How to Build an AI Intake–Triage Engine to Speed Legal Response

How to Build an AI Intake–Triage Engine to Speed Legal Response

In most in-house teams, over half of inbound requests are routine—yet they arrive as scattered emails and DMs that bury risk and slow revenue. Industry reports from ACC (Association of Corporate Counsel), CLOC (Corporate Legal Operations Consortium), and Thomson Reuters consistently show rising matter volumes without corresponding headcount. The fix isn’t more triage meetings; it’s a system. This is where an AI-powered intake–triage engine turns chaos into flow.

Sandstone’s view: legal should be the connective tissue of the business. An AI-backed operating layer makes playbooks and positions actionable at the moment of intake—so every request strengthens your foundation, not your inbox.

Why It Matters Now

Legal is already the system of record for risk, but not always the system of action. When Sales–Legal handoffs happen in email threads, you lose context, service levels, and learning loops. Response times slip, teams escalate unnecessarily, and institutional knowledge disappears with the messenger.

A dedicated intake–triage engine centralizes demand, applies consistent rules, and routes work by risk. The benefits compound:

- Faster cycle time and predictable SLAs (Service Level Agreements)

- Fewer escalations and cleaner handoffs with Sales, Finance, and Security

- Playbooks applied consistently, not selectively

- Data for KPIs (Key Performance Indicators) and capacity planning

On platforms like Sandstone, AI agents can classify, route, and even draft first-pass answers—so attorneys focus where judgment matters.

Definitions And Scope

- Intake: the single front door where all legal requests land (portal, Slack app, or email alias).

- Triage: policy-backed categorization, risk scoring, and routing to humans or automation.

- LLM (Large Language Model): AI that interprets text, applies policy, and drafts responses.

- RACI (Responsible, Accountable, Consulted, Informed): role clarity for approvals and visibility.

- PII (Personally Identifiable Information): sensitive data that may trigger privacy workflows.

Scope this to core, repeatable flows first—NDAs, vendor reviews, marketing claims, procurement terms, and policy questions.

A Practical Framework For AI Intake–Triage

1) Centralize The Front Door

- Stand up a uniform form (or Slack app) with required fields by request type.

- Auto-acknowledge receipt in under 5 minutes with next steps and SLA.

- Map email aliases to the same queue so nothing bypasses the system.

2) Encode Policy As Prompts And Rules

- Translate playbooks into machine-usable checklists and guardrails.

- Example: “If NDA is mutual and uses approved template, route to auto-approval; if unilateral to our form, auto-approve with watermark; else escalate.”

- Maintain versioning so the AI always cites the current position.

3) Classify, Score, And Route With AI Agents

- Use an AI classifier to tag request type, urgency, data sensitivity, and business unit.

- Apply risk scoring to determine workflow: auto-resolve, paralegal, or attorney escalations.

- Surface the right artifacts automatically—template, clause fallback, or policy citation.

4) Automate Low-Risk Actions

- Generate first-pass responses, redlines, or approvals using your templates.

- For FAQs, let the agent draft answers with citations to policy or prior approvals.

- Gate anything material with human-in-the-loop review until trust thresholds are met.

5) Instrument For Learning

- Track KPIs: acknowledgement time, cycle time by tier, auto-resolve rate, rework rate, and requester CSAT.

- Feed outcomes back into the model: closed-loop tuning with examples of good vs. bad routing.

- Publish dashboards to Sales, Finance, and Security to align expectations.

On Sandstone, these steps live as layered workflows: intake schemas, AI routing policies, and knowledge objects that update once and propagate everywhere.

Common Pitfalls And How To Avoid Them

- Policy in prose only: if your guidance lives in PDFs, AI can’t act. Convert to structured rules and examples.

- One big queue: without tiering, attorneys become dispatchers. Route by risk—don’t triage by hand.

- Shadow channels: Slack DMs and private email threads create blind spots. Funnel every request to the front door with friendly, automated nudges.

- No RACI: unclear approvals stall decisions. Publish who is Responsible/Accountable and automate FYIs for Consulted/Informed.

- Metrics without meaning: report by business outcome—time-to-sign for sales deals, time-to-launch for marketing claims—not just ticket counts.

Tools, Checklists, And Templates

- Intake schema checklist: request type, business unit, contract counterparty, data sensitivity (PII?), revenue impact, deadline, required artifacts.

- Risk tiers and SLAs: Tier 0 (auto-resolve, <1 day), Tier 1 (paralegal, 2 days), Tier 2 (attorney, 3–5 days), Tier 3 (counsel + exec, bespoke).

- Prompt library: redline guardrails, escalation criteria, fallback clauses, privacy triggers.

- KPI dashboard: acknowledgement time, cycle time by tier, auto-approval %, rework %, requester CSAT.

Actionable next step: run a 30-day intake audit. Route all new requests through a single form, tag outcomes, and baseline your KPIs. Then pilot AI auto-resolve for one workflow (e.g., NDAs) with human review.

Mini Case: From Slack Chaos To Scalable Flow

A 1,200-employee SaaS company funneled all legal asks through a Slack app linked to an intake form. An AI agent classified requests, attached the right templates, and routed by risk. NDAs with approved templates moved to same-day turnaround; routine policy questions were answered with citations to the handbook; vendor reviews with PII flagged privacy early, pulling Security into the thread.

Within one quarter, the team met a 1-hour acknowledgement SLA, introduced transparent triage statuses for Sales, and shifted attorney time to Tier 2–3 matters. The backlog shrank—and so did escalations.

The Bedrock Of Trust And Growth

When intake becomes a living, AI-powered operating layer, legal shifts from reactive gatekeeper to proactive force. Every request teaches the system; every decision strengthens the foundation. That’s the promise of Sandstone—strength through layers, crafted precision, and natural integration that meets teams where they work.

Get the template and start with one workflow. Build your engine, then let knowledge compound.