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What Is AI Intake Triage & Why Do In‑House Legal Teams Need It Now?

AI-powered intake and triage turns legal from a bottleneck into a growth enabler by standardizing requests, routing work with precision, and activating playbooks automatically. Here’s how modern…

Jarryd Strydom

September 18, 2025
Up to 40% of inbound legal requests in many mid-market and enterprise teams are misrouted, missing context, or duplicative—meaning nearly half your queue is noise before work even starts. That’s not a resourcing problem; it’s an intake and triage problem. The fix is now within reach with AI.

The Bottleneck You Can Actually Fix

Legal can’t control demand, but it can control how demand enters the system. When requests arrive via email, Slack, and hallway conversations, three things happen: context gets lost, priorities blur, and cycle times balloon. The result is a perception that legal is slow—even when the team is sprinting.
AI intake triage solves this upstream. It intercepts requests where they start, gathers the context legal needs, and routes work to the right path—automatically. The payoff is immediate: fewer back-and-forths, cleaner queues, faster cycle times, and clearer expectations for the business.
What AI Intake Triage Actually Is (Without the Hype)
At its core, AI intake triage is a structured front door plus a smart router:
  • Structured intake: Forms, Slack apps, or email capture that require key fields (counterparty, jurisdiction, contract type, deadlines) and attach relevant documents.
  • Classification: AI reads the request and documents to identify the matter type, urgency, risk signals, and whether legal is even needed.
  • Routing: Requests land in the correct workflow—self-serve, legal review, procurement, privacy, or outside counsel—based on rules and playbooks.
  • Activation: The right template, position playbook, or approval path kicks off instantly.
  • Feedback loops: Requesters get status updates; legal gets analytics by source, type, and cycle stage.
On Sandstone, this becomes a living operating system: your playbooks, positions, and workflows are layered data that the AI can reference and refine. Every intake strengthens future decisions instead of starting from scratch.

A Day in the Life: AI Agents Orchestrating NDA Intake

Take NDAs—high-volume, low-complexity, and a perfect place to start.
  1. A salesperson submits an NDA request via Slack. The Sandstone bot asks two clarifying questions, pulls the counterparty name, use case, and governing law from the form and attached PDF, and checks for an existing agreement.
  2. Classification identifies “Mutual NDA, standard terms, low risk.” The AI triggers a self-serve workflow: generates the latest approved template with deal-specific data, applies the correct fallback positions, and sends it to the requester for e-sign.
  3. If the counterparty paper arrives, the agent flags non-standard clauses (unlimited liability, data residency inconsistencies), attaches the relevant playbook guidance, and routes to the right reviewer with a summary of issues and recommended redlines.
  4. Throughout, the requester sees status and SLAs. If the request is a duplicate or non-legal, the agent closes the loop with a friendly explanation and a pointer to the correct business process.
The net effect: legal’s time shifts from triage and chasing context to high-value judgment calls. Cycle time drops. Trust rises.

The Metrics That Matter

To move beyond anecdotes, track a small set of KPIs before and after you stand up AI intake triage:
  • Intake quality score: Percentage of requests that arrive “review-ready” (all mandatory fields and docs present).
  • Auto-resolution rate: Share of matters deflected to self-serve or non-legal pathways without human review.
  • Cycle time by matter type: Especially for NDAs, DPAs, SOWs, marketing reviews, and vendor onboarding.
  • Rework rate: How often legal has to chase missing info or reassign matters.
  • SLA adherence and requester CSAT: Simple survey on clarity and speed.
Sandstone’s knowledge layer ties these metrics to the underlying playbooks and positions. When a fallback is overused or a clause drives delays, you see it—then tune the workflow, not just push the team harder.
How to Start in 30 Days
You don’t need a big-bang rollout. Layer strength the way sandstone forms—one dependable stratum at a time:
  • Pick one high-volume workflow (NDAs or vendor intake) and define “review-ready.” What fields and docs are mandatory? What auto-routes to self-serve?
  • Codify your playbook in plain language: standards, fallbacks, and deal-breakers. Keep it opinionated and short.
  • Stand up a single intake surface where your business already works (Slack, email, or a simple web form). Make it the only path.
  • Turn on AI classification and routing to three outcomes: self-serve, legal review, or redirect (not a legal matter).
  • Publish your SLA and status visibility so business partners see progress without pings.

Actionable takeaway: In the next week, implement a mandatory intake form for NDAs with five fields (counterparty, contract type, jurisdiction, effective date, urgency) and auto-routing. Measure baseline cycle time today; compare again in four weeks.

Why This Becomes Your Legal Foundation

When intake and triage are consistent, every request enriches your system: which positions speed deals, which clauses trigger escalations, which teams create the most rework. Knowledge compounds instead of disappearing. That is the shift from reactive to proactive legal.
Sandstone was built for this: layered data that gets stronger with every matter, crafted precision that fits your exact contours, and natural integration with how your teams already work. Put AI intake triage at the front door, and you turn legal from a perceived bottleneck into the connective tissue of growth—faster decisions, cleaner risk posture, and a business that runs with clarity and confidence.

About Jarryd Strydom

Jarryd Strydom is a contributor to the Sandstone blog.