Feature
Legal workflow automation with task-scoped agents
Operational outcome: automate repetitive legal ops tasks with auditable agent runs and measurable completion quality.
NDA Agent
Captures intake, validates key fields, and creates an NDA draft.
Review Agent
Starts contract review and produces a practical action summary.
Redline Agent
Suggests safer language based on high-risk clause findings.
Intake Agent
Collects jurisdiction and urgency details and submits lawyer queue intake.
Agent run lifecycle and control points
Legal teams adopt agents successfully when runs are deterministic, auditable, and easy to recover on failure. Each LegalDoc run follows a defined lifecycle so operations leaders can monitor reliability at scale.
Queued
Run is accepted with validated input and ownership context.
Processing
Agent executes task-specific workflow steps and records intermediate logs.
Complete
Output artifacts and summaries are attached for user review and downstream actions.
Failed
Failure reason is captured so users can retry with corrected data.
Execution boundaries for legal agents
Legal workflow automation agents should run within explicit control boundaries so teams can trust outputs and explain outcomes. Treat agents as orchestrated workflow accelerators, not autonomous legal decision makers.
Scope boundary
Each agent is task-scoped and cannot perform arbitrary legal reasoning outside configured workflow actions.
Approval boundary
Agent output must be reviewed by legal team members before acceptance or external commitment.
Data boundary
Runs remain ownership-scoped with traceable status, input payloads, and artifact references.
Teams and workflows best suited for agents
- Use NDA Agent for repeat intake and first-draft creation.
- Use Review Agent to convert contract analysis into negotiation priorities.
- Use Redline Agent to prepare safer fallback wording before counsel review.
- Use Intake Agent to package high-risk work for lawyer queue triage.
When manual orchestration is required
- Define allowed inputs and required fields for each agent workflow before rollout.
- Set explicit completion criteria so runs can be audited as success or failure.
- Record output artifacts and decision owners for every completed run.
- Route unresolved high-risk outputs into counsel escalation workflow.
Related resources: intake policy template and reviewer calibration guide.
Agent reliability scorecard
Legal workflow automation agents should be monitored like production systems. Reliability metrics indicate whether runs are predictable, useful to reviewers, and aligned with escalation quality requirements.
Run completion rate
Track percentage of agent runs that complete without manual recovery.
Retry dependency
Track how often runs require retries to identify fragile steps in orchestration.
Output usability
Track share of runs where legal reviewers can use output artifacts without major rework.
Escalation quality
Track whether agent-generated escalation packets are accepted without missing-context callbacks.
If completion quality drops, tighten input validation and reduce agent scope before scaling to additional teams.
Agent launch phases
Phase 1: Input hardening
Restrict each agent to validated schema input and reject runs that omit policy-critical fields.
Phase 2: Output review discipline
Require reviewer acceptance criteria per agent type before outputs can drive external contract actions.
Phase 3: Scale governance
Track run quality and escalation acceptance rates before enabling broader organizational usage.
Failure recovery patterns
- On failed run, surface exact failed step and recommended input correction instead of generic error states.
- For repeated failures, route run to manual review queue with preserved intermediate logs.
- When output confidence is low, skip auto-follow-on actions and create escalation-ready summary only.
- Record retry outcomes by agent type to identify orchestration weaknesses before scale-out.
Scale readiness questions
- Do run logs make it easy to explain why outputs were accepted or rejected?
- Are failure categories stable enough to automate remediation guidance?
- Can reviewers process agent outputs without repeated manual restructuring?
- Are escalation acceptance rates holding as run volume increases?
References
Workflow readiness FAQ
Are agents autonomous?
No. Agents are scoped workflows with deterministic steps and explicit output records.
How are runs tracked?
Each run stores input, lifecycle status, output artifacts, and audit metadata.
Can I rerun a failed workflow?
Yes. Failed runs can be retried with corrected input.
Do agents provide legal representation?
No. They automate tasks and route matters, but legal advice comes from licensed professionals.
Agent governance metrics
Run-to-output latency
Measure median time from run start to usable output artifact by agent type.
Manual intervention rate
Measure percentage of runs requiring manual correction before final use.
Escalation package completeness
Measure whether agent-generated escalations include all required decision context.
Agent metrics should feed release and scope decisions directly. If intervention rates or escalation quality degrade, reduce workflow breadth and correct orchestration issues before adding new agent capabilities.
Treat agent rollout as an operations program with explicit ownership and monthly governance review. This keeps automation gains measurable and prevents silent quality erosion as workflow volume increases.
Agent adoption guardrails for multi-team rollout
Start with one team and one high-frequency workflow before enabling shared usage across the organization. Multi-team rollout should require documented runbook ownership, alert routing, and weekly exception review so operational drift is detected early.
- Do not add new agents and new jurisdictions in the same rollout sprint.
- Require baseline success and intervention-rate targets before opening broader access.
- Version prompt and policy logic so quality changes can be traced to specific releases.
Team-level rollout guidance: legal ops solution and law firm solution.