From SaaS Dependence to Speed: How I Built an AI Feedback Agent in a Weekend

I recently built a fully-automated AI feedback agent using n8n, LangChain and Azure OpenAI (GPT-4) — and that experience opened my eyes to a much bigger shift in how enterprises should be thinking about tooling.

You can see the full project details here: How I Built an AI Feedback Agent That Replaces Traditional Surveys — which I’ll refer to throughout this post.

The Project

In that project, I replaced a traditional survey platform with a conversational AI agent:

• Users speak naturally
• The system detects language automatically
• It asks relevant follow-up questions
• It categorizes feedback (bug vs feature vs praise)
• It assigns priority levels
• Everything logs to Google Sheets automatically

The cost difference? The whole setup now runs at ~30-100 SEK/month instead of ~1,500–2,000 SEK/month for a survey SaaS platform.

The real magic? I did it in a weekend (after initial setup) with just a few components:

Related reading: Beyond Dashboards: Conversational Analytics - How modern tools enable custom solutions

n8n
Workflow

Azure OpenAI
Intelligence

Google Sheets
Storage

The Bigger Insight

What struck me while building this is: if this is possible for one small feedback loop, what about dozens of internal processes?

In a typical enterprise you buy SaaS tools for everything:

• Onboarding platforms
• Feedback collection
• Ticketing systems
• Survey tools
• Analytics dashboards

Traditional vs Modern Approach

Traditional SaaS Approach Procurement takes weeks Integration takes months Costs add up continuously Customization is limited or expensive

Modern Build Approach Prototype in hours Deploy in days, not months Customize exactly to your needs Pay only for compute and storage

The project showed me that the technical barrier is now much lower. It requires the right mindset and competencies, but you can build custom solutions that are:

• Faster to deploy
• Cheaper to operate
• More tailored than off-the-shelf SaaS

Are Enterprises Ready?

Here’s where things get interesting — many enterprises are not set up for this shift.

Current Enterprise Blockers

1. Procurement Assumes Buying

• Their procurement process is built around evaluating and buying from SaaS vendors
• Not designed for spinning up lightweight internal tools
• Security reviews are SaaS-centric

2. Competency Gap

• Internal competency often leans toward vendor management
• Not toward code + workflow automation + AI orchestration
• IT departments may lack modern development practices

3. Infrastructure Mindset

• Data and security setups assume third-party SaaS
• Not optimized for building in-house with open components
• Cloud-native thinking may be missing

The Upside When You Bridge the Gap

But if a team does ramp up the competency, the upside is huge:

• More agility in responding to business needs
• Complete ownership of data and processes
• Significantly lower operational costs

My project example: ~90% cost reduction compared with survey SaaS platforms.

What This Means for SaaS Vendors

SaaS companies may start facing a real challenge in the coming years.

If enterprises decide that custom build is:

• Cheaper
• More flexible
• More aligned to their workflows

Then SaaS becomes “nice to have”, not “must have”.

SaaS Companies That Will Survive

The companies that survive this shift will be those that:

1. Offer Highly Differentiated Features

• Capabilities that can’t easily be reproduced with glue tools
• Deep domain expertise embedded in the product
• Network effects that make the platform more valuable

2. Move Fast to Embed AI/Automation

• Integrate AI capabilities faster than enterprises can build them
• Provide pre-trained models and industry-specific solutions
• Offer AI-powered features that justify the premium

3. Position as Platforms, Not Monoliths

• API-first architecture
• Composable features
• Integration-friendly
• Allow customers to use only what they need

The Build-First Mindset

My weekend project with n8n + Azure OpenAI taught me an important lesson:

Building is now not just possible — it’s practical.

When to Build

Consider building when:

• The process is unique to your business
• You need rapid iteration and customization
• SaaS pricing doesn’t scale with your usage
• You have (or can develop) the internal competency
• Data sovereignty is critical

When to Buy

SaaS still makes sense when:

• The problem is commoditized (email, accounting)
• Vendor has deep domain expertise you lack
• Compliance/security requirements are complex
• Scale requires infrastructure you don’t want to manage
• The feature set is highly differentiated

What Enterprises Need to Succeed

To make this shift, you need:

1. The Right People

• Engineers comfortable with low-code platforms
• Understanding of AI/ML capabilities and limitations
• DevOps mindset for deployment and monitoring

2. Mindset Shift

• Default to “can we build?” instead of “which vendor?”
• Embrace experimentation and rapid prototyping
• Accept that not everything needs enterprise-grade from day one

3. Governance Framework

• Security guidelines for self-built tools
• Data handling policies
• Cost monitoring and optimization
• Documentation standards

Real-World Savings

Let me show you the numbers from my project:

Traditional SaaS Survey Platform:

• Monthly cost: 1,500-2,000 SEK
• Annual cost: 18,000-24,000 SEK
• Limited customization
• Vendor lock-in

Custom AI Feedback Agent:

• Monthly cost: 30-100 SEK (Azure OpenAI + n8n hosting)
• Annual cost: 360-1,200 SEK
• Fully customizable
• Complete data ownership

Savings: ~90% cost reduction

And that’s just one tool. Imagine applying this to 10, 20, or 50 internal processes.

The Competitive Advantage

Early adopters of the build-first mindset will gain:

Speed Advantage

• Deploy solutions in days, not months
• Iterate based on user feedback immediately
• No waiting for vendor roadmaps

Cost Advantage

• 80-90% lower operational costs for many use cases
• Pay only for what you use
• No per-seat pricing surprises

Data Advantage

• Complete ownership of your data
• Custom analytics and insights
• No vendor data silos

Flexibility Advantage

• Customize to exact business needs
• Integrate with any system
• Change direction quickly

Getting Started

If you’re in an enterprise and want to explore this approach:

Start Small

1. Pick a non-critical internal process
2. Build a proof of concept in 1-2 weeks
3. Measure costs, speed, and user satisfaction
4. Compare to equivalent SaaS solution

Build Competency

1. Train a small team on modern low-code platforms
2. Experiment with AI APIs (OpenAI, Azure, Anthropic)
3. Learn workflow automation (n8n, Zapier, Make)
4. Document learnings and best practices

Scale Gradually

1. Start with internal tools
2. Move to customer-facing once proven
3. Build governance as you go
4. Share successes across the organization

Final Takeaway

My weekend project with n8n + Azure OpenAI taught me a fundamental truth:

Building is now not just possible — it’s practical, fast, and economical.

If you’re in an enterprise and still defaulting to “let’s buy the SaaS tool”, maybe it’s time to ask:

• Can we build this faster?
• Can we own our data?
• Can we spend far less?

You’ll need the right people, a mindset shift, and some governance. But when you get it right, the savings, the speed, and the control are real.

In short: The future of enterprise tooling isn’t just buy vs build — it’s build first, buy only when it makes sense.

And my little weekend project is proof that the future is already here.

Want to see the full technical details? Check out my complete guide: How I Built an AI Feedback Agent That Replaces Traditional Surveys

Ready to start building? The tools are all available today:

n8n
Workflow automation

Azure OpenAI
AI capabilities

Docker
Your infrastructure

Python
Scripting & automation

The only question is: are you ready to challenge the default?