Legal Ops Guide: How to Triage Intake, Automate Approvals, and Prove Value

Most in-house teams report that 60–70% of inbound requests follow repeatable patterns—NDAs, vendor reviews, marketing approvals, and routine contract edits. Yet many still triage by inbox and Slack pings. The result: long queues, invisible priorities, and slow trust leaks across the business. There’s a better way: layer structured intake, a simple triage matrix, and AI-driven first-mile automation to move fast without adding risk.

Start With the Outcome: What Should Move First, and Why?

Before tooling, align on outcomes. Legal’s goal is not to close tickets; it’s to protect speed and reduce risk where it matters. Map your top request types and define the desired end state for each.

- Common requests: NDAs, DPAs, MSAs/SOWs, vendor due diligence, marketing/PR review, policy questions.

- Desired outcomes: signed doc within SLA, approved copy with tracked risk flags, fast “no-touch” closure for low-risk items, clear escalation for high-risk items.

- Constraints: regulatory requirements, contractual playbooks, procurement/security standards, revenue timelines.

This lens helps you draft a triage schema that is simple, teachable, and enforceable by automation.

Build a Triage Matrix That Scales Beyond the Inbox

Create a two-axis matrix: Business Criticality (Low/High) x Legal Risk (Low/High). Then attach rules.

- Low Risk / Low Criticality: auto-approve or template-only. Example: mutual NDA under threshold, standard marketing claims with pre-approved language.

- Low Risk / High Criticality: fast-track. Example: logo use in a launch blog—auto-approve with a quick AI checklist and audit trail.

- High Risk / Low Criticality: schedule review. Example: vendor with subprocessor chains—queue for specialized counsel.

- High Risk / High Criticality: escalate immediately. Example: redlines to liability caps in a late-stage deal.

Operationalize with three assets:

1) Intake form that captures key decision fields (counterparty type, data processed, revenue impact, deadlines).

2) Playbook with clear thresholds and fallback rules (e.g., “data residency change → escalate to privacy counsel”).

3) SLA ladder matched to the matrix (same-day, 2–3 days, 5+ days) with visible statuses.

Automate the First Mile With AI Agents (Without Disrupting Workflows)

Most delay happens before a lawyer ever reviews the request. Sandstone’s AI agents handle that first mile by turning knowledge into action:

- Classify and route: read email or portal intake, detect request type, and apply your triage matrix.

- Standardize artifacts: generate the right template (e.g., NDA type), load approved clauses, and pre-fill fields from CRM or procurement.

- Policy checks: compare proposed terms to your playbook; flag deviations; suggest redlines.

- Context briefs: compile a one-page summary with counterparty details, risk indicators, and recommended next step.

- Smart escalations: notify the right owner with priority, SLA, and a draft response.

Example workflow: a sales rep submits an NDA request. The agent verifies thresholds, selects the mutual NDA template, inserts the correct governing law and term from the playbook, and returns a ready-to-send draft—often without human touch. If the counterparty insists on unilateral terms, the agent flags the variance, suggests fallback language, and escalates with a context brief.

Strength through layers matters here: each triage decision and resolution updates the knowledge layer—tightening thresholds, improving clause suggestions, and sharpening routing accuracy over time.

Measure What Matters: From Tickets to Trust

Track a small set of metrics that show speed and risk control to the business and the board.

- Time-to-first-response: how long to acknowledge and classify. Target minutes, not hours.

- Cycle time by risk band: show that low-risk items move fast while high-risk items get the right scrutiny.

- Touchless rate: percent of requests resolved without lawyer intervention (for qualified scenarios).

- Deviation rate and reasons: where deals slow down and why (e.g., data residency, liability caps).

- SLA adherence and aging: surface bottlenecks early, not at quarter end.

Publish a simple monthly dashboard. Pair numbers with narratives: where automation removed friction; where playbooks need updating; where new risks emerged. This is how legal earns credibility as a proactive operator, not a reactive gate.

Practical Next Step: Run a 30-Day First-Mile Automation Pilot

Pick one high-volume, low-to-medium risk workflow. NDAs or marketing review are great candidates. Then:

1) Define the triage matrix and SLAs for that workflow.

2) Convert your playbook into structured rules and fallback positions.

3) Connect intake channels (email alias, portal, Slack) to an AI agent.

4) Measure baseline metrics for one week; then switch the agent on.

5) Review results weekly; tune thresholds; expand to the next workflow.

Your goal: cut time-to-first-response to under 10 minutes and achieve a 50%+ touchless rate for qualifying requests—while keeping an audit trail that strengthens compliance.

Closing: Make Legal the Bedrock of Speed, Alignment, and Trust

When intake is structured, triage is explicit, and the first mile is automated, legal stops being a bottleneck and becomes the connective tissue of the business. Sandstone turns layered knowledge—playbooks, positions, and workflows—into a living operating system where every request improves the next. The payoff is simple: faster deals, clearer risk decisions, and a foundation of trust that scales with the company.