European CLM platforms for migrating existing contracts into structured data

When a company moves hundreds or thousands of existing agreements into a new contract management system, the migration needs to bring together documents, existing data, and the relationships between them. Legal also needs to decide which information to preserve, which gaps to fill, and how the resulting contract records will be maintained.

AI can help identify dates, parties, renewal terms, obligations, and other contract data. But an extracted value is still a proposed answer. A reviewer may need to check where it came from, whether an amendment changed it, and how it relates to information already held in the previous system.

In this article, we compare how Zefort, ContractHero, Contractify, and Fabasoft Contracts support the migration of an existing contract portfolio. We look at metadata extraction, custom data requirements, review workflows, and the transition to ongoing contract management. We also explain what to test in a migration pilot.

What metadata extraction brings to contract migration

Let’s start with one of the core capabilities of post-signature contract management: metadata extraction. It turns information inside contract documents into structured data that teams can search, filter, and use in their daily work. During a migration, AI can identify details such as contracting parties, effective dates, notice periods, and renewal terms, then populate corresponding fields in the new system.

Standard contract fields cover many common needs, but each organization also has information it wants to track for its own purposes. Custom metadata allows teams to define additional fields, such as supplier category, internal contract owner, or a particular contractual requirement. Some of these values come from the agreement; others reflect how the organization manages its contracts.

AI custom metadata extraction extends extraction to organization-defined fields. For example, a legal team might want to identify the liability cap or a specific reporting obligation across its supplier agreements. Configuring AI to extract that information can reduce the manual work involved in building a contract record that reflects the team’s needs.

Existing metadata needs separate attention. If the previous system already holds checked dates, assigned owners, or internal classifications, the migration plan should establish how those values will be mapped into the new system. AI extraction can help fill gaps, but it should not silently replace information the organization has already validated.

European CLM platforms compared for existing contract migration

Based on publicly available product information, we compare Zefort, ContractHero, Contractify, and Fabasoft Contracts for organizations migrating an existing contract portfolio into a new CLM system. The table uses the same criteria for each platform: extraction and custom data, review and correction, and migration and ongoing management.

These capabilities overlap substantially. Customizable contract data and continued maintenance are relevant across the products, so their presence alone does not establish a meaningful difference. The buying decision depends on how the workflows operate, what configuration they require, and which features and services are included in the proposed package.

The entries summarize documented capabilities, not exclusive advantages. A custom field does not by itself establish that AI can populate it automatically, and a bulk status change does not establish that every underlying value has been checked. Those details should be demonstrated using the same requirements and contract sample for every vendor.

What to examine in each platform’s migration workflow

Zefort: custom extraction, review, and migration projects

Zefort’s AI custom metadata tools allow administrators to define prompts for supported metadata fields. A saved prompt can run automatically when a contract is uploaded, and AI Chat can also populate fields across selected contracts through bulk operations.

During contract review, users can inspect suggested information against the document preview, correct values, and mark the contract as reviewed. Zefort also provides a contract audit log and tools for maintaining contract details.

For a migration pilot, follow the complete sequence: import existing data, extract an additional custom field, review the result, and update it later. Establish how imported values and manual corrections interact with any subsequent AI operation. The agreed migration scope should also identify which documents, relationships, and historical information will be carried over.

ContractHero: configurable fields and verification controls

ContractHero also supports AI prompts for custom fields. Its documentation describes configuring extraction instructions at field level, so the analysis can reflect the organization’s data requirements.

Its contract-analysis workflow includes verification of individual fields, whole contracts, or multiple contracts. The guidance states that manual corrections are kept when analysis runs again. Jump to Source provides links to supporting passages; the documentation describes a rollout, so confirm availability in the proposed environment.

ContractHero’s onboarding guidance covers fields, responsibilities, permissions, and import options. In the pilot, test those controls with an imported value, a manual correction, and a newly added field to establish how each is handled.

Contractify: custom fields, source review, and bulk status updates

Contractify’s Ada suggests contract data, shows where it was found, and lets a person verify and save it. Users can also ask for specific information through chat. Contractify supports custom fields with types including text, number, date, and lists.

Its bulk-editing documentation explicitly includes the Verified field. This allows teams to update verification status across selected contracts. In a pilot, establish what that status represents in your review process and how users distinguish checked information from unresolved questions.

Contractify also provides reporting and dashboards and advertises migration and onboarding support. Ask the vendor to demonstrate the path from a requested custom value to a maintained field, including any manual steps, and show what happens to that value when the documents are analyzed again.

Fabasoft Contracts: structured imports and configurable contract records

Fabasoft Contracts documents import workflows for existing contracts, metadata, and associated documents. These include Excel or CSV metadata imports and worksheets that associate documents with contract records.

Its contract-management guidance describes AI-assisted metadata population during upload, split-view review, and a History area for metadata changes. Custom forms and user-defined fields extend the data model, while reports and reminders support continued use.

In a pilot, test the mapping from your existing export to the target records, including document associations and custom fields. Ask the vendor to demonstrate how the requested fields are populated, how reviewers record progress, and what configuration is needed to support your process.

Compare the migration service, configuration, and total cost

A product’s import features and the work included in its migration service are separate questions. An import tool may be available while data cleanup, field mapping, document matching, or acceptance testing remains the customer’s responsibility. A vendor-led project may cover some of those tasks, but its scope needs to be explicit.

