Contract review
Classify documents, summarize key terms, identify missing clauses, and route exceptions for human review.
Legal document intelligence
Turn contract review into a governed, searchable, auditable workflow
DigiScience helps legal and operations teams build document intelligence for clause extraction, obligation tracking, review queues, legal knowledge search, and audit-ready evidence.
Review with accountability
The workflow surfaces clauses, obligations, risks, and source references while legal owners remain accountable for decisions.
Legal AI workflow modules
Clause extraction
Extract termination, renewal, liability, data protection, payment, jurisdiction, and obligation clauses with source references.
Legal knowledge assistant
Search across contracts, playbooks, templates, policies, and prior guidance with access control and audit trail.
Pilot success criteria
A credible pilot should measure review productivity, extraction precision, exception routing quality, user confidence, and auditability.
Document ingestion and classification
Clause and obligation extraction
Review queue and approval workflow
Audit trail and source traceability
Pilot blueprint
Data inputs
One contract family, approved templates, clause playbooks, obligation categories, policy documents, metadata, and controlled prior guidance.
Reference architecture
Document repository → secure ingestion and OCR → classification and extraction → retrieval and comparison → legal review queue → approval → source traceability and audit.
Target measures
Review time, extraction precision and recall, clause exception quality, obligation completeness, source-link accuracy, reviewer acceptance, and audit completeness.
How do we verify an extracted renewal or notice obligation before relying on it?
Keep the extracted statement connected to its document version, exact source and review decision. Separate finding words in a document from deciding their legal effect. Missing dates, conflicting amendments or ambiguous parties should enter a review queue rather than become an automatically accepted obligation.
Begin with one document family and an approved review playbook. Ask the buyer's legal reviewer to label a representative sample, including amendments, poor scans and absent clauses. Agree what counts as a correct extraction before evaluating the system.
A source-to-review worksheet
| Field | What to capture | Expected review outcome |
|---|---|---|
| Document and revision | Document ID, version and related amendments | Reviewer identifies the applicable source set |
| Source evidence | Page or section and the extracted passage | Reviewer can locate and compare the source |
| Candidate obligation | Action, responsible party and relevant condition | Accept, correct or reject the candidate |
| Date components | Trigger, stated period and required reference date | Missing components remain unresolved |
| Uncertainty and disposition | Conflict, missing evidence, reviewer and decision | Clear owner and next action before reliance |
Worked fictional example
In an invented contract, section 8 refers to notice “30 days before renewal,” but the extracted record contains no confirmed renewal date. A second uploaded document appears to amend the notice provision. The workflow should retain both source references, mark the date and applicable wording unresolved, and ask the authorized reviewer to determine which provisions apply.
It should not choose today's date, assume the newest filename controls or issue a notice automatically. This example illustrates a review design; it is not a customer result or legal interpretation of an actual contract.
Measure extraction separately from legal judgment
On the labelled sample, precision is correct extracted items divided by all extracted items; recall is correct extracted items divided by all reference items. Define item matching consistently. Report missing fields, wrong source references and unresolved cases alongside these measures.
A model confidence score can help route review, but is not proof that an obligation is legally correct. Choose thresholds from the task's evidence and consequences; this worksheet sets no universal pass score.
Choose a bounded next step
A Solution Assessment can examine one document-review problem and recommend a workflow and implementation brief. It does not replace legal advice or include coding, a working proof of concept or production integration. Review the document-intelligence blueprint, then describe the review decision without sending confidential contracts through the public form.
Start with one document family and one review workflow
Expand after accuracy, source traceability, governance, security, user acceptance, and legal accountability are clear.
Discuss legal document AI