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Parseflow.tech
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ParseFlow is a document parsing API that converts PDFs, DOCX files, and plain text into structured, evidence-backed JSON output for developers, automations, and AI workflows.
Unlike tools that return opaque extracted values, ParseFlow includes evidence metadata with every result โ confidence scores, source character offsets, and evidence snippets showing exactly where each value came from. This makes output easier to verify, debug, and trust in production.
Key features: - Structured JSON extraction with evidence spans - Table-aware chunking with presets for RAG, summarization, and extraction - Async jobs and batch processing - LangChain and LlamaIndex adapters - MCP / OpenClaw tooling support - BYOK for advanced extraction with your own model provider keys - Free deterministic tier for evaluation
Best use cases: invoice processing, contract clause extraction, receipt parsing, document intake pipelines, RAG preprocessing, AI workflow integration.
Built by a student. Priced for builders and small teams.
Free deterministic tier available. Starter: $10/month Growth: $15/month
Docs: docs.parseflow.tech
Atlassian Design
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Parseflow.tech's answer:
Parseflow is built for solo devs and small teams. Unlike competitors, Parseflow has a simple set up and usage and is much more affordable compared to enterprise options while offering the same features and quality.
Parseflow.tech's answer:
As a student, AI chatbots and LLMs would always struggle to understand correctly my school homework and documents. To fix this, I built Parseflow to help improve the context for AI models simply to help me complete my homework. Today, Parseflow has become a finished product that can parse, chunk and organize all types of documents to improve context and reduce token usage.
Parseflow.tech's answer:
Parseflow is completely built with Python.
Based on our record, Atlassian Design seems to be more popular. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
As the official evolution of react-beautiful-dnd, this library also comes with extensible accessibility features right out of the box. The default assistive controls are based on the Atlassian Design System, so if youโre already using that, integration will be seamless. But if you arenโt, you can easily replace those components with your own, or completely redefine how accessibility is provided and take a more... - Source: dev.to / over 1 year ago
Atlassian Design System: Atlassian's Design System encompasses a color module encompassing primary, secondary, and functional colors, along with an extended palette for shades and tints. The system provides comprehensive guidelines for effective color usage and emphasizes accessibility. - Source: dev.to / almost 3 years ago
Atlassian design system: https://atlassian.design/. Source: about 3 years ago
Regarding discoverability, you could build a directory with documentation. Similarly to how design systems are documented, e.g: https://atlassian.design/ But if you really want to share them you'll probably need to evangelize it somehow. Source: over 3 years ago
Step 5: Study design system Atlassian design system Primer design system Spectrum, Adobeโs design system Carbon design system. - Source: dev.to / over 3 years ago
Design Principles - An open source repository of design principles and methods
Reducto - Reducto is the complete agentic document platform for leading AI teams needing performance at enterprise scale.
Facebook Design - Resources for Designers from the Facebook Design team
Mindee - Extract any data point, from any document, in a second
Colorbox.io - Create accessible color systems ๐จ
ABBYY - ABBYY's leading AI and machine learning technology solutions range from process analysis, data capture, pdf editor, text and content recognition (OCR) and extraction, combining process and content insights to deliver digital intelligence.