Use the same migration inventory with each vendor. Include document counts and formats, existing metadata, amendments and attachments, relationships between agreements, permissions, and any historical records that must remain available. Ask which items can be transferred directly, which need transformation, and which require a separate archive.

Compare licensing on the same basis. For example, Zefort’s AI custom metadata documentation places the capability in its Advanced AI package, while Fabasoft’s service description identifies separate licensing for contract-type recognition and metadata extraction. For all four platforms, obtain a quote covering the actual features, processing volumes, users, configuration, and migration services required.

Include your own team’s work in that comparison. A lower subscription price may not mean a lower total cost if the migration requires substantially more preparation or ongoing administration. Equally, a more configurable workflow is useful only if the organization can maintain it.

A useful migration pilot tests difficult contracts

A demonstration built around one clean, recent PDF tells you little about a portfolio containing scans, amendments, inconsistent metadata, and documents in several languages. The pilot should represent the material the organization actually intends to move.

1. Define what should be transferred and what should be extracted. Identify existing values that should be preserved, gaps for AI to fill, and internal information that cannot be inferred from the documents. Agree which source takes priority if values conflict.
2. Use the same documents and data with every vendor. Check that agreements, amendments, and attachments arrive in the intended records. Reconcile document and record counts and investigate failed or duplicate imports.
3. Test standard and custom extraction. Ask each vendor to configure the same additional field. Record who can make the change, how much setup it requires, and how it is applied to existing contracts.
4. Look behind the extracted value. Use an ambiguous renewal term or a conflicting amendment. Ask the reviewer to locate the relevant wording and explain which value should be used.
5. Correct a value and process the document again. Check whether the correction is preserved, replaced, or presented for another review. Inspect the available history and whether it identifies the change, the user, and the time.
6. Move from one contract to the portfolio. Test review status, bulk actions, permissions, and exception handling. Confirm what a bulk confirmation changes and how unresolved records remain visible.
7. Use the migrated information in daily work. Find upcoming renewals, update an owner, add a new field, and produce a report. Record the remaining manual work and confirm which features and services are included in the quote.

A useful pilot leaves the team with evidence about both data quality and operating effort. Measure how much work it takes to reach an acceptable record, how exceptions are handled, and whether the same process remains manageable across the full portfolio.

Where Zefort fits in an existing contract migration

Zefort can support the migration project and the contract management work that follows. In the Rovio customer case, the company commissioned a migration project from Zefort to move more than 15,000 documents from its previous system. This provides a concrete example of vendor-supported migration, while the scope of each new project still needs to be agreed.

For your own migration, that discussion should cover data preparation, field mapping, document relationships, and acceptance criteria. Specify which metadata, attachments, and historical information need to move and how their completeness will be checked.

Once the portfolio is in Zefort, custom metadata and AI-assisted extraction can support additional information needs. Reviewers can check and correct values, and teams can use the resulting metadata for search, filtering, and reporting. Internal owners, supplier categories, and other management fields can be maintained as responsibilities and reporting needs change.

These capabilities make Zefort relevant to organizations evaluating a supported migration with configurable contract data. The pilot should establish how well that combination fits the organization’s requirements, using the same tests applied to the other platforms.

How to choose a CLM platform for an existing contract portfolio

The public documentation supports comparing specific workflows. It does not establish a universal ranking for migration quality, extraction accuracy, or ease of ongoing management.

All four platforms provide capabilities relevant to maintaining contract records after import. The decision should therefore follow the results of the pilot and the proposed implementation scope:

• Migration completeness: Can the agreed documents, data, and relationships be transferred and reconciled?
• Extraction and configuration: How well does the system populate the required fields, and who can adjust them?
• Review and correction: Can reviewers trace values, resolve exceptions, and understand what happens when analysis is repeated?
• Ongoing administration: Can the team maintain owners, fields, permissions, reminders, and reports without excessive support?
• Total cost and responsibility: What is included, what remains the customer’s work, and what will future changes cost?

A platform may perform well on standard extraction while requiring more work for your custom fields or existing data structure. Another may offer extensive configuration that your team does not need. The useful comparison is the effort and reliability of completing your actual migration and maintaining the portfolio afterward.

Human judgment remains necessary when an agreement is ambiguous or an amendment changes an earlier term. The system should help the team locate the evidence, record its decision, and carry that information forward.

Key takeaways

• Migrating an existing contract portfolio involves documents, metadata, relationships, and access requirements. Agree what must be preserved and how the transfer will be checked.
• Metadata extraction can fill information gaps. Custom fields and AI custom extraction support organization-specific needs, but field configuration and automatic population should be evaluated separately.
• Zefort, ContractHero, Contractify, and Fabasoft Contracts have overlapping capabilities for maintaining contract information. Compare specific workflows and configuration requirements rather than treating shared capabilities as exclusive advantages.
• Review controls need to be tested in context. Field-level verification, contract-level status, bulk updates, change history, and correction handling answer different operational questions.
• Zefort offers custom metadata, AI-assisted extraction, review tools, and migration projects. Assess their fit through the same portfolio-based pilot used for the other vendors.
• A useful pilot tests difficult documents, existing metadata, custom fields, and deliberate corrections. Combine those results with an agreed migration scope and a complete cost comparison.