
Canny.io
Upvoty
UserVoice
Featurebase
productboard
Nolt.io
Frill
BareMetrics
Parseflow.tech
DocParser
Nanonets
Reducto
Parseur.com
DocuClipper
Mindee
Klippa
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 — 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
Canny.io
Parseflow.techProduct managers, software development teams, startups, and companies that want to engage their user base in the feedback process and prioritize feature development based on real customer input.
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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, Canny.io seems to be more popular. It has been mentiond 43 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.
So I have been looking at what already implements it. Canny and Featurebase both do dedup, but their pricing scales with tracked users or admin seats. Fider is open source but is a feedback board only, with no roadmap or changelog attached. FeedLog is the closest to what I described here: MIT licensed, self-hostable, and it runs the similarity search at input time rather than as a batch job, which is the part I... - Source: dev.to / 22 days ago
What's the difference between this and like https://canny.io/ ? - Source: Hacker News / over 1 year ago
This is a slightly different feature set, but being more customer feedback centric rather than OKR centric might be worth considering: https://canny.io/. Source: over 2 years ago
Solutions like canny.io makes >$2M in ARR. My aim is to create product combining some features from canny and wiredash. Source: over 2 years ago
Researched the market and found https://wiredash.io/ - which is great tool, but it costs so much. 99 usd monhtly is.... 5 hours of work in Poland, where I live. Also I want to share project roadmap with my users inside it. Something like https://canny.io/ integrated into app. Source: over 2 years ago
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