Intelligent Legal Intake: A Playbook for In‑House Legal Teams

Knowledge workers spend roughly 19% of their time searching for information (McKinsey). In corporate legal, that number spikes when intake lives across email, Slack, shared drives, and tribal knowledge. This post shows how to replace ad‑hoc triage with an AI‑assisted intake layer that routes, answers, and learns—so legal moves from bottleneck to connective tissue.

What “Intelligent Intake” Looks Like

Intelligent intake turns every request—NDAs, vendor reviews, policy questions—into structured data the moment it arrives. Instead of free‑form emails, requesters complete a guided form or chat that captures essentials: party, jurisdiction, data flows, template preference, risk flags, and due date. An AI agent classifies the matter, pre‑checks policy, and either auto‑resolves (e.g., issue a pre‑approved NDA) or routes to the right owner with a crisp brief.

On a platform like Sandstone, the intake layer is your living playbook: layered data, modular workflows, and decisions that build on each other. Agents can:

- Auto‑answer policy FAQs with cited sources from your knowledge layer.

- Preflight DPAs against your data map and standard positions.

- Generate issue lists from vendor security questionnaires.

- Pull the right template, apply playbook fallbacks, and log rationale.

Each action strengthens institutional knowledge, so the system gets faster and more precise over time.

Why It Matters: Cycle Time, Visibility, and Trust

Ad‑hoc triage hides the queue. Work piles up in inboxes; stakeholders escalate because they can’t see progress; legal becomes the blocker. Intelligent intake replaces that chaos with a visible, measurable workflow. You reduce handoffs and rework, and you can finally separate urgent from merely loud.

The biggest win is trust. When legal provides reliable SLAs, transparent status, and consistent outcomes, the business starts routing requests earlier—before risk compounds. AI‑assisted summaries and rationale also improve explainability to procurement, security, and finance. And because every step is logged against a playbook, you can audit decisions without heroics.

Just as important, intelligent intake avoids SLA theater. Instead of celebrating a 24‑hour “first response” that’s just an acknowledgement, you track the metrics that matter to your customers: time to clarity, time to safe unblock, and percentage auto‑resolved with zero escalation.

How to Implement in 30/60/90 Days

Start small, ship value, then layer on complexity.

- Days 1–30: Baseline and blueprint

- Instrument today’s intake (email aliases, Slack channels) to tag request type, owner, and outcome.

- Identify your “pattern matters” (e.g., NDAs, DPAs, marketing review) and codify approved positions and fallbacks.

- Stand up a single front door with a short form or chat. Map fields to matter types and owners.

- Days 31–60: Automate the obvious

- Enable an AI agent to classify requests, populate briefs, and route with service levels.

- Auto‑resolve low‑risk NDAs and policy FAQs with citations to your playbook.

- Preflight vendor intake: collect data flows, link to your privacy register, flag gaps for security.

- Days 61–90: Layer knowledge and controls

- Add redline copilots that propose playbook‑aligned edits with rationale.

- Introduce approval gates for exceptions and high‑risk jurisdictions.

- Push status and outcomes to business systems (Salesforce, Jira, procurement) to reduce back‑and‑forth.

Sandstone is designed for this “strength through layers”: start with intake, add crafted precision on positions, and integrate naturally with where your teams already work.

KPIs That Beat SLA Theater

Measure what customers feel and what the system learns.

- Time to clarity: minutes from submission to a clear next step (auto‑resolve, assigned with scope, or info request).

- Time to unblock: working hours to a safe path forward (e.g., signed NDA, approved vendor decision, approved creative).

- Auto‑resolution rate: percentage handled without human touch within policy guardrails.

- Rework rate: matters reopened due to missing info or mis‑routing; use this to fix forms or playbooks.

- Exception rate and rationale capture: how often you deviate—and why—to refine standards.

- Requester CSAT: quick thumbs‑up/down with a comment on usefulness and speed.

When these improve, legal’s reputation improves—and demand moves earlier in the cycle, where risk is cheapest to address.

Guardrails: Privacy, Security, and Change Management

AI should never be a black box in legal. Keep humans‑in‑the‑loop for high‑risk changes; require explicit approvals for non‑standard terms; and log every decision with sources. Use tenant‑isolated models and limit data exposure by design. For privacy work, ensure your agent references authoritative data maps and records of processing, not stale spreadsheets.

Change management matters as much as models. Publish your playbooks, announce the new front door, and close side doors over time. Celebrate quick wins (e.g., 60% faster NDAs) and share rationale so partners in sales, security, and procurement understand the “why.”

Note: This article is for informational purposes only and does not constitute legal advice.

One Practical Next Step

Run a one‑week intake sprint. Pick one pattern matter (NDAs). Stand up a simple front door, capture three fields (counterparty, template, effective date), and auto‑issue approved forms. Add an agent that classifies and routes exceptions with a one‑paragraph brief. Measure time to clarity, time to unblock, and requester CSAT. Use the results to prioritize your next workflow.

When legal becomes a living operating system—where every intake, triage, and decision compounds knowledge—you trade reactive firefighting for scalable, streamlined operations. That is the foundation of trust and growth. Sandstone turns this into practice: layered data, crafted workflows, and natural integration that make legal the connective tissue of the business.