How to Operationalize AI Intake–Triage to Reduce Legal Cycle Time

Here’s the uncomfortable math: in many in‑house teams, 40–60% of contract cycle time leaks before Legal ever edits a clause—at intake, triage, and context gathering. The fix isn’t more headcount; it’s a front door that captures structured data, applies policy, and routes work with precision. Done right, an AI agent becomes the fastest paralegal you’ve ever hired—never tired, always on‑brand, and auditable.

Why Intake Is the Bottleneck You Can Actually Fix

Most requests show up as unstructured messages: a forwarded email, a Slack ping, a “quick question.” Legal spends days converting that fog into facts: What’s the deal type? Risk profile? Jurisdiction? Data flows? Without a common form, shared Service Level Agreements (SLAs), or a triage rubric, work stalls and context disappears into inboxes. The cost is real—slow revenue, mistrust, and inconsistent risk treatment.

Standardizing intake unlocks three compounding benefits:

- Better data: Required fields drive clean handoffs and reporting.

- Faster routing: Clear categories and SLAs reduce time-to-first-touch.

- Safer decisions: Playbooked positions are applied consistently, not from memory.

A Practical Blueprint for AI-Powered Intake–Triage

You don’t need to “boil the ocean.” Start with one high-volume, low‑to‑medium risk workflow (e.g., NDAs, vendor security reviews under a spend threshold, low-risk order forms):

1) Map request types and required fields

- Decide what you must capture up front: counterparty, contract type, governing law, data sharing, timeline, commercial owner, and links to docs.

2) Codify go/hold/escalate rules in a playbook

- Write the decision tree you wish every new hire had. Define thresholds (e.g., DPA needed if PII—Personally Identifiable Information—flows; security review only if new system of record; auto-approve if standard NDA with no edits).

3) Design the triage rubric and routing

- Owner by category, fallback assignment, and SLAs by risk tier. Include a self-serve path for truly low-risk items.

4) Implement an AI intake agent in your current channels

- Surface the same structured form in Slack/Teams, Gmail/Outlook, and a web portal. The agent should classify, validate completeness, and explain next steps in plain language.

5) Instrument metrics and feedback

- Track time-to-first-touch, auto-resolve rate, deflection to self-serve, escalation reasons, and requester CSAT.

On Sandstone, these elements live as layered objects—intake schema, playbooks, routing rules—so each request both uses and strengthens your knowledge base. When policies change, you update the layer once; every workflow benefits.

What “Good” Looks Like in Production

A request arrives in Slack. The Sandstone agent asks targeted follow‑ups only if fields are missing, then:

- Classifies the request and maps it to the right playbook.

- Runs lightweight checks (e.g., detects PII, flags nonstandard governing law, identifies data-processing needs).

- Suggests the correct template (standard NDA, DPA addendum) and pre-fills known terms from CRM/ERP.

- Applies the triage rubric: auto-approve, self-serve template, or escalate with a crisp summary and recommended positions.

- Logs everything with an audit trail for compliance and reporting.

Human-in-the-loop is mandatory for higher risk or off‑playbook items. The agent’s job is to compress “what is this and who should do it?” from days to minutes—without making silent decisions outside policy.

Guardrails That Build Trust (and Pass Audit)

Speed without safety backfires. Bake guardrails into the system:

- Data boundaries: Keep sensitive content in your tenant; redact or mask before any external model calls.

- Role‑based access: Least‑privilege on matters, documents, and fields; requester sees status, not internal notes.

- Explainability by design: Every auto‑action shows the rule invoked and the playbook version applied.

- Approval checkpoints: Require human review for changes to templates, fallback positions, or risk-tier overrides.

- DPIA (Data Protection Impact Assessment) once, version forever: Treat the intake agent as a system with a maintained register.

- Vendor hygiene: Document model providers, sub‑processors, and data retention. No “black box” shortcuts.

Metrics That Matter to the Business

Legal leaders need numbers that translate to revenue confidence and risk control:

- Time-to-first-touch and time-to-route

- Auto-resolve and self-serve rates

- Escalation mix and top off‑playbook drivers

- Cycle time by risk tier and contract type

- Requester CSAT and internal NPS

- Risk severity distribution (before vs. after playbooks)

These metrics become your operating dashboard—and your budget story.

A Two‑Week Pilot You Can Run Now

Week 1

- Choose one workflow (e.g., NDAs). Draft the intake schema and triage rubric.

- Convert your latest positions into a concise playbook: thresholds, fallbacks, red‑flag list.

- Configure the agent in one channel (Slack or email) and define SLAs.

Week 2

- Roll out to a small Sales–Legal cohort. Track completeness at submission and time-to-first-touch.

- Review escalations daily. Tighten prompts, thresholds, and templates.

- Report pilot metrics and requester quotes to stakeholders. Decide go/no‑go for the next workflow.

Actionable takeaway: Write your triage rubric today. One page, three tiers (low/medium/high), and five rules that determine route, SLA, and required artifacts. That document becomes your agent’s brain.

The Bedrock of Faster, Safer Growth

When intake, playbooks, and routing live as a layered, AI-powered system, knowledge compounds instead of disappearing into inboxes. Every request strengthens the next decision. That’s the Sandstone philosophy—strength through layers, crafted precision, and natural integration with how your team already works. Turn Legal from a reactive help desk into proactive infrastructure for speed, alignment, and trust across the business.