Budget: 1000 USD Deadline: 10 days
Hello!
I am ready to take on the task quickly and efficiently. I am always available and will promptly consider all requests.
Budget: 700 USD Deadline: 7 days
Hello, there is a similar bot for Telegram that recognizes purchase receipts (any), categorizes them into predefined categories + according to its own understanding. Google OCR + Gemini AI. Accuracy 99.99%. Recognition speed up to 2 seconds. I can show an example. We need to discuss the details of the project, what has already been done.
Budget: 1500 USD Deadline: 4 days
Smart OCR Module — Business Proposal
My name is Christopher Bruce, founder of ActuarialOS, a financial analytics and software engineering company focusing precisely on this kind of challenge. I propose an architecture f your OCR System as a proposal.
We propose a Smart OCR Module to automate the input of expense data from receipt photos, delivering a seamless, production-ready, and scalable solution. At its core, the system is dataset-driven, extracting a canonical structure per receipt: {Amount, Date, Category} + metadata + user validation. This dataset is the backbone of all operations.
The module includes:
Capture & Guidance UI: Real-time camera feed with overlay frame; frame turns green when the receipt is aligned, focused, and well-lit; guides users to capture high-quality images.
Quality Assessment Engine: Evaluates blur, skew, and lighting; provides feedback to ensure only usable images proceed.
OCR & Field Extraction Engine: Recognizes amount, date (including Hebrew formatting), and optional metadata; outputs structured data with per-field confidence scores.
Category Classification: Assigns each expense to predefined categories (Food, Transport, Clothing, Leisure, Utilities, Children, Other) with confidence scoring.
User Validation Layer: Populates recognized fields for review and correction; updates the canonical dataset with validated values.
Integration Layer: Secure APIs connect frontend, backend, and main system; supports scalability, batch processing, and analytics pipelines.
The system is modular and extensible: new categories, layouts, languages, or metadata can be added without altering the core engine. Confidence scores, error logging, and user validation ensure high accuracy, while structured outputs integrate seamlessly into financial analytics, accounting, or reporting systems.
Deliverables: fully implemented Smart OCR engine, frontend capture and validation interface, backend recognition and classification, structured dataset outputs, and integration-ready API. The solution is scalable, robust, and user-centric, turning every receipt photo into actionable, validated expense data.
I can deliver this rapidly, in 7 four days. I have the expertise and the streamlined workflows to accomomdate.
Sincerely, Christopher
Budget: 700 USD Deadline: 2 days
Good day, I will write Smart OCR for you. I have experience in writing OCR for bank statements, everything works quickly and accurately with the integration of Azure OCR + OpenAI GPT-4 in the client's startup. Please contact me, we will discuss the details. I will be happy to collaborate.
Budget: 10000 USD Deadline: 12 days
Hi,
I can build the Smart OCR module to capture receipt photos, check quality, and extract amount, date, and category.
I have experience integrating recognition systems and validating data with user-friendly UI/UX.
I can ensure the extracted data is correctly populated and allow users to confirm or edit it.
I am confident in delivering a reliable and accurate solution for your platform.
Best regards,
Budget: 400 USD Deadline: 2 days
Hello! I am ready to complete this project and have extensive experience in developing various applications.
Budget: 800 USD Deadline: 7 days
Hello!
We will create the Smart OCR module for $800 within 7 days.
We already have experience in developing systems with image recognition, browser automation, and security solutions. We implement a full cycle:
— optimization of image capture with framing and autofocus (green indication of photo quality),
— assessment of photo quality and user notification,
— recognition of the amount and date on the receipt (including support for Hebrew),
— automatic classification by expense categories (food, transport, utilities, etc.),
— filling in the relevant fields and user verification.
We will provide a user-friendly UI/UX and a stable server side with expansion for future features.
