The "Contact Sales" button is a technical debt indicator. Every time a vendor hides their pricing behind a form, they are adding friction to your stack's scalability.

We spent months building a pipeline that tracks hundreds of SaaS pricing pages daily. But raw data is just noise. To make it actionable, we built a dashboard that treats software procurement like engineering: with logic, formulas, and daily data pipelines.

Here is the technical breakdown of the three core engines we’ve just deployed at comparedge.com.

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1. The Vendor Lock-In Score: Quantifying the "Exit Cost"

Most teams choose software based on features. Smart teams choose based on how hard it is to leave.

We developed the Vendor Lock-In Score to measure this. It’s not a gut feeling. It’s a weight-based matrix looking at:

• Data Portability: Does the API allow full bulk exports?
• Integration Depth: How many proprietary hooks are you forced to use?
• Contractual Friction: Auto-renewal clauses and seat minimums.

The Logic: If a tool scores an 8/10 on Lock-In, your "cheap" $50/mo starter plan is actually a high-risk liability. We’ve mapped this for hundreds of tools (on our roadmap to cross the 1,000+ mark), so you can see the trap before you step in it.

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2. Stack Builder: Moving Beyond the Spreadsheet

Procurement usually happens in a messy Excel sheet. It breaks. It’s never updated.

The Stack Builder is our solution for "Infrastructure as a Budget."

• You select tools across 28+ growing categories (CRMs, Hosting, Security).
• The engine pulls daily-synced prices (no more stale data).
• It calculates the total monthly and annual burn, accounting for per-seat vs. flat-rate scaling.

It’s essentially a sandbox for your CFO. You can swap a $200/mo CRM for a $50/mo alternative and instantly see the ripple effect on your total stack cost.

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3. LLM Price Calculator: The 2026 Margin Saver

LLM pricing is a moving target. With 6 providers and 25+ models (from GPT-4o to Llama 3 on Groq), calculating token costs for a production app is a nightmare.

Our LLM Calculator normalizes this. Input your expected monthly tokens (Input/Output), and it spits out a side-by-side comparison.

• Why it matters: We found that switching providers for the same model can save up to 40% in margins.
• Data Freshness: Since we sync daily, we catch those "stealth" price drops the moment they hit the docs.

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The Infrastructure of Transparency

Everything we do is Open Data.

• GitHub: Fork the logic.
• Kaggle: Use the raw SQLite/CSV dumps for your own models.
• Railway API: Hit our public end-points (no auth required) to pipe these prices directly into your internal tools.

We are building a public utility. Software is the biggest line item for modern companies after payroll. It shouldn't be a black box.

Try the dashboard: comparedge.com/dashboard
Code & Data: comparedge.com/open-data

No "Contact Sales" buttons were harmed in the making of this project.