Canny vs. building in-house
You could build a version of Canny. That's not the hard part.
Building one feature is easy. Running the whole system means managing a second product.
AI made software cheap to build, not cheap to own
Building parts of Canny is doable now, whether that is a feedback board or automated feedback capture. But there are a lot of supporting features that teams often do not consider. Deduplicating feedback, organizing it by product area, adding revenue context, and closing the loop with customers are each projects of their own. If you build your own feedback tools, you own adding functionality and fixing things when they break.
That is the second product problem. You set out to solve a problem, and end up owning a product nobody planned to run. It has users, a backlog, and a support burden, and every improvement competes with your roadmap for engineering time.
Canny does all of it starting at $79 a month.
What you'd actually be replacing
Most teams look to build at least one of three main parts of Canny. You can build a convincing v1, but getting each right is harder than it looks.
A customer-facing feedback portal
The v1: your customers submit requests and vote on them. You can see what is popular.
- Deduplication
Duplicates split the count across four versions of the same request
- Account matching
Who is asking, letting them log in with existing accounts, and account details on feedback
- Moderation
A public portal is an open door vulnerable to spam and abuse
Organizing and prioritizing feedback
The v1: a filterable list of feedback with statuses on it.
- Revenue context
Every request connected to accounts, ARR, and open opportunities. This makes prioritization defensible
- Merging and triaging
Hundreds of requests into a prioritized view sorted by product area
- Views per stakeholder
Sales, CS, and execs each need a different cut of the same data
Automated feedback capture
The v1: feature requests pulled from your support queue. Convincing, at first.
- Accuracy
Typeform audited 1,725 tickets and found Autopilot 93% accurate, and 30% better than their live team
- Sources
Every tool you capture from (Gong, Intercom, Zendesk) is an integration you maintain
- Model changes
Every model update shifts extraction behavior, so prompts and benchmarks need upkeep
Don’t forget about closing the loop
Most customer intelligence tools stop at capturing insights. Nothing goes back to the customer who shared their feedback, and in-house builds often skip this too. Keeping customers updated reduces churn, grows accounts, and keeps the feedback coming.
Other things you might want to build
Illustrative, not exhaustive.
You’ll need to secure your customers’ data
A public feedback portal with anonymous requests poses few security risks, but it also does not have much value. The version worth having holds account identity, revenue figures, and CRM data. That is a system of record for sensitive customer data, and it needs real authentication, permissions, audit trails, and someone responsible for keeping it secure and up to date.
One recent analysis found 434 exploitable flaws across a set of vibe-coded apps. The most common were missing rate limiting and broken authorization. Read the analysis.
The data is not only yours, since support tickets and call transcripts contain your customers’ information, and that surfaces in your next enterprise vendor questionnaire. Automated feedback capture also sends conversations to LLM APIs, which raises questions about data-processing terms, retention, and training. A vendor answers those contractually. A homegrown build usually does not consider them.
Canny is SOC 2 Type 2 certified, with SSO, encryption, and GDPR compliance already in place, and our agreements ensure customer data is never used to train models.
Three hidden costs
It's easy to underestimate the cost of building in-house
Engineer hours (an opportunity cost) plus AI usage. The part that got easier, and usually the only part teams factor in.
Roughly 15 to 20% of build cost, every year the tool exists. Broken integrations, model migrations, accuracy drift, security fixes.
Every ticket, call, and review runs through an LLM, and that cost scales with your feedback volume.
Canny’s plans start at $79/mo and cover all three.
Calculating your actual cost to build in-house
| Step | How | Note |
|---|---|---|
| 1 · Spec your features | Check every feature you would want | Most teams underestimate this and end up having to build more later |
| 2 · Build cost | Engineer hours × their hourly cost, plus AI usage | Token usage and cost is easy to overlook but it adds up |
| 3 · Maintenance cost | 15 to 20% of build cost | Recurs annually |
| 4 · Operating cost | Monthly feedback volume × per-item cost | If you specced automated feedback capture. Recurs and scales. |
| 5 · Compare | Total vs. Canny's price for the same features | Book a call with our team to discuss Canny’s full offering |
When building is genuinely right
If you are bootstrapping and all you want is a basic feedback board, building it can make sense.
Some compliance environments rule out vendors entirely. Then the build cost is the cost of doing business.
Enterprise customer intelligence platforms can run north of $50K a year, and building can beat that. The build that beats a $50K contract rarely beats Canny at $79 a month.
“But building means we get exactly what we want”
True on day one. Then your needs change, and every change is a ticket your team has to handle. Feedback capture, deduplication, organization, and closing the loop work the same way at almost every company. The part that is genuinely specific to you is your views, your workflows, and your internal dashboards. That part is small.
Build that part using Canny’s API and MCP server. It lets you use organized and enriched Canny data in ChatGPT or Claude. You can also make updates in Canny from these LLMs so you can actively manage your feedback. Keep the system, own the custom layer.
If Canny doesn’t do something you need, request it on our Portal and watch it ship
Reserve your roadmap for your own product
Canny captures your feedback, deduplicates it, and shows you the ARR behind every request.
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Frequently asked questions
Can I build my own feedback tool with Claude or Cursor?
You can build something usable quickly. Depth is where the effort lives: deduplication at scale, CRM enrichment, source integrations, and accuracy that holds as models change. Many teams find the ongoing cost outweighs the subscription they were avoiding.
How much does it cost to build a feedback tool in-house?
Three costs. Building is engineer hours times your rate. Maintenance typically runs 15 to 20% of build cost annually. Operations is mostly usage costs, metered per item, and is more expensive if you build automated feedback capture. Price all three for every feature you want before you decide.
Should we build or buy?
Run the math honestly. Price the full spec, not the v1. Add 15 to 20% a year for maintenance, and inference costs if you are capturing automatically. Then ask one non-financial question: who owns this in year two?
What are the parts of a customer intelligence system?
Capture, organization, analysis, and closing the loop. Capture pulls feedback from tickets, calls, reviews, and a customer-facing portal. Organization deduplicates it, groups it, and ties each idea to accounts and ARR. Analysis shows which themes are growing, what is blocking renewals, and how much revenue sits behind a request. Closing the loop tells customers what happened. Most builds cover one.
Is AI-generated code safe enough for customer data?
Treat it as unreviewed code. If your build touches revenue figures or support conversations, it needs the same security review any production system gets.