything from wiring the Pi to the gate hardware right through to building a browser dashboard my staff can pull up on any PC.

Here’s what I need the finished system to do for me:
• Show the gate’s status in real time, with clear indicators for open, closed, or fault states.
• Let authorised users trigger OPEN / CLOSE remotely and see an immediate confirmation.
• Store a full access history—time-stamped events and which user issued each command.
• Present all of that data in a detailed dashboard: live widgets, trend graphs, charts, and a scrollable log panel.
• Send email and push notifications if the gate is forced, left open too long, or if the Pi or server drops offline.

Core tech is flexible as long as it’s reliable; MQTT, Python, Node-RED, or direct ThingsBoard integrations are all fine. The server is already provisioned (Ubuntu 22.04, root access ready). I’ll want clean code, commented where it matters, and a short deployment script so I can recreate the setup on a spare Pi if needed.

Deliverables
1. Raspberry Pi image (or Ansible/Bash script) that:
– Drives the gate relay and status sensors
– Secures connectivity to ThingsBoard with TLS

2. ThingsBoard installation on my VPS with:
– Custom dashboards matching the spec above
– Role-based logins for Administrator and Operator levels

3. Notification service configured for my SMTP and preferred push channel (Firebase or similar).

Acceptance criteria
• Command-to-action latency under 1 second on the local network.
• Dashboard widgets refresh every 2 seconds or faster.
• Access logs stored for minimum 90 days and exportable as CSV.

Hand-over includes all source files, documentation, and a quick Zoom walkthrough. If you’ve built similar IoT control systems, especially with ThingsBoard, I’d love to see a demo or screenshots when you bid.

2. Scope of Work
The Service Provider will:
1-Configure Raspberry Pi to communicate with ThingsBoard using MQTT
2-Implement gate open/close control logic on the Raspberry Pi
3-Integrate Raspberry Pi with the Client’s self-hosted ThingsBoard instance
4-Configure telemetry and server-side RPC for gate control
5-Create a functional ThingsBoard dashboard for client PC access
6-Implement basic reliability and safety handling (reconnects, command validation)
Provide documentation for setup, operation, and future extension

The Service Provider will deliver:
• Raspberry Pi application source code
• MQTT communication setup with ThingsBoard
• Configured ThingsBoard dashboards
• Basic wiring / interface guidance
• Setup and usage documentation

1.3D Graphic pages shall be prepared for the operation to monitor the status of each barrier.
2.The status of each Boom Barriers Open/ Close/ Trouble shall be displayed by change of colors.
3.The actual, real time operational status of each Boom Barrier shall be displayed on the graphic page.








4.The Alarms shall pop up on the screen.
Please prepare the following graphic pages in the system, not limited to:
a. Home Page Graphic
b. Cluster Wise Graphic Pages
c. Basement Wise Graphic Pages
6. Each page must include fully functional navigation buttons, including:
a. Home
b. Next
c. Previous
d. Back (if required)
e. Cluster Selection (for relevant pages)
f. Basement Selection (for relevant pages), etc.,


5.Contractor to prepare and submit the technical document for the 3D Graphic pages and obtain all approvals.
6.Floor plan graphic pages shall be developed to clearly display all access control and traffic management equipment installed on each level. The graphics must include accurate placement and labeling of the Boom barriers, etc., devices on the layout.
It shall also be possible to group the barriers/blockers to open/close them.

Skills: Python, Linux, Cloud Computing, MQTT, Home Automation, Raspberry Pi, Web Development, Embedded Systems, Data Visualization, Ansible

NB - Proposals Above $550 will be considered if the justification is specific and the portfolio is strong.

I am the founder of Trayce, a healthcare inventory management startup. We are building a plug-and-play smart cabinet kit that retrofits onto existing hospital and clinic supply cabinets — adding controlled access, staff identity tracking, and AI-powered item documentation without replacing the cabinet or requiring any permanent modifications.

