Process Street
Kissflow
Pipefy
ifttt
Apache Airflow
Make.com
Pushwoosh
Tallyfy
Parseflow.tech
Reducto
Mindee
ABBYY
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, Process Street seems to be more popular. It has been mentiond 7 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.
The only thing I found is process.st but itโs a paid service. Source: about 3 years ago
So far I am working on the idea of workflow saas app, something like notion + process.st, but much simpler to use. I haven't done any wireframes or design yet. I am just at initial stage of exploring this area. Source: about 3 years ago
I'm using process street. It can trigger different workflows using links + having a conditional workflow. Source: almost 4 years ago
I took a look at process.st, it's more oriented towards office workers, whereas we're targeting in-the-field activities (take a photo, send an SMS, etc.). Source: almost 4 years ago
> I want that temporally and semantically linked set of activities to appear on a timeline with links to and from the various tools I use Sounds like what you want is a repeatable, digital workflow. Using workflow software like Process Street (https://process.st) you can build that documentation as part of performing the work itself. You could capture, say, the AWS policies you create and the ARNs theyโre... - Source: Hacker News / over 4 years ago
Kissflow - Kissflow is a workflow tool & business process workflow management software to automate your workflow process. Rated #1 cloud workflow software in Google Apps Marketplace.
Reducto - Reducto is the complete agentic document platform for leading AI teams needing performance at enterprise scale.
Pipefy - Pipefy is a process management software that empowers anyone to create and automate efficient workflows on their own without code.
Mindee - Extract any data point, from any document, in a second
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
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.
