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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
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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, Amazon CloudFront seems to be more popular. It has been mentiond 87 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.
Using a Content Delivery Network (CDN) like CloudFront to serve static assets faster. - Source: dev.to / 3 months ago
Semantic Caching: Cache similar queries' results using result fingerprinting. Edge caching via Amazon CloudFront for reduced latency. - Source: dev.to / 3 months ago
CloudFront may sound like Cloudflare, but it is an unrelated AWS service (https://aws.amazon.com/cloudfront/) (Disclaimer: I work for Cloudflare, which is not CloudFront). - Source: Hacker News / 3 months ago
In this post we are using an Amazon EC2 T3 Micro instance running Ubuntu with an nginx web server. We'll use AWS Systems Manager to help set up a CI/CD pipeline using GitHub Actions. We'll then configure AWS Certificate Manager with Amazon CloudFront and have it connected to our domain with Amazon Route 53! We'll be using a Vue Nuxt 4 application as our web app. - Source: dev.to / 5 months ago
A best practice for your web applications is to use Amazon S3 to store content and Amazon CloudFront to deliver it to users and protecting your data at rest and in transit. Encryption is one of protection controls AWS provides you to reduce the risks of unauthorized access, loss, or exposure. In this blog post, you will learn how to implement one of these options (SSE-KMS) in S3 when using CloudFront for content... - Source: dev.to / 6 months ago
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Reducto - Reducto is the complete agentic document platform for leading AI teams needing performance at enterprise scale.
KeyCDN - KeyCDN is a high-performance Content Delivery Network (CDN). Lowest price globally at $0.04/GB with HTTP/2 Support and free Origin Shield.
Mindee - Extract any data point, from any document, in a second
CDN77 - Content Delivery Network - website speed acceleration with CDN77. 28+ PoPs, Pay-as-you-go prices, no commitments.
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.
