Why Legal Intake and Triage Matter for In-House Teams (and How to Automate Them)

Across midsize to enterprise legal teams, 50–70% of requests still land in email or chat—often missing key details like contract value, jurisdiction, or due date. That gap turns into delays, back-and-forth pings, and untracked risk. The payoff for getting intake and triage right is big: faster cycle times, fewer surprises, and a living knowledge layer that compounds with every matter.

When intake becomes a guided, AI-assisted workflow, legal shifts from a bottleneck to the connective tissue of the business. Requests arrive complete, routed to the right owner, and paired with the right playbook—so work starts immediately and decisions are captured.

Why Intake and Triage Set the Pace

- Predictability: Clear request types and required fields reduce rework and stabilize SLAs. Stakeholders get reliable timelines; legal gets fewer fire drills.

- Risk clarity: Early classification (NDA vs. MSA vs. data processing vs. marketing review) drives the right level of scrutiny. High-risk exceptions escalate; low-risk paths move fast.

- Knowledge capture: Intake is where context is richest. When it’s structured, every matter strengthens your playbooks, fallback positions, and decision logs—so the next one is faster.

For teams operating across procurement, sales, and privacy, this is the fulcrum. Intake is where upstream data (deal size, data types, vendors) meets downstream execution (templates, redlines, approvals). Tighten the handoff, and the whole system accelerates.

Common Pitfalls (And How to Avoid Them)

- Too many forms: A maze of portals drives shadow intake. Keep one front door with smart branching.

- Generic queues: A single inbox hides risk and stalls quick wins. Use routing rules by type, value, and region.

- Manual triage: Humans shouldn’t parse every email. Let an AI agent classify, extract fields, and propose next steps.

- Disconnected knowledge: If playbooks live in docs, they’re hard to apply. Embed guidance in the workflow at the moment of work.

- No feedback loop: Without outcome data, you can’t improve your fields, rules, or SLAs.

How to Get It Right

1) Define the front door

- Offer one intake entry—web form plus Slack/Teams handoff—to meet requesters where they work.

- Keep it minimal: request type, urgency, counterparties, value, jurisdiction, data sensitivity, due date. Let follow-up questions branch dynamically.

2) Standardize request types

- Start with 6–8 high-volume categories (NDA, sales contract, vendor onboarding, marketing review, privacy request, policy question). Align templates and playbooks to each.

3) Automate triage and routing

- Use rules and an AI classifier to assign owner, set priority, and flag risk markers (e.g., personal data, cross-border, unusual indemnity).

- Auto-create matters in your tracker with all metadata, so reporting “just works.”

4) Put playbooks in the flow

- Embed clause guidance and fallback positions at the point of review. Turn scattered notes into structured decision trees.

- Suggest the right template on intake; pre-fill with known data.

5) Orchestrate approvals and escalations

- Trigger privacy/security reviews based on answers (e.g., DPIA needed if special data categories).

- Capture approvals in-line and link them to the matter record for audit-readiness.

6) Close the loop and learn

- Require a close reason (signed, blocked, withdrew, superseded) and capture non-standard terms.

- Feed outcomes back to update fields, playbooks, and routing logic.

What to Automate with AI Agents (On Sandstone)

- Intake Agent: Conversationally collects missing details in Slack/Teams or email, normalizes to your schema, and opens the matter with full metadata.

- Classifier Agent: Reads requests and attachments, tags request type, risk level, and jurisdiction, then applies the right workflow.

- Playbook Agent: Surfaces clause guidance and fallback positions as you review, drafts responses, and explains tradeoffs in plain language.

- Approvals Agent: Detects when privacy/security/finance sign-off is needed and runs the sequence asynchronously—no chasing.

- Decision Logger: Captures deviations from standard, links to the underlying rationale, and updates your knowledge layer so the next review is faster.

Sandstone’s design mirrors how high-performing teams work: layered data, modular workflows, and decisions that build on each other. It integrates naturally with your existing stack (email, Slack/Teams, Salesforce, Jira) so adoption is frictionless, not forced.

One Actionable Next Step

Pilot a single, high-volume request type—NDAs. Define 6 must-have fields, wire an intake form plus Slack handoff, route to the right owner, and embed a one-page playbook with fallbacks. Track three metrics for 30 days: median cycle time, completion on first pass, and requester satisfaction. Use the insights to extend to MSAs and vendor reviews.

The Bottom Line

Structured, automated intake and triage turn legal from a reactive inbox into a proactive operating system. When every request enters through one smart front door and every decision feeds a living knowledge layer, speed and trust compound. That’s the promise of scalable legal operations—and it’s the bedrock Sandstone is built to deliver. Read more.