How Were My Users Feeling?
You're collecting feedback. Imagine asking: How were my users feeling last week? What should I prioritize? Assign priority, move it to Linear — I have a meeting in 30 minutes.
A one-shot prompt can't do that.
And Encatch isn't trying to. We could have built a full in-product AI tooling experience like everyone else — complete with its own workflows, limits, and learning curve. We thought there was a better option: meet users in the tooling they're already most comfortable with. Users keep the prompts, memory, and workflows they've invested in. Encatch stays focused on collecting and organizing feedback. Win-win.
Because the AI inside most products is restricted by design: predefined prompts, fixed workflows, limited outputs, and models that know nothing about how you work. It may sit inside the product, but it isn't really your AI.
Bring Your Own AI Tooling, Not Just AI
Imagine going to a party where the food is already laid out — and still bringing your own personal chef.
It may sound extreme. But your chef already knows what you like, how you like it made, and the little adjustments that only come from cooking for you over time. You're not rejecting the party. You're just not starting from a kitchen that doesn't know you.
That's closer to what Bring Your Own AI tooling really means. You're not just bringing a model. You're bringing the prompts you've refined, the workflows you've built, and the memory that tool has of how you think. That setup doesn't stay still. It gets sharper the longer you use it.
Many professionals already have this in place. Some use ChatGPT. Others use Claude, Gemini, Perplexity, Cursor, Copilot, or internal enterprise AI systems. They don't just prefer a model — they depend on a working system they've invested months into.
So why force them to abandon that tooling and start from scratch inside another platform?
Instead of asking users to adapt to a platform's AI implementation, we asked a different question:
What if Encatch simply helped users take their data into the AI tooling they already rely on?
That question led to the creation of Analyse with AI.
What is Analyse with AI?
Analyse with AI is a feature within Encatch that helps you export your feedback and analytics data in a format that is immediately usable by AI tools.
Rather than providing another limited in-platform chatbot, Encatch prepares your data and generates a contextual prompt that gives your preferred AI assistant the information it needs to start working.
Think of it as a bridge between Encatch and the AI ecosystem you already use.
Whether you want to:
- Identify emerging customer issues
- Detect sentiment trends
- Discover feature requests
- Generate executive summaries
- Create presentations for stakeholders
- Build action plans from feedback
You can do so using the AI platform you already trust.
Why Use It?
1. Freedom of Choice
You decide which AI model to use. Want GPT-5? Use GPT-5. Prefer Claude for long-form analysis? Use Claude. Have an enterprise AI deployment with strict data governance requirements? Use that instead. The choice remains yours.
2. Better Results Through Familiarity
The best AI outputs rarely come from a single prompt. Most experienced users have developed their own prompting techniques, templates, and workflows over time — and those investments shouldn't be lost simply because they're working inside a feedback platform. Analyse with AI lets you continue using the methods that already work for you.
3. No Vendor Lock-In
AI capabilities evolve rapidly, and today's best model may not be tomorrow's. By separating feedback collection from AI analysis, users are free to adopt new models and technologies without waiting for platform updates.
4. Cost Efficiency
AI processing isn't free. Running large-scale analysis inside a platform means someone has to bear the cost — and eventually, that cost reaches the customer. Many professionals and organizations already subscribe to AI services, and a premium AI subscription often provides significantly more value than a platform-specific AI add-on. If you're already paying for advanced AI capabilities, why pay again for a limited version embedded inside every product you use?
How Does It Work?
A click of a button. Really.
Head over to your dashboard and click Analyse with AI. Encatch will gather the relevant data and even put together a prompt to give you a head start.
From there, you're free to take it wherever you want. Paste it into ChatGPT, Claude, Gemini, or whichever AI tool you prefer and continue the analysis your way.
Why Doesn't Encatch Provide AI Analysis Directly?
It's a fair question. The answer is that meaningful data analysis is more complex than asking a single question to a language model.
Real Analysis Requires Iteration
Experienced AI users know that one-shot prompts rarely produce the best results. Analysis is usually an iterative process: ask a question, review findings, refine assumptions, request deeper investigation, validate conclusions, and generate reports. The best outcomes come from multiple cycles of exploration, not a single prompt-and-response interaction.
Large Datasets Have Practical Limits
Even the largest context windows available today have limits. As datasets grow, models become more expensive to run and more prone to overlooking details or making incorrect assumptions. Meaningful analysis often requires breaking data apart, running multiple analytical passes, validating results, and combining findings.
Agentic Workflows Are Complex
Advanced AI analysis increasingly relies on agentic workflows — systems that repeatedly analyze, validate, calculate, and cross-check information before presenting conclusions. Building and maintaining those capabilities inside a feedback platform is a significant undertaking and would inevitably introduce constraints around model selection, usage limits, and pricing.
Users Already Have AI Tools
Perhaps the most important reason is the simplest one: many users already have access to excellent AI tools. Rather than asking them to switch, Encatch helps them leverage the tools they already know and trust.
The Philosophy Behind Analyse with AI
Most software companies are racing to add AI features. We took a different approach. Instead of building another AI assistant, we focused on helping users get more value from the AI assistants they already use. Analyse with AI isn't about replacing ChatGPT, Claude, Gemini, or whatever comes next — it's about making Encatch data instantly accessible to those tools. Because sometimes the best AI strategy isn't building another AI product. It's giving users the freedom to use their own.
Conclusion
Feedback data is only valuable when it leads to action. The challenge isn't collecting feedback anymore — it's understanding it quickly enough to make informed decisions. Analyse with AI helps bridge that gap by allowing teams to take their Encatch data directly into the AI workflows they already rely on. No restrictions. No lock-in. No predefined way of thinking. Just your feedback, your insights, and your AI of choice.