If you’ve got a mountain of old contracts and need to get them into Agiloft, you’re not alone. Migrating legacy data sounds simple until you’re knee-deep in inconsistent formats, missing fields, and surprise duplicates. This guide is for anyone who needs to import old contracts into Agiloft with minimal pain—admins, project leads, or just the unlucky soul who drew the short straw. I’ll walk you through the process, flag what actually matters, and call out what you can skip.
Step 1: Audit Your Legacy Contracts First
Don’t rush to import everything. Start by figuring out what you’ve actually got. Most companies have contract folders that are a mess—expired deals, duplicates, scanned PDFs, maybe even faxes. The more you clean up now, the less you’ll regret later.
What’s worth importing? - Active contracts, amendments, and renewals - Recently expired contracts you might reference or report on - Key historical contracts (high-value, high-risk, or required by law)
Skip or archive: - Superseded drafts - Obsolete or irrelevant contracts - Anything missing critical information (unless you want to chase details later)
Pro tip: Don’t aim for “perfect.” If in doubt, archive instead of importing. You can always add more later.
Step 2: Standardize Your Data—Or Pay for It Later
Legacy contracts come in every flavor: Word docs, PDFs, scanned images, emails. Agiloft isn’t magic—you need structured data for a clean import.
What you need: - Key contract metadata: Title, parties, start/end dates, renewal terms, contract value, status, etc. - Contract files: Attachments in a consistent format (PDF preferred). - Contract text (optional): If you want full-text search or clause extraction.
How to get there: - Use OCR for scanned contracts. It’s not perfect, but it’s better than nothing. - Build a spreadsheet template. At minimum, each row = one contract, each column = a field in Agiloft. - Assign someone to spot-check the data. Garbage in, garbage out.
Don’t: Try to extract every possible field. Start with the essentials. You can always add more fields down the line.
Step 3: Map Your Data to Agiloft Fields
Agiloft has its own fields and structure. Don’t assume your spreadsheet columns match up. Spend some time mapping your data to Agiloft’s field names and types.
How to do it: - Get a list of required and optional fields from your Agiloft admin or system documentation. - Make a mapping sheet: “Spreadsheet Column” → “Agiloft Field” - Check for required fields—Agiloft will reject rows missing these. - Normalize data types. Dates should be in a consistent format (YYYY-MM-DD is safest), dropdowns should use the expected values, and so on.
Watch out for: - Mismatched picklist/dropdown values (e.g., “Active” vs “In Progress”) - Blank values in required fields - Duplicates and weird characters from old exports
Pro tip: Run a few sample records through Agiloft’s import tool to see what breaks—fix those issues before importing everything.
Step 4: Use the Import Tool—But Test on a Sandbox First
Agiloft has a built-in import wizard. It’s not flashy, but it does the job. Don’t make your first attempt on your live system.
Steps: 1. Get access to a sandbox environment. If you don’t have one, ask your admin or Agiloft support. 2. Run a small test import. 10–20 contracts is enough to shake out mapping errors. 3. Check for errors or weirdness. Are files attached correctly? Are dates and parties showing up as expected? Any duplicates? 4. Review imported records with the business team. Do they make sense? Is anything missing or misfiled?
Don’t: Import your entire legacy set at once. No system is immune from bad data.
Pro tip: Keep a log of what you import and when. If you need to roll back, you’ll be glad you did.
Step 5: Fix Import Errors and Clean Up
You will hit snags. Common issues: - Required fields missing (import fails) - File attachments not linked (wrong file path or format) - Date or currency formatting errors - Duplicate contracts
How to fix: - Use Agiloft’s error logs—they’re not pretty, but they tell you what broke. - Update your spreadsheet or source data, not just the import file. Otherwise, you’ll keep repeating mistakes. - Re-import only the failed records, not the whole batch.
Don’t: Ignore small errors. They add up and are harder to fix later.
Step 6: Validate and Get Sign-Off
Once your test batch looks solid, import the rest in chunks (100–500 contracts at a time, depending on your system and comfort level).
Checklist: - Spot-check a sample of each import batch - Make sure attachments are present and readable - Check reporting fields (contract value, date, parties) for accuracy - Get business owners or legal to sign off—nobody likes surprises months later
If something’s off: Stop and fix before going further. Partial, clean data is better than a giant mess.
Step 7: Train Your Users and Set Expectations
Don’t assume everyone will magically find contracts in Agiloft. Show users how to search, filter, and report on the new data.
Tips: - Short, live demos work better than long documentation. - Set up saved searches or dashboards for common needs (expiring contracts, contracts by vendor, etc.) - Make it clear where to find attachments and how to request corrections if anything’s missing or wrong.
Don’t: Overpromise on what’s there. Legacy imports are rarely perfect, and that’s fine.
Honest Takes: What Works, What Doesn’t
What actually helps: - Cleaning and standardizing your data before import. The time you spend here saves you triple later. - Testing imports on a sandbox. This catches 95% of problems before they hit production. - Small, incremental imports. Large batches hide errors and make troubleshooting miserable.
What you can skip: - Importing every single field or clause. Focus on what’s actionable and required. - Fancy OCR or AI extraction for every contract. For most legacy sets, a manual review of key fields is faster and more accurate.
What doesn’t work: - Assuming “import” means “done.” You’ll need to review, fix, and support users after the fact. - Trusting old spreadsheets or file names. Double-check the source data.
Keep It Simple—And Iterate
Legacy contract imports are rarely fun, but they don’t have to be a disaster. Do the basics well: clean your data, map your fields, test in small batches, and get real users to check the results. Skip the bells and whistles until you have a working baseline. You can always improve later. The goal isn’t perfection—it’s making things findable, usable, and a lot less messy than before.
Good luck, and remember: done is better than perfect.