Discovery AI uses mappings to extract provisions from uploaded documents. For Discovery AI to do this, you must define the types of documents you expect it to receive. For example, you might define a master service agreement, a non-disclosure agreement, or a construction quitclaim. For each agreement type, you must map for extraction the provisions you anticipate in the agreement.  

Provisions can be either fields or clauses.  A field contains some measurable, normal property: a date, a percentage, a duration, or a cash value. Clauses do not have a measurable characteristic; for example, a stipulation, an indemnification clause, or a representation of fact. Access provisions through the Data Extraction Setup tab in the left navigation bar. Manage provisions using the Provision Library. 

When built-in provisions do not meet your needs, you can create and train your own custom provisions to provide bespoke extraction solutions. Mapping Data Extractions

Provisions

Built-In Provisions

Discovery AI extracts these fundamental provisions (if possible) from all contracts it reviews: 

  • Agreement Title
  • Parties
  • Effective Date
  • Commencement Date
  • Original Expiration Date
  • Termination Notice
  • Renewal Type
  • Renewal Period
  • Renewal Notice
  • Renewal Limit 
  • Signatures
  • Notice
  • Notice Address
  • Related Master Agreement Name
  • Total Contract Value

These provisions are required because without them a contract is not effective, and they are available for every Discovery AI extraction. 

You can select from the following common built-in provisions as your needs dictate:

  • Audit Rights
  • Pricing/Billing Frequency
  • Data Security Breach Notification
  • Dispute Resolution
  • Exclusivity/Not granted
  • Exclusivity/Required
  • Governing Law
  • Indemnification Provision
  • Non-Solicitation Period
  • Pricing/Payment Model
  • Pricing/Payment Terms

Additionally, you can pick specialized terms from our library of over 1,200 provisions for extraction. These are specialized for several industries and improve the granularity and specificity of your extractions.

Note

Not all provisions are available for attorney review with Verified Extraction. If you need Verified Extraction, you must negotiate the projected provision set with your Conga account executive. 

Mapping Data Extractions 

To set up a new data extraction map

  1. Click the Data Extraction Setup tab in the left navigation bar to raise the Data Extraction Setup window.
  2. Click the New button to raise the New Document Extraction Mapping popup.
  3. Give the new mapping a name, enter a brief description, and choose a record type from the Choose database record pull-down menu. These values correspond to a particular contract or document type. For example, in a CLM deployment, this shows agreement records.
    • To remove the requirement to review, select 0 - Skip Review.

      Note:

      If any field's extracted value cannot be normalized to match its data type, the file is sent to Ready for Review and must be reviewed.

    • To use a single-stage review process, select 1- One level - Review and Complete from the "Choose review level" pulldown.
    • For a more formal process, select 2 - Two levels - Review and Approve and select one or more approver names from the "Choose reviewer(s)" menu.
  4. To let users to check out batches of documents for review, slide the Allow reviewers to get next batch toggle, then set the batch size. This convenience enables users to check out a block of records with a single "get batch" action. Users cannot request a new batch until they review or reassign all documents currently assigned to them.
  5. Depending on whether this is a purchase or vendor agreement, set the Organization Role? toggle to either Buyer or Seller.
  6. Click Save to return to the Data Extraction Setup window.  
  7. Click the name of the new mapping to raise its detail window.
  8. Click the WORKSHEETS tab. 

  9. Select the Fields or Clauses tab, then click New to raise the New Field Mapping or New Clause Mapping  popup. 

  10. For each field or clause, select:

    • A data field or clause in the CLM, CC, or CFS system (fields are at the database level, while clauses are in the clause library). If no such field or clause exists in the host app, you can create a dummy/placeholder field or clause there to complete this mapping and edit the placeholder or the mapping later.
    • The type of mapping. This is your selection from built-in extractions.

      Tip

      Hovering over a provision type in the Choose Provision field raises explanatory text describing the provision. 

    • Whether the extraction is manual or automatic 
    • Whether to extract only the clause or the entire paragraph in which it is found (clauses only)
    • Whether the extraction is required

  11. Click SAVE. 


To edit a data extraction map

  1. Click the Data Extraction Setup tab in the left navigation bar to raise the Data Extraction Setup window.
  2. Find the name of the map you will edit. 
  3. To edit the name, description, or record type, click the Edit (pen) button.
  4. To edit the provisions mapped to the named extraction, click the name hypertext in the Name column.
  5. Edit the mapping as described in To set up a new data extraction map.

To delete a data extraction map

From the Data Extraction Setup window, either click the trash can button next to any single mapping or click the checkbox next to one or multiple rows and click the DELETE button.