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What is Legal Intake & Triage Automation & Why Do In‑House Legal Teams Need It?

A practical primer on modern legal intake and triage automation—what it is, why it matters to in-house legal, how AI agents operationalize playbooks, and a 30‑day plan to get started.

Jarryd Strydom

September 21, 2025
By some estimates, in-house lawyers spend up to a third of their week wrangling intake—emails, chat pings, and half-filled templates. That is cycle time where risk is not reduced and deals do not move. The fix is not another shared inbox; it is a smarter intake and triage layer that captures context, applies your playbook, and routes work with decision logic built in.

The Intake Problem: Where Work Goes to Die

Most legal requests arrive without the basics: who the counterparty is, what the spend is, what the deadline is, and which template or position applies. Work stalls as lawyers chase context, reclassify requests, and manually assign owners. The result is a noisy queue, inconsistent decisions, and limited visibility for the business.
A modern legal org needs intake that behaves like an operating system: standardized data capture, predictable routing, embedded guidance, and auditability. When intake is structured and decisions are repeatable, the team moves faster with less variance—and knowledge compounds instead of disappearing in email threads.
What Intake & Triage Automation Actually Is
Intake and triage automation combines structured forms, routing rules, and AI agents that apply your playbooks in real time. Concretely, it means:
  • Smart request capture via web, Slack, or email that asks only the questions needed for each request type.
  • Automated classification and routing based on risk, value, region, or product line.
  • Policy and playbook enforcement at the edge—preferred templates, fallback positions, and escalation thresholds.
  • A knowledge layer that remembers prior decisions and surfaces them as recommendations.
  • Closed-loop updates back to the requester and systems of record.
On platforms like Sandstone, this becomes a living, AI-powered operating system: each intake strengthens the knowledge layer; each decision is logged, searchable, and reusable across future work.

Why GCs and Legal Ops Need It Now

  • Speed without shortcuts: Cut time to first response and reduce cycle time by resolving low-risk work automatically.
  • Consistency at scale: Encode positions once; apply them the same way across regions, products, and counsel.
  • Risk visibility: See what is in the queue, what is blocked, and why exceptions are happening.
  • Lean team leverage: Let AI handle context gathering, classification, and first drafts so attorneys focus on judgment calls.
  • Better business experience: Clear status updates, predictable SLAs, and fewer back-and-forths.

A Workflow Example: AI Agent-Powered NDAs

Consider the highest-volume legal request in most companies—the NDA. Here is how an AI agent on Sandstone can handle end-to-end:
  1. A salesperson submits an NDA request in Slack. The form expands dynamically to capture counterparty, governing law needs, and urgency.
  2. The agent classifies the request as mutual, low-risk, and routes to the standard template. It pulls the latest positions from the knowledge layer.
  3. The agent pre-fills parties, pulls the counterparty address from the CRM, and applies fallbacks where needed (e.g., 2-year term if 3-year is not allowed).
  4. If the counterparty insists on their paper, the agent checks for known clauses and flags deviations from policy with plain-language explanations.
  5. For standard cases, the agent returns a signature-ready draft with a tracked-changes summary, updates the requester, and logs decisions for reporting.
  6. Exceptions auto-escalate to the right attorney with full context so review starts at 80% complete, not from scratch.
This is intake and triage as connective tissue—natural in the tools people use, crafted to your contours, and layered so each decision improves the next.
How to Get Started in 30 Days
  • Week 1: Identify one high-volume, low-to-medium risk workflow (NDAs, vendor DPAs, marketing reviews). Document the must-have fields and the 10 core positions.
  • Week 2: Build a dynamic intake form and routing rules. Define SLA tiers and escalation thresholds.
  • Week 3: Encode positions and fallbacks in your knowledge layer. Connect Slack and email for submission and updates.
  • Week 4: Pilot with a friendly business unit. Track time-to-first-response, auto-resolution rate, and exceptions. Iterate playbook language based on actual deviations.

Actionable next step: Pick the single workflow with the most volume and write a one-page playbook—positions, fallbacks, and redline guidance. If you do only this, you unlock 80% of the value of automation.

Metrics That Prove ROI

  • Time to first response: Measures perceived responsiveness and queue health.
  • Cycle time by request type and risk tier: Shows where automation or playbook clarity removes friction.
  • Auto-resolved rate: Percentage of requests closed without attorney intervention.
  • Exception rate and top deviations: Where to refine positions or train the business.
  • Queue aging and SLA attainment: Operational discipline and forecasting signal.
  • Requester satisfaction: The simplest proxy for business trust.

The Foundation for Trust and Growth

When intake becomes a living system—layered data, modular workflows, and decisions that build on each other—legal shifts from reactive support to a proactive force. Sandstone’s knowledge layer turns every request, triage, and decision into an asset the whole company can rely on. That is the bedrock of scalable, streamlined legal operations: speed with alignment, precision without friction, and a foundation of trust that lets the business move with clarity and confidence.

About Jarryd Strydom

Jarryd Strydom is a contributor to the Sandstone blog.