When a client’s CFO noticed a recurring charge of $1,200 for a contract tool nobody had touched in months, it set off alarms-and led to reclaiming over $30,000 in wasted SaaS spend. If your cloud bill hides similar surprises, follow this three-step process to uncover hidden data, organize it efficiently, and move it to a secure, lower-cost home without risking compliance.

Discover Hidden Data

Why this matters

  • You can’t pause or cancel a subscription until you know what’s in it
  • Manual clicks across multiple screens are slow and error-prone

How we do it
Most SaaS platforms provide a REST API (Representational State Transfer application programming interface) – a set of HTTP endpoints for creating, reading, updating, and deleting data. We run lightweight scripts to:

  • Pull complete lists of records, attachments, and metadata
  • Scan tens of thousands of entries in minutes
  • Tag items as “must-keep,” “archive,” or “delete” based on your policies

With full visibility into your data footprint, you’ll know exactly what to tackle next.

Next up: turning raw exports into clear categories.

Organize with a Large Language Model (LLM)

Why this matters

  • Raw JSON or XML exports are hard to review manually
  • Accurate classification helps you meet retention policies and cut storage costs

How we do it
We feed API dumps into a large language model (LLM) – an AI trained to read, cluster, and summarize text at scale. For example, processing thousands of customer notes might yield categories like support requests, billing inquiries, and feedback – each with concise summaries.

Sample record:

{
  "id": 345,
  "type": "customer_note",
  "content": "Discussed renewal options; follow up in Q3."
}

LLM output:

  • Category: Customer interactions
  • Action required: Follow up
  • Recommended retention: 2 years

By assigning each record to a must-keep, archive, or delete bucket, you avoid over-retaining data and reduce ongoing fees.

With your data organized, you’re ready to extract and secure it seamlessly.

Extract, Transform, Store

Why this matters

  • Keeps critical data accessible and secure in a lower-cost environment
  • Ensures compliance through encryption and strict access controls

How we do it

  1. Extraction
    • Automate API calls while respecting rate limits
    • Log requests and handle errors gracefully
  2. Transformation
    • Validate, normalize, and dedupe fields
    • Scrub or encrypt sensitive information
  3. Storage
    • Load into a data warehouse (Snowflake, BigQuery)
    • Archive in object storage (Amazon S3, Google Cloud Storage)
    • Or move to an on-premise archive for full control

For one client, archiving five years of support tickets in object storage cut storage costs by more than 60% – all while keeping records accessible.

Bottom Line

In under a month, we had unlocked over $30,000 in savings. Ready to expose your own hidden budget?