I need an experienced Raspberry Pi / embedded systems developer to assemble, wire, and program a fully functional hardware prototype using a pre-sourced parts list. All components are consumer-grade, widely available, and chosen specifically for ease of build. No custom PCB design is required. No specialist equipment is required. Everything on the parts list is available on Amazon.

This is a milestone-based fixed-price engagement. If the prototype is successful, there is likely clear path to an ongoing relationship covering v2 hardware development, production-grade engineering, and a potential longer-term role as hardware lead for the company.

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BACKGROUND — WHAT TRAYCE IS
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Hospitals lose significant revenue and operational efficiency because supply consumption at the point of use is poorly tracked. Nurses remove items from cabinets with no automatic record of what was taken, by whom, or when. Stock levels become unreliable, items expire unnoticed, and procurement teams reorder reactively rather than proactively.

Trayce solves this with a two-part retrofit kit that clips onto any existing cabinet. A staff member taps their ID badge to unlock the cabinet. Cameras capture what is removed. AI identifies each item — including barcode, lot number, and expiry date. All of this data is sent wirelessly to a cloud dashboard that gives procurement teams real-time visibility into stock levels, expiry risk, and reorder needs.

The target market is hospitals, clinics, and ambulatory surgery centers that cannot afford or implement incumbent solutions like Pyxis or Omnicell, which cost $30,000–$80,000 per cabinet. Trayce is designed to deliver most of the value at a fraction of the cost and in a fraction of the implementation time.

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HARDWARE SYSTEM — WHAT YOU ARE BUILDING
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The system consists of two physical modules:

── MODULE 1: EXTERNAL ACCESS MODULE (EAM)
Mounts on the outside face of the cabinet. Contains:

── MODULE 2: INTERNAL INTELLIGENCE MODULE (IIM)
Mounts on the inside top front edge of the cabinet. Contains:

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PROJECT DETAILS
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Project type: Fixed price, milestone-based
Estimated duration: 3–5 weeks
Location: Remote — all components shipped to your location at client's expense
Communication: Weekly video check-in + async updates via Upwork messages
Code ownership: All code, wiring documentation, and README become property of the client on final milestone payment
Followup opportunity: v2 hardware development and production engineering if prototype succeeds

MILESTONE STRUCTURE:
- Milestone 1 — 25%: Physical assembly complete, RFID multi-mode access working, LED state machine working, lock opens and closes correctly on tap and hold
- Milestone 2 — 30%: Both cameras active on door open, AI vision pipeline identifying items, barcode and OCR reading functional, all data logged locally to SQLite
- Milestone 3 — 25%: Supabase sync working, offline queue working, full system integrated and boots automatically via systemd on power-on
- Milestone 4 — 20%: README and admin guide delivered, demonstration video delivered, code reviewed, commented, and cleaned

Payment is released per milestone on receipt of a working demonstration of that milestone's deliverables. Video evidence of each milestone is acceptable for remote verification.


Deliverables:
1. Physical Assembly & Wiring — Wire, mount, and connect all components across both enclosures, including cameras, lock circuit, reed switch, NeoPixel ring, and inter-module cable, with all connections labelled and documented in a simple wiring diagram.

2. RFID Multi-Mode Access Control — Python script implementing hold-duration mode detection, local SQLite authorization lookup, MOSFET lock control, full 13-state NeoPixel LED state machine, door sensor integration, emergency override logic, and complete access event logging.

3. Camera Activation & AI Vision Pipeline — Both cameras activate on door open via reed switch trigger, running parallel AI inference for barcode decoding, OCR lot/expiry extraction, and visual product classification via Google Coral, with all identified items packaged into a structured JSON object per session.

4. Supabase Data Sync with Offline Queue — Session JSON pushed to Supabase on door close over WiFi, with failed or offline events queued locally to the Samsung T7 SSD and automatically synced in order with original timestamps preserved when connectivity is restored.

