How We Replaced $180K/Year in SaaS Subscriptions with One Custom AI App

The $180K Problem

When Marcus, the operations director at a mid-size Melbourne logistics company, first called us, he wasn’t looking for a custom AI app. He was looking for a cheaper CRM.

“We’re spending $15,000 a month on software,” he told us. “And I’m pretty sure half of it does the same thing.”

He was right. But the problem was worse than he thought.

After a two-hour discovery session, we mapped out their entire software stack. Twelve tools. Twelve monthly invoices. Twelve vendors, each with their own pricing model, their own login, their own support team that takes 48 hours to respond.

“I knew we were overspending. I didn’t realise we were paying three different companies to do basically the same thing.”

— Marcus, Operations Director

The total annual cost? $183,600. For a company with 40 employees, that’s $4,590 per person, per year, just on software subscriptions. And the kicker? Their team was using maybe 30% of the features across all those tools.

Auditing the Stack

The first thing we did was run our SaaS Savings Audit — a structured analysis of every tool, its actual usage, overlap with other tools, and the cost per active feature.

Here’s what we found across their twelve subscriptions:

• HubSpot CRM — $1,800/mo (Enterprise tier, 40 seats)
• Salesforce Essentials — $1,000/mo (legacy contract, barely used)
• Zendesk — $1,200/mo (customer support ticketing)
• Intercom — $800/mo (live chat, overlaps with Zendesk)
• Monday.com — $600/mo (project management)
• Asana — $400/mo (some teams preferred this over Monday)
• Notion — $320/mo (internal wiki, barely maintained)
• Zapier — $500/mo (glue holding everything together)
• Typeform — $300/mo (lead capture forms)
• Calendly — $480/mo (booking for sales team)
• Mailchimp — $350/mo (email marketing)
• Custom reporting tool — $7,250/mo (built by a previous agency)

The pattern was clear. This wasn’t a technology problem — it was an accumulation problem. Every new hire, every new initiative, every new pain point had been solved by adding another subscription. Nobody had stepped back to ask: do we actually need all of this?

The Technical Approach

We proposed building a single, unified system powered by Claude’s API. Not a generic chatbot. Not a wrapper around ChatGPT. A purpose-built AI application designed around their specific workflows. You can see the full range of custom solutions we build for businesses facing exactly this kind of tool sprawl.

The decision to use claude-sonnet-4-6 as the primary model came down to three factors:

1. Structured output reliability. Claude consistently generates valid JSON for our internal data pipelines, which means fewer parsing errors and more predictable automation.
2. Context window size. With 200K tokens of context, we could feed entire customer histories into a single prompt without chunking or retrieval hacks.
3. Cost-performance ratio. At the volume we were projecting, Sonnet delivered enterprise-grade output at a fraction of GPT-4 pricing.

Architecture Overview

The system was built as a Next.js application with a PostgreSQL database, deployed on a single $48/month DigitalOcean droplet. The simplicity of the infrastructure was deliberate — we wanted Marcus’s team to be able to understand and maintain what they were running.

Building the Replacement

We broke the build into four two-week sprints:

1. Sprint 1: Core CRM + Contact Management. Migrated 23,000 contacts from HubSpot and Salesforce into a unified database. Built AI-powered lead scoring that analysed inbound enquiries and assigned priority levels automatically.
2. Sprint 2: Customer Support + Communication. Replaced Zendesk and Intercom with a single inbox. Claude handled first-response drafting, ticket categorisation, and escalation routing.
3. Sprint 3: Project Management + Reporting. Consolidated Monday, Asana, and the legacy reporting tool into a purpose-built dashboard. Automated weekly reports that previously took a team member 4 hours every Friday.
4. Sprint 4: Integration + Automation. Eliminated Zapier entirely by building direct integrations. Connected email (replacing Mailchimp), scheduling (replacing Calendly), and forms (replacing Typeform) into the core platform.

The test results after the final sprint spoke for themselves. Contact import accuracy hit 99.7%, AI lead scoring correlation reached 94.2%, and support ticket auto-categorisation landed at 97.1%. Report generation dropped from 4 hours of manual work to 12 seconds of automated output.

Results & ROI

Here’s the bottom line after 12 months of operation:

The custom system replaced all twelve SaaS subscriptions. Total build cost was $12,500 — less than one month of their previous software spend. Ongoing costs dropped to roughly $97/month: $48 for hosting and $49 average for Claude API usage. For a detailed breakdown of what projects like this typically cost, see our 2026 custom AI app pricing guide.

“It’s not just the money. It’s that everything works together now. One login, one system, one place to look. My team actually enjoys using it — which was never true of the old stack.”

— Marcus, Operations Director

The numbers tell the story:

• Year 1 savings: $170,000+ (after accounting for build cost and operational expenses)
• Ongoing annual savings: $182,400+ per year
• Payback period: 6 weeks from deployment
• Team productivity increase: 23% (measured by tasks completed per person per week)
• Support response time: Reduced from 4.2 hours average to 18 minutes
• Weekly reporting time: From 4 hours manual work to 12-second automated generation

Five-year projected savings: $899,600. That’s not a rounding error. That’s the cost of adding ten new team members — freed up by simply not renting software anymore.

Lessons Learned

After delivering this project and several like it, we’ve distilled the key takeaways for any business considering a SaaS-to-custom transition:

• Audit first, build second. You can’t optimise what you haven’t measured. Our SaaS Savings Audit consistently reveals 30–60% waste in most software stacks.
• Don’t replicate features — replicate outcomes. Nobody needs a “Zendesk replacement.” They need customer issues resolved quickly. Build for the outcome, not the feature list.
• AI makes custom affordable. Two years ago, this build would have cost $150K+ and taken 6 months. Claude’s API lets us deliver enterprise-quality AI features at SMB prices.
• Ownership matters. When you own the code, you control the roadmap. No more begging a vendor’s product team to add the feature you need.
• Start with the biggest pain. Don’t try to replace everything at once. Start with the tool that costs the most, gets used the least, or causes the most friction — and expand from there.

If this sounds like your business — drowning in subscriptions, frustrated by tools that don’t talk to each other, and spending more each year for diminishing returns — we should talk. Not sure if you’ve hit the tipping point? Check the five signs your business is ready for a custom AI tool to find out.

Our free SaaS Savings Audit takes 30 minutes and gives you an exact picture of what you could save. No commitment, no pitch deck, just numbers.