
Upvoty
UserVoice
productboard
Nolt.io
Frill
BareMetrics
FeedBear
Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.

DocAcquire
Upload PDFs, office docs, or scans, describe the data you need in plain language, and get a spreadsheet, CSV, or JSON back. No manual entry, no brittle templates.

Which is more popular?
Based on our record, Canny.io seems to be more popular. It has been mentioned 43 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | canny.io | stract-api.com |
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| Platforms | — | |
| Company | Startup from Canada | Startup from the United States · 1 - 9 employees · 2026 |
| Listed in |
What each product offers, as listed by its team.


Possible disadvantages
No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Product 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.
No analysis of Stract API yet.
Walkthroughs and reviews on video.
How to Collect Customer Feedback Using Canny.io
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Canny.io and Stract API.
Stract API's answer:
Legal services and title companies are growing segments for Stract API
Stract API's answer:
The primary technologies used in build Stract API are LLMs, Typescript, React, and Java.
Stract API's answer:
Stract API is different because it lets the people closest to the questions get answers straight from their documents, with no templates, no custom tooling and no manual data entry. You upload your files, describe the data you need in plain language, and Stract API runs every document in the batch from start to finish. It returns clean, structured results you can put to work right away. You choose the model that fits the job, from fast, economical options for high-volume work to the newest, most capable LLMs for your highest-stakes analysis. Under the hood, it draws on techniques from the latest AI research to improve the quality of what gets extracted. The same analysis costs less than 10% of the equivalent staff time, so your team can skip the grind and go straight to analysis. And because sensitive work is the norm for many of your users, Stract API is fully SOC2 compliant, so your documents stay yours.
Stract API's answer:
A person should choose Stract API over its competitors because it gets them from a pile of documents to usable data with the least effort and risk. They describe what they need in plain language, so they don't build templates or learn a tool's vocabulary. They can use the point-and-click UI or the API for automated workflows, so the same product works for a one-off project and for a recurring pipeline. They also keep control over the tradeoff that matters most to them. They pick the model for each job, from fast, economical options for high-volume work to the newest, most capable LLMs for high-stakes analysis, instead of paying top-tier prices for everything. The extraction itself uses techniques from the latest AI research to improve quality. The cost is under 10% of the equivalent staff time, and results come back fast even on huge batches. Finally, Stract API is fully SOC2 compliant, which matters to teams handling case files, sources and survey data. Together, that means a team clears its "Needs Attention" pile and gets to analysis faster, without trading security or depth for speed.
Stract API's answer:
The primary audience for Stract API is small-to-mid-sized teams, along with enterprises, that run recurring, document-heavy workflows and need to pull consistent information out of growing batches of files faster than manual review allows. These teams are typically staff-constrained, facing rising intake volumes of contracts, case files, forms or survey responses, and working from question lists that keep changing over time. Buyers tend to be operations leaders, legal and contract review leads, insurance claims intake leads, research leads, marketing and CRM operations managers, and engineering teams responsible for pipeline automation. Day-to-day users include the document reviewers who need the extracted information and the developers and analysts who feed that structured output into downstream systems. The audience spans insurance and claims, legal (contracts, discovery and case files), journalism (FOIA releases, court records and meeting minutes), marketing (reviews, support tickets and call transcripts), social science (surveys, interviews and field notes) and academic research. Stract API is a weaker fit for organizations that only need occasional one-off extraction from a handful of documents, or teams committed to strictly template- or regex-driven extraction rather than plain-language field specifications.
Stract API's answer:
Stract API grew out of founder Matt Moreno's repeated frustration with the same problem. At a construction tech startup in Google's accelerator, his team built an LLM feature that matched a crew's plain-language daily report to labor and material options. It worked, but it was fragile. Parsing the output was hard, bad output was constant, and any change to the structure broke it. When he asked a Google director whether a product existed to extract arbitrary structured data from unstructured text, the director said no, but that Google probably should build one. Later, on a venture to automate land title research, he again spent tens of hours building flexible document extraction. That work pulled him away from the core mission, and he wished a third-party service would handle it. When he had time this summer (2026), he found few existing solutions. Remembering the director's words, he built Stract API, which took five months to reach MVP. It lets users describe the information they want, from simple facts to judgment-heavy analysis, and returns a spreadsheet, CSV or JSON from their documents.
Share your experience with using Canny.io and Stract API. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


UserVoice is a Canny.io alternative that dives deeper into customer feedback. While Canny offers feedback based on upvoting, UserVoice goes further by collecting feedback from multiple avenues including email,...
Canny stands out as a popular solution for enterprise-level clients seeking robust product roadmap and feature request capabilities. Beyond its core functionalities, Canny (opens in new tab) has an enhanced user...
If you're a founder, product manager, or part of a product team evaluating tools to manage customer feedback and feature requests, you've likely come across Canny. But before settling on Canny, it's worth exploring...
We have no reviews of Stract API yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


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... - Source: dev.to / 3 months 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: almost 3 years ago
Tracking Stract API since Nov 2026.
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