In enterprise environments, data migrations often look simple on paper until you’re deep in terabytes of business-critical documents that power everyday operations.
At Aavenir, where Enterprise Contract Management is the backbone of our solutions, we recently took on a massive internal challenge: migrating more than 33,000 contract documents from our Sandbox to Production ServiceNow instance without losing a single byte or breaking any relational link.
Each file represented years of contract history, ranging from 1 MB to 200 MB, linked to detailed metadata and parent records within Contract Automation workflows. The mission? Achieve complete data fidelity while accelerating migration time, and we did it, taking the process from two full days to just four hours.
Here’s how our engineering team engineered a scalable, repeatable, and fully automated migration and what it teaches about automation in enterprise contract management.
The Challenge: Moving More Than Just Files
In an enterprise contract ecosystem, every document is connected, not just stored. Contract attachments in ServiceNow are kept in the sys_attachment table and linked to parent records, such as dms_document_revision.
That meant we weren’t simply transferring files; we were moving relationships, dependencies, and business continuity.
The challenge came down to three non-negotiables:
- Maintain accurate parent-child record links for every document.
- Handle large file sizes without bottlenecks.
- Ensure a repeatable, error-proof process fit for enterprise scale.
Traditional tools could move data, but not with the precision and reliability enterprise-grade contract workflows demand.
Approach 1: XML Export/Import – A Familiar but Manual Route
We started with ServiceNow’s native XML export/import method. It’s simple and effective for small datasets, but it quickly became unmanageable for the scale of our migration.
Batching data into smaller groups of 500–1000 records slowed down execution and increased manual oversight.
- Pros: Simple to configure
- Cons: Manual effort, no scalability, limited automation
This method reinforced an important truth: manual processes don’t scale in modern contract automation environments.
Approach 2: API-Based Migration – Smarter, But Still Sequential
The next step was automation through ServiceNow REST APIs, which provided more control and eliminated manual exports.
However, APIs in ServiceNow execute sequentially — one attachment at a time — creating a new bottleneck.
- Pros: Automated, consistent, reliable
- Cons: Sequential transfer, not suited for large-scale migrations
This was faster than XML imports but still too slow for 33,000+ documents.
Approach 3: Python-Powered Multi-Threaded Migration – The Breakthrough
To truly scale, our engineers designed a custom Python-powered multi-threaded migration that combined ServiceNow’s robustness with Python’s parallel processing power.
Here’s how the process worked:
- Temporarily detach attachments from parent records by clearing the sys_id linkage.
- Stored mapping data in a temporary field for re-linking post-migration.
- Migrated parent records (dms_document_revision) into the Production instance.
- Re-associated attachments using saved mapping references.
- Executed a custom Python script to migrate attachments using six parallel threads via REST APIs.
This innovation created a high-performance, automated migration pipeline that preserved all relationships, ensured zero data loss, and scaled effortlessly.
- Pros: Fully automated, parallel processing, enterprise scalability
- Cons: Required scripting and live monitoring
The Results: 33,000+ Contracts, Zero Data Loss
After validation and testing, the results spoke for themselves:
✅ 33,000+ contract documents successfully migrated
⚡ Migration time reduced from 2 days to 4.5 hours
🔒 Zero data loss or corruption
🔁 Fully automated and repeatable process
This wasn’t just a technical success; it was a proof point for automation in enterprise contract management.
Why It Matters for Enterprise Contract Management
Contract data is the lifeblood of any enterprise. Yet, manual or fragmented systems often create operational blind spots, especially during transitions, mergers, or platform upgrades.
By combining automation, scalability, and intelligent design, Aavenir’s engineering team demonstrated how contract automation can deliver reliability and precision across massive datasets, something many global enterprises struggle with.
The lesson: Whether you’re migrating thousands of legacy agreements or implementing a new Contract Lifecycle Management (CLM) platform, automation is no longer optional; it’s foundational to maintaining data integrity and business continuity.
Key Takeaways
- Manual doesn’t scale: Traditional methods like XML imports can’t keep up with enterprise volume.
- Automation accelerates accuracy: APIs and scripting ensure consistency and traceability.
- Custom innovation drives value: Combining ServiceNow’s structure with Python’s power created an efficient, repeatable model.
- Contract data deserves intelligence: In modern enterprises, contracts aren’t documents; they’re data assets.
Closing Thoughts
Every enterprise transformation begins with trust in your data. For Aavenir, this migration project reinforced our belief that Contract Automation isn’t just about speed; it’s about accuracy, governance, and scalability.
Whether migrating contracts or managing them daily, Aavenir continues to deliver AI-powered, automation-first solutions that keep enterprise contract management systems resilient, efficient, and ready for what’s next.
If this migration story resonated with your team’s challenges, let’s talk!
Schedule a personalized demo of Aavenir Contract Management and explore how Aavenir can streamline your contract workflows from creation to compliance.