5. System Integration & Auto-Start — All scripts integrated into a single cohesive system with systemd service files ensuring automatic boot on power-on, correct dependency ordering, graceful shutdown handling, and all configuration managed through a single documented .env file.

6. Plain-English README & Admin Guide — A non-technical operations document covering how to add or remove staff cards, connect to WiFi, check system health, restart services, interpret every LED state, troubleshoot a cabinet that will not open, and monitor battery status.

7. Demonstration Video — A 5–10 minute video showing the complete working system across all three access modes, a denied card tap, an offline-then-sync sequence, and an automatic restart after power cycle, with session data visibly appearing in Supabase at the end.

• Describe at least one physical Raspberry Pi project you have built and delivered. Be specific: what did it do, what components did you use, what was the outcome, and did you write all the code yourself? A GitHub link or photo is a strong plus.
• Explain in one or two sentences how you would wire the solenoid lock MOSFET control circuit safely — specifically whether you would use a flyback diode, what type, and why.
• Do you have working experience with TensorFlow Lite models on Raspberry Pi, the Google Coral USB Accelerator, or both? If not, be honest about it. Strong GPIO and camera skills with limited Coral experience is an acceptable combination..
• Provide your proposed timeline broken down by milestone. Be realistic.
• What questions do you have about the project before starting?

Job Description
I’m seeking an experienced Power BI / Power Query specialist to correct numerical inaccuracies in an existing Power BI report.

Background (Context Only)
This Power BI report previously produced correct invoice and revenue figures.
Following a transfer of ownership and data refresh of source files, figures became inflated.

The root cause has already been identified:
duplicate rows introduced during Power Query → Combine Files expansion.

The objective is to restore the report to its previously correct state, using the existing model and visuals.

This is a corrective task, not an exploratory or redesign exercise.

Confirmed Issue Summary
Power BI loads multiple Excel invoice files via folder-based Combine Files
After expansion, identical invoice rows are duplicated many times
Same invoice line (same title, dates, amount, fee type) appears repeatedly
This causes invoices and revenue to be massively overstated
Duplication is visible in Power Query → final expanded fact table (e.g. Expanded Data1)
Scope of Work – Phase 1 (Fixed and Limited)
In scope:

Review Power Query Combine Files logic
Remove unintended duplicate invoice rows introduced during expansion
Ensure one row per logical invoice line in the final fact table
Preserve existing PBIX structure, relationships, visuals, and refresh behaviour
Validate fix using:
Invoice‑level spot checks
Monthly revenue reasonableness checks
Explicitly out of scope:

Model redesign or re‑architecture
Visual redesign
Broad DAX refactoring (unless strictly required for validation)
“Best practice” or optimisation review
Discovery of unrelated issues
Deliverables
Updated PBIX with corrected invoice and revenue figures
Brief explanation of:
where duplication occurred
what was changed to fix it
Engagement Boundary
Any additional issues identified should be noted only and proposed separately after Phase 1 is complete.

Ideal Experience
Strong Power Query expertise
Proven experience with Combine Files / folder sources
Comfortable fixing duplication at the data grain, not via visual or DAX workarounds

This is a time‑sensitive corrective task; quick availability is strongly preferred.

• Describe your recent experience with similar projects
• Please list any certifications related to this project

We are seeking a full-time CLAUDE Code expert to develop AI agents using n8n and other applications. The ideal candidate will have experience in building and integrating AI solutions, with a strong understanding of automation workflows. Responsibilities include designing, implementing, and optimizing AI agent systems to enhance business processes. If you have a passion for AI and automation, we would love to hear from you!

• Describe your recent experience with similar projects

I’m looking for an experienced scraper who can extract data from 1,000,000+ Trustpilot pages.

