How to Automate Legal Intake–Triage to Boost Speed and Control

Knowledge workers spend nearly 20% of their time searching for information (McKinsey). In legal, that translates to delayed deals, invisible risk, and burned-out teams. The highest-leverage fix isn’t another email alias—it’s an intake–triage system that routes every request to the right policy, template, or person on the first try.

What “Good” Legal Intake–Triage Looks Like

A modern intake–triage flow does three things well:

- Captures structured context up front (counterparty, jurisdiction, data types, contract value, timelines)

- Applies clear decision logic based on risk and complexity

- Resolves routine work automatically, and escalates exceptions with a crisp brief

Think in tiers. Tier 0: self-serve answers and pre-approved language. Tier 1: low-risk approvals with guardrails. Tier 2: medium complexity routed to the right specialist. Tier 3: novel or high-risk matters for senior counsel. Service Level Agreements (SLAs) set expectations for response and turnaround; the triage layer enforces them.

Strength Through Layers: Playbooks + Data + Agents

Teams don’t scale on heroics—they scale on layers. Start with crafted precision in your playbooks: the “company position” on indemnity caps, data transfer clauses, and security questionnaires. Add structured data so each decision builds on the last: risk thresholds, approved templates, fallback positions, and signatory limits. Then introduce AI (Artificial Intelligence) agents to operationalize knowledge:

- Classify intent: Is this an NDA, DPA, or a pricing exception masquerading as legal?

- Risk-score requests using contract value, data sensitivity, and counterparty risk

- Auto-answer FAQs with citations to the policy or clause library

- Pre-fill templates with CRM data and route for e-sign when within thresholds

- Escalate with a tidy brief: key facts, suggested positions, and open questions

On Sandstone, these layers work naturally with the way legal already operates: your intake forms, your positions, your workflows. Agents don’t replace judgment—they make it available at scale.

A Workflow Example: Vendor NDA → MSA, End to End

Let’s ground it in a common path where speed matters: a vendor starts with an NDA, then moves to an MSA.

1) Intake: Requester selects “Vendor NDA.” The form captures vendor name, region, data types, and urgency. The agent detects that the vendor is already in the system.

2) NDA resolution: If within policy, the agent generates the company-standard NDA, maps fields from the vendor record, and routes for e-sign. If the vendor insists on its paper, the agent flags redlines required by policy (e.g., mutual vs. unilateral confidentiality) and suggests playbooked alternatives.

3) Auto-anticipation: The agent sees a purchase order in procurement and predicts an MSA is next. It launches a short follow-up intake to capture contract value and services scope.

4) Risk scoring: Using value thresholds and data sensitivity, the agent assigns Tier 1 (low) or Tier 2 (medium) and proposes the correct template. For low-risk deals, it inserts pre-approved fallbacks; for higher risk, it assembles a counsel brief with playbook positions and unresolved issues.

5) Handoffs and systems: If approved, the agent pushes metadata to CLM (Contract Lifecycle Management), updates the vendor record, and posts a status update in the requester’s channel. All steps are tracked against SLAs.

The outcome: NDAs are handled in minutes, low-risk MSAs in hours, and counsel time is focused on the 10–20% that truly need judgment.

Measure What Matters: KPIs and Thresholds

If you can’t see it, you can’t scale it. Instrument these KPIs from day one:

- Auto-resolution rate: % of requests closed without attorney intervention

- Time to first response: from submission to acknowledgment (target minutes, not days)

- Cycle time by tier: T0/T1 measured in minutes–hours; T2/T3 in days

- Escalation quality: % of escalations with complete briefs and correct routing

- Policy adherence: variance from approved positions by clause or category

- Knowledge reuse: frequency of playbook or template reuse per matter type

Aim to move 30–50% of intake into T0/T1 within the first quarter, then ratchet thresholds carefully as confidence grows.

One Practical Next Step

Run a two-week triage pilot on a single high-volume queue (e.g., NDAs or vendor reviews):

- Define three thresholds: deal value, data sensitivity, and non-standard terms that force escalation

- Publish a one-page playbook with default and fallback positions

- Launch a structured intake form that collects the three threshold inputs

- Deploy a triage agent limited to T0/T1 decisions; require a brief for anything it escalates

- Baseline the four KPIs above; compare week 1 (manual) vs. week 2 (agent-assisted)

Success looks like faster first responses, fewer back-and-forths, and cleaner escalations—without increased risk.

The Bedrock of Trust and Growth

When intake and triage are layered—policy, data, and agents—legal stops being a bottleneck and becomes connective tissue. Every request strengthens institutional knowledge instead of burying it in inboxes. That’s the Sandstone model: strength through layers, crafted precision in playbooks, and natural integration with how your team already works. Operationalize your expertise once, and let it compound. Speed goes up, risk goes down, and trust grows across the business.