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

Most legal work goes sideways before it even starts. World Commerce & Contracting has long noted that poor contracting practices can erode close to 9% of value—much of it lost in delays and handoffs. Intake is the first mile where that friction compounds. When requests show up in email or Slack without context, when NDAs queue-hop, and when data is incomplete, cycle time balloons and risk visibility drops.

The fix isn’t a bigger portal or more forms. It’s a smarter front door: AI-powered intake triage that classifies, enriches, and routes work the moment it arrives—so legal stays fast, precise, and trusted.

The first mile determines speed and risk

Intake isn’t just an inbox. It’s where you decide urgency, owners, risk profile, and the data you’ll use downstream. If those decisions are inconsistent or slow, you feel it everywhere: contract cycle times drift, procurement stalls, and business partners go around legal.

Common failure points:

- Missed context: "Need a DPA" without deal size, data flows, or vendor status.

- Misrouting: Privacy issues land with commercial counsel—or vice versa.

- Rework: Legal has to ask basic questions two or three times.

- Shadow queues: Requests splinter across channels with no consolidated view.

AI triage reduces these failure modes by turning ad hoc requests into structured, decision-ready work. It pulls relevant details, applies your playbooks, and sends each request to the right lane—commercial, privacy, employment, or self-serve—before a human lifts a finger.

What AI-powered triage looks like in practice

Think of triage as a set of layered decisions that build on one another:

1) Capture

- Meet requesters where they are (email, Slack, forms).

- Use lightweight prompts to collect essentials (counterparty, value, region, data types, deadline).

2) Classify

- An AI agent categorizes by matter type (NDA, MSA, DPA, marketing review, subpoena) and flags sensitivity.

- It maps to your taxonomy and routing rules—not generic labels.

3) Enrich

- Auto-fetch context from CRM/ERP (deal size, vendor status), prior matters, and approved templates.

- Normalize fields (e.g., currency, region, business unit) for reporting consistency.

4) Decide and route

- Apply your playbooks: thresholds, approvers, fallback owners, SLAs.

- Auto-route low-risk work to self-serve flows (e.g., NDA via approved template) and escalate exceptions.

5) Act

- Draft first-pass responses, assign tasks, spin up a workspace, and log the matter with complete metadata.

- Keep business stakeholders updated in their channel of choice.

On Sandstone, this happens inside a living knowledge layer: your positions, playbooks, and workflows are encoded so each intake strengthens the next. Decisions become durable—layered, precise, and naturally integrated with how your team already works.

A simple implementation playbook

You don’t need a transformation program to get value. Start tight, then scale:

- Pick a high-volume lane: NDAs, vendor DPAs, or routine commercial reviews.

- Define a minimal schema: 6–10 fields you must have to work fast (counterparty, value, region, data categories, template, deadline).

- Encode decisions: Write the plain-language rules you already use (e.g., “Under $50k and standard terms = self-serve”).

- Calibrate prompts: Give the AI examples of correct classifications and routing edge cases.

- Keep humans in the loop: Require review on new categories or high-risk flags until precision is proven.

- Wire the stack: Connect email/Slack intake → Sandstone triage agent → matter system → docs and approvals.

- Roll out visibly: Publish SLAs and a single intake link in Slack and intranet. Close the back doors.

Sandstone’s layered model helps here: you can compose modular workflows, reuse decisions across matter types, and refine without breaking what’s already working. It’s crafted precision—tools carved to fit your contours, not force new ones.

KPIs that prove it’s working

Measure the first mile and the downstream impact:

- Time to first response: Minutes, not days. Target <1 hour during business hours.

- Time to route: From intake to correct owner or self-serve path.

- Auto-resolution rate: Share of requests completed without attorney touch.

- Cycle time by matter type: Especially NDAs and low-risk DPAs.

- Rework rate: Instances where legal requests additional info after intake.

- Requester satisfaction (CSAT): Quick pulse after closure.

- Legal time on task: Hours saved per matter; capacity gained for complex work.

- Exception rate: Escalations versus total volume; trend down as playbooks mature.

With consistent metadata at intake, these metrics stop being anecdotes and become operational levers you can trust.

One next step you can take this month

Stand up an AI triage pilot for NDAs:

- Create a single intake entry point (Slack app or email alias) that asks 6 fields.

- Encode the NDA playbook: template selection, thresholds, signature routing, and when to escalate.

- Let Sandstone’s triage agent classify, enrich from CRM, and auto-generate the NDA or route to counsel.

- Set an SLA (same-day turnaround). Track time to first response, auto-resolution rate, and requester CSAT for two weeks.

You’ll know it’s working when the queue is quieter, questions are smarter, and stakeholders stop asking, “Who owns this?”

The foundation for trust and growth

When intake is intelligent, legal stops being a bottleneck and becomes connective tissue. Every request strengthens your knowledge layer; every decision compounds. That’s how legal scales with confidence: layered data, modular workflows, and AI agents that make institutional knowledge actionable. Sandstone turns the first mile into an advantage—so your team can move faster where it matters and build the bedrock of trust at the heart of the business.