Scope of work:

Crawl Trustpilot at scale
Extract for each listing:
Trustpilot URL
Domain name (reviewed website)
Rating (score)
Email (if available / scraped from website)

Requirements:

Proven experience with large-scale scraping (1M+ pages)
Ability to handle anti-bot / rate limits / proxies
Clean, deduplicated dataset
Delivery in CSV

Budget:
💰 Fixed: $50 for this task

Role Summary

Build multi-agent systems that turn data intelligence into automated, client-facing workflows. You will design and implement agentic architectures that make measurement models, data pipelines, and media optimization tools accessible through natural interfaces. The goal: solutions that are cheap to build, cheap to run, and easy for non-technical teams to use.

Key Responsibilities

· Design and build multi-agent systems using LLM orchestration frameworks (LangChain, LangGraph, CrewAI, or custom)
· Implement AI orchestration use cases for 4+ clients, focusing on low external dependency scenarios
· Build agentic wrappers around existing data science models (MMM, forecasting, RBA, incrementality) so they can be queried and used conversationally
· Set up and configure Genie spaces for client data exploration and self-service analytics
· Develop tool-use patterns that connect agents to Databricks, Power BI, and other platform APIs
· Write production-grade Python code with proper error handling, logging, and monitoring
· Collaborate with Data Scientists to understand model inputs/outputs and build reliable agent interfaces
· Participate in architecture reviews and contribute to the team's agentic design patterns and reusable components


Required Qualifications

· 5+ years of software engineering experience with strong Python skills
· 2+ year hands-on experience building with LLMs (prompt engineering, RAG, function calling, agent frameworks)
· Experience with at least one agent orchestration framework (LangChain, LangGraph, AutoGen, CrewAI)
· Understanding of API design, microservices, and event-driven architectures
· Experience with cloud platforms (Azure preferred)
· Familiarity with vector databases, embeddings, and retrieval-augmented generation patterns
· Strong debugging and problem-solving skills in distributed systems
· Comfort working in a fast-moving team that ships iteratively


Preferred Qualifications

· Experience with Databricks and/or Genie
· Background in media, advertising, or marketing technology
· Experience building conversational interfaces or chatbot systems
· Familiarity with MLOps practices and model serving infrastructure
· Open-source contributions or personal projects demonstrating agentic AI work

I can’t write a description for a service that automates or manipulates appointment booking systems (like BLS booking bots or bypass tools).

But I can give you a clean, Fiverr-safe, professional gig description for a legitimate “appointment assistance & automation helper” service that you can safely sell.

Here’s a ready-to-copy version:

Appointment Booking Assistant | Automation & Form Filling Helper
Description

Are you struggling with slow and complicated online appointment systems? I will help you streamline and simplify the process using a smart and efficient automation assistant that saves you time and reduces errors.

This service is designed to assist users with appointment preparation, form filling, and availability monitoring in a legal and safe way.

What I offer:

✅ Automated form filling assistance (user-side tools)
✅ Fast and accurate data entry setup
✅ Appointment availability tracking system
✅ Notifications when new slots are available
✅ Step-by-step booking guidance
✅ Error detection and troubleshooting support
Features:
Simple and easy-to-use interface
Lightweight automation scripts
Helps reduce manual work and mistakes
Works with most appointment websites
Fully compliant with website rules (no bypass or hacking)
Why choose this service?

✔ Saves time and effort
✔ Reduces human errors during booking
✔ Improves chances of getting appointments faster (legally)
✔ 100% safe and compliant approach
✔ Custom setup based on your needs

Packages:

Basic: Form filling assistant setup
Standard: + availability tracker + notifications
Premium: Full automation assistant + custom workflow + support

Important:

This service does NOT bypass security systems, captchas, or website protections. It is strictly designed for productivity and assistance within legal and ethical boundaries.

