Why AI Intake Triage Matters for In‑House Legal Teams (and How to Get It Right)

Every week, more than half of legal requests hit legal through email, chat, or ad hoc forms. That unstructured reality is why intake is either your biggest accelerator or your biggest drag. When triage is manual, lawyers become switchboard operators. When triage is AI‑assisted and grounded in your playbooks, legal becomes a force multiplier.

Why AI-Powered Triage Matters Now

Legal demand is up, headcount is flat, and the business expects answers in minutes, not days. Intake triage is where speed, accuracy, and risk posture collide. AI can classify matters, pull context, and route to the right workflow in seconds, but the real value comes when that intelligence is anchored to your policies, templates, and positions.

Done well, AI triage reduces context switching, enforces consistency, and creates a living data set about what the business asks legal to do. That data powers better resourcing decisions, more accurate SLAs, and a virtuous cycle of automation. Most importantly, it turns institutional knowledge into a system: who handles what, which clauses are approved, when procurement or security must weigh in. On a platform like Sandstone, that knowledge becomes executable — not just documented — so every intake strengthens your legal foundation.

The Common Pitfalls That Slow Teams Down

- Unstructured requests: Free-form emails lack the fields you need for risk, routing, and reporting.

- Tribal routing: Work gets assigned based on who yells loudest in chat, not expertise or bandwidth.

- Context gaps: Legal loses time chasing missing details such as contract value, data flows, or counterparties.

- Inconsistent playbooks: Guidance lives in static docs. People can’t find the right clause or exception standard when it matters.

- Shadow workflows: Sales, Finance, and Security have their own processes. Without integration, legal becomes the blocker by default.

These patterns are solvable with an intake agent that knows your playbooks, collects the right information by request type, and orchestrates handoffs across systems.

How to Get It Right: A Practical Blueprint

1) Define your top request types. Start with the 3–5 categories that drive 80% of volume: NDAs, vendor reviews, sales contracts, marketing approvals, policy questions. For each, list the minimum fields legal needs to triage confidently.

2) Encode playbooks as positions, not prose. Convert guidelines into structured rules: approved clauses, fallback options, escalation thresholds, mandatory reviewers, and SLA targets. This is the knowledge layer your AI should reference on every request.

3) Stand up a single front door. Centralize intake in one channel with smart forms or a chat assistant that can classify, ask follow-up questions, and capture attachments. Keep it where your business already works (email, Slack, Salesforce), but maintain a single source of truth behind the scenes.

4) Automate classification and routing. Use an AI agent to tag request type, risk signal, business unit, and urgency, then auto-assign to the right owner or queue. Include auto-invites to Security, Privacy, or Procurement when thresholds are met (for example, personal data in scope or deal size over a set amount).

5) Enrich with context automatically. Pull the account from CRM, the vendor from your vendor master, and the latest approved templates from your clause library. Pre-fill checklists and surface relevant positions so attorneys start in motion.

6) Create outcome-driven workflows. For each request type, define the happy path and the off-ramps: redlines, approvals, exceptions, and sign-off. Track timing and outcomes to evolve your playbooks with evidence, not anecdotes.

7) Close the loop and learn. On completion, capture final status, cycle time, and exception reasons. Feed that data into dashboards for capacity planning and into the AI so routing and guidance improve over time.

On Sandstone, these steps map cleanly: positions become machine-readable rules, forms and chat become the front door, and agents handle classification, enrichment, routing, and checklists. The outcome is a cohesive operating system, not another point tool.

A Quick Vignette: Sales NDAs at Scale

A growth-stage company saw NDAs clogging legal’s queue. With AI triage, the NDA agent classifies the request in Slack, confirms counterparty and jurisdiction, pulls the latest template, and checks if mutual vs. one-way is permitted under policy. If there is no PII or export-control risk and value is under a threshold, it auto-generates and returns a signature-ready document in minutes; exceptions route to counsel with context and recommended fallbacks. Result: hours saved weekly and fewer off-template versions in the wild.

Your Next Step

Pick one request type and implement the front door start to finish. Define required fields, encode a simple playbook (approved template plus two fallbacks), and set auto-routing. Measure cycle time and exception rate before and after. Expect a 20–40% faster turn on that category within the first month — because the work starts complete and the decisions are repeatable.

The Bigger Picture: A Stronger Legal Foundation

Intake is not just productivity plumbing. It is how legal operationalizes judgment at scale. When your playbooks and decisions are layered into an AI-powered workflow, every request compounds institutional knowledge instead of dispersing it. That is the promise of Sandstone: crafted precision in how your team works, natural integration with the tools you already use, and strength through layers so business and law move in harmony.

Make intake the strongest layer in your stack, and the rest of legal moves faster with greater trust.