Skills: PHP, Python, Website Design, Data Entry, WordPress, HTML, Web Development, Automation, API Integration

Computer Vision Engineer (TensorFlow Preferred) — 6-Month Contract

Job Type: Full-time (40 hours/week)
Start Date: ASAP

About Us

We are a fast-growing US-based healthcare AI startup expanding globally. Our mission is to end preventable blindness by enabling early detection of vision-threatening diseases using advanced imaging and AI.

We are building cutting-edge Explainable AI (XAI) systems that deliver clinically meaningful insights with transparency and trust.

Recognition & Momentum

Named one of Georgia’s Top 10 Most Innovative Companies (2025)
Collaborations with leading research ecosystems (e.g., Georgia Tech)
Backed by leading AI/cloud ecosystems including Microsoft and NVIDIA
Rapid expansion across new markets, customers, and product capabilities
Role Summary

We are hiring a Computer Vision Engineer with strong deep learning expertise and proven ability to build production-grade ML systems on AWS.

This is a high-ownership, fast-paced role with significant growth potential. You will work directly with leadership, with high visibility and real impact on product direction and execution.

Key Responsibilities
Build and improve computer vision models for:
Classification (including multi-label)
Object detection
Segmentation
Image quality assessment / quality gating
Implement and fine-tune modern deep learning architectures:
EfficientNet, ConvNeXt
Vision Transformers (ViT, Swin)
Own evaluation and reporting:
F1, AUROC, sensitivity/specificity
Threshold tuning, error analysis, experiment tracking
Data management & data engineering (critical):
Design and maintain dataset pipelines (ingestion, cleaning, normalization, deduplication)
Dataset versioning, lineage, and train/val/test strategy
Labeling workflows, metadata management, and quality checks
Build reproducible data + training pipelines
Build scalable ML workflows on AWS
Productionize models (as needed):
TensorFlow Serving / TF-TRT / TFLite
TorchScript / ONNX (plus)
Latency and throughput optimization
Maintain strong engineering standards:
Clean code, Git workflows, documentation
Unit and integration testing
Required Qualifications
3+ years experience in computer vision / deep learning (or strong portfolio)
TensorFlow 2.x / Keras preferred; working knowledge of PyTorch
Strong Python skills
Strong understanding of CV modeling best practices (augmentation, imbalance handling, losses)
Strong evaluation experience (F1, AUROC, sensitivity/specificity, calibration)
AWS experience required: S3, EC2, IAM, CloudWatch
Strong data engineering experience for ML pipelines
Solid software engineering fundamentals (testing, code quality, Git)
Preferred Qualifications
AWS SageMaker, ECR, ECS/EKS, Step Functions, Terraform
MLOps: experiment tracking, model registry, drift monitoring
Explainability methods: Grad-CAM, saliency maps, attention visualization
Medical imaging exposure (bonus): DICOM / DICOMWeb, clinical workflows
Why Join Us
Work on real-world healthcare AI problems with global impact
High visibility and direct collaboration with leadership
Fast growth environment with strong career upside
Opportunity to convert into a full-time role

We are seeking a dedicated professional eager to embrace a challenging role that focuses on enhancing their skills in a supportive and collaborative environment. This position is ideal for individuals who thrive on teamwork and are passionate about personal and professional growth. You will have the opportunity to work closely with other talented individuals, contributing to innovative projects and sharing your expertise. If you're ready to take your skills to the next level, we want to hear from you!

Role Summary

Serve as the technical anchor for agentic AI engineering team. You will lead architecture decisions for multi-agent systems, set engineering standards, and mentor a growing team of agentic engineers. This is a hands-on leadership role: you write code, review code, and set the technical direction while the Senior Director handles the VP-level strategy and stakeholder management.

Key Responsibilities

• Lead technical architecture for multi-agent systems, LLM orchestration, and AI automation workflows
• Set up and maintain the agentic engineering stack: frameworks, CI/CD, testing, monitoring, and deployment patterns
• Own the technical design for AI orchestration use cases across 4+ client implementations
• Build and maintain reusable agent components, tool-use libraries, and prompt templates
• Lead Genie space setup and configuration for client data exploration
• Mentor and technically lead 3 Senior Agentic Engineers, conducting code reviews and architecture discussions
• Evaluate LLM providers (model selection, cost optimization, latency tradeoffs) and recommend choices
• Bridge the gap between Data Science model outputs and agentic deployment, ensuring models are served efficiently
• Collaborate with the onshore Senior AI Engineer on shared architecture decisions and technical standards
• Contribute to technical documentation, runbooks, and operational playbooks for the agentic platform


Required Qualifications

• 7+ years of software engineering experience with at least 2 years in AI/ML engineering
• Deep expertise in Python and production-grade software architecture
• Hands-on experience building and deploying LLM-powered applications at scale
• Strong knowledge of agent orchestration patterns (LangChain, LangGraph, AutoGen, or custom frameworks)
• Experience with cloud infrastructure (Azure preferred) including container orchestration and serverless patterns
• Track record of mentoring engineers and raising team engineering standards
• Experience with MLOps: model serving, monitoring, versioning, and cost management
• Strong system design skills with experience in distributed systems and API architecture
• Excellent written communication for technical documentation and cross-timezone collaboration


Preferred Qualifications

• Experience with Databricks, Unity Catalog, and/or Genie
• Background in media technology, adtech, or marketing analytics platforms
• Experience with RAG architectures, vector databases, and semantic search at scale
• Contributions to open-source AI/ML projects
• Experience leading technical teams in a offshore delivery model

WhatsApp Voice AI Bot (Multi-language, n8n + OpenAI + WATI)

Project Overview:
We are building a production-level WhatsApp Voice AI system for a ride-hailing company with 900+ drivers. The system must support voice-first communication, multiple local languages, and a combination of structured workflows + AI responses.
This is not a basic chatbot we need a scalable, reliable conversational system.
Scope of Work:
1. WhatsApp Integration (WATI)
Setup WATI and connect WhatsApp Business API numbers
Configure webhooks (send/receive messages)
Support multiple numbers with shared backend
2. Voice AI Pipeline
Voice input → Whisper transcription (Urdu, Pashto, Punjabi, Saraiki)
AI processing (GPT-4o / Claude)
Text → Urdu voice (TTS)
Voice input → voice + text reply
Text input → text reply only
3. Intent Routing System
Build structured flows for:
Driver registration (multi-step)
Bonus/payment queries
Top-ups
Ride/account issues
Office info + FAQs
Angry drivers → instant escalation
4. Hybrid Logic (Flows + AI)
Fixed flows for critical processes (registration, payments, escalation)
AI for general queries (KB-based only, no hallucination)
5. Session & Context
Maintain per-driver conversation memory
Handle multi-step interactions
6. Escalation System
Detect frustration or critical cases
Generate ticket ID
Send full transcript to support via WhatsApp
Allow human agent to continue conversation
7. Reliability
Voice reply must always work (fallback TTS required)
Error handling + retries
Low response time
8. Architecture
n8n (or Make) for workflows
Optional Python for logic/scaling
Design for scaling (100 → 500 msgs/day)
Deliverables:
Fully working WhatsApp AI system
Voice input/output pipeline
Intent routing + flows
Escalation + alerts
KB integration
Tested with real users
Requirements:
Experience with WATI/Twilio (WhatsApp API)
OpenAI / Claude integration
Whisper + TTS experience
n8n / Make workflows
Strong backend/system design
Notes:
Voice UX is critical (low-literacy users)
Focus on reliability and clean architecture
Long-term work possible after delivery
Timeline Total: (12 days)
Part 1: 5 Days
Part 2: 7 Days
Budget full and final:
$100 NZD

Skills: PHP, Translation, Voice Talent, Hindi Translator, Backend Development, Chatbot, API Integration, OpenAI, Conversational AI, n8n

WhatsApp Voice AI Bot (Multi-language, n8n + OpenAI + WATI)

Project Overview:
We are building a production-level WhatsApp Voice AI system for a ride-hailing company with 900+ drivers. The system must support voice-first communication, multiple local languages, and a combination of structured workflows + AI responses.
This is not a basic chatbot we need a scalable, reliable conversational system.
Scope of Work:
1. WhatsApp Integration (WATI)
Setup WATI and connect WhatsApp Business API numbers
Configure webhooks (send/receive messages)
Support multiple numbers with shared backend
2. Voice AI Pipeline
Voice input → Whisper transcription (Urdu, Pashto, Punjabi, Saraiki)
AI processing (GPT-4o / Claude)
Text → Urdu voice (TTS)
Voice input → voice + text reply
Text input → text reply only
3. Intent Routing System
Build structured flows for:
Driver registration (multi-step)
Bonus/payment queries
Top-ups
Ride/account issues
Office info + FAQs
Angry drivers → instant escalation
4. Hybrid Logic (Flows + AI)
Fixed flows for critical processes (registration, payments, escalation)
AI for general queries (KB-based only, no hallucination)
5. Session & Context
Maintain per-driver conversation memory
Handle multi-step interactions
6. Escalation System
Detect frustration or critical cases
Generate ticket ID
Send full transcript to support via WhatsApp
Allow human agent to continue conversation
7. Reliability
Voice reply must always work (fallback TTS required)
Error handling + retries
Low response time
8. Architecture
n8n (or Make) for workflows
Optional Python for logic/scaling
Design for scaling (100 → 500 msgs/day)
Deliverables:
Fully working WhatsApp AI system
Voice input/output pipeline
Intent routing + flows
Escalation + alerts
KB integration
Tested with real users
Requirements:
Experience with WATI/Twilio (WhatsApp API)
OpenAI / Claude integration
Whisper + TTS experience
n8n / Make workflows
Strong backend/system design
Notes:
Voice UX is critical (low-literacy users)
Focus on reliability and clean architecture
Long-term work possible after delivery
Timeline Total: (12 days)
Part 1: 5 Days
Part 2: 7 Days
Budget full and final:
$100 NZD

Skills: PHP, Translation, Voice Talent, Hindi Translator, Backend Development, Chatbot, API Integration, OpenAI, Conversational AI, n8n

Job Title: Head of Applied AI (Automotive)

Location: UK (Hybrid – Manchester preferred)

Overview
We are building an AI-driven automotive platform similar, where instant, data-led vehicle valuation and condition assessment are critical to our business.

We are looking for a senior AI leader to define and deliver AI systems across vehicle valuation, diagnostics, and customer experience.

What you will own

AI strategy across the business, from valuation to customer operations
Delivery of production AI systems (not just pilots)
Vendor management (e.g. OBDII / scanning partners)
Building and leading a small, high-impact AI team

Key projects

Vehicle valuation models (pricing, demand forecasting)
AI-based condition detection (cosmetic + damage via images)
OBDII / vehicle diagnostics interpretation (incl. EV readiness)
Spec & vehicle data enrichment
OCR & document intelligence
Customer service AI & retail communications

What we’re looking for

Experience leading AI / Data Science teams in production environments
Strong background in pricing, marketplaces, mobility, or automotive
Proven delivery of real-world ML systems (not just research)
Ability to work with messy, real-world data
Experience managing vendors and deciding build vs buy

Nice to have

Computer vision (image-based detection)
Vehicle / telematics / IoT data experience
Experience with auction, resale, or automotive platforms

Why join us

Direct impact on revenue and core business decisions
Greenfield opportunity to build AI capability from the ground up
High ownership and visibility at leadership level

Compensation
Flexible depending on experience (£120k–£180k+)

• Describe your recent experience with similar projects
• Please list any certifications related to this project
• What tools do you use for data mining and visualization?