AI Intake and Triage for Legal Ops: How to Scale Support Without Added Headcount


AI Intake and Triage for Legal Ops: How to Scale Support Without Added Headcount

Legal Ops teams report that up to 40% of in-house legal time disappears into intake, triage, and chasing context. That’s work you can standardize, automate, and measure. AI‑driven intake turns scattered asks into structured data, routes them with precision, and accelerates decisions—all while improving visibility, ownership, and impact.

Sandstone’s view: when intake becomes a living, AI-powered operating system, every request strengthens your legal foundation. Knowledge compounds instead of disappearing.

What It Is

AI intake and triage use natural language processing and playbook logic to convert unstructured requests (email, Slack, portals) into structured matters with next-best actions.

- Intake: capture the ask, gather required details, extract entities (counterparty, value, risk flags), and normalize request types.

- Triage: classify, prioritize, and route based on business rules, SLAs, and capacity. Suggest templates or positions.

- Fulfillment: kick off the right workflow—self‑serve guidance, quick answer, or full review—while tracking cycle time and outcomes.

On Sandstone, this looks like Intake → Triage → Fulfillment with AI agents that read playbooks, propose responses, and log decisions to the knowledge layer.

Why It Matters

AI intake isn’t just faster—it’s a force multiplier for Legal Ops:

- Visibility: always-on dashboards for request volume, type, and risk. No more hidden queues.

- Ownership: clear routing, SLA expectations, and audit trails. Requests don’t bounce or stall.

- Impact: faster cycle times and higher requester satisfaction. Legal becomes connective tissue, not a bottleneck.

When every request lands in a consistent flow, you reduce context switching and reclaim hours for high‑value work like policy design and vendor strategy.

How to Run It

Start with a narrow slice and scale in layers.

1) Define request types and SLAs

- Pick 3–5 high-volume categories (NDA, vendor review, marketing copy). Set intake fields and SLA targets.

2) Codify playbooks

- Turn positions into if/then rules and reusable clauses. Capture exceptions. Keep language business-friendly.

3) Map the workflow

- Intake → Triage → Fulfillment. Decide what should be auto-routed, auto-answered, or escalated.

4) Integrate channels

- Meet people where they work: Slack, email, ticketing, or a portal. Auto-acknowledge and confirm requirements.

5) Pilot with guardrails

- Roll out to one business unit. Enable human-in-the-loop approvals for high-risk paths. Collect feedback weekly.

6) Iterate and expand

- Add request types, enrich playbooks, and tighten SLAs based on data. Document changes in your knowledge layer.

Pro tip: use Sandstone’s crafted precision to fit your contours—custom forms, modular workflows, and role-based routing without heavy IT lift.

Metrics and Scoreboard

Track what proves value to the business and to Legal Ops:

- Cycle time (intake-to-first-response, intake-to-close)

- SLA adherence (% on-time responses by request type)

- Deflection rate (% resolved via self‑serve or auto‑answer)

- First‑touch resolution (% closed without escalation)

- Intake completeness (required fields captured on first submission)

- Requester satisfaction (CSAT after closure)

- Knowledge reuse (playbook citations per matter)

Callout: a 20–40% cycle-time reduction is common when moving from inbox chaos to structured, automated intake.

Tools and Examples

What enables this in practice:

- No‑code intake forms and smart templates that adapt based on answers.

- AI entity extraction and classification tied to your taxonomy.

- Policy- and playbook-aware suggestion engine to propose positions and drafts.

- Natural integrations: Slack commands, email ingestion, ticketing sync, CRM lookups.

- Capacity-aware routing to balance workload across the team.

Mini-scenario:

- A sales rep DMs “Need NDA for Acme.” Sandstone’s Slack app recognizes "Mutual NDA," grabs counterparty, proposes your standard, and checks for an existing record. The AI agent drafts the NDA, applies negotiation positions, and sends for e‑signature—or routes to counsel if deal value exceeds a threshold. Everything logs back to the matter, updating the knowledge layer for next time.

Pitfalls to Avoid

- Over-automation without governance: keep humans in the loop for high-risk categories.

- Vague SLAs: set clear response and close targets by request type.

- Unstructured taxonomies: define request types and naming conventions before scaling.

- Playbooks that live in PDFs: convert to modular clauses and rules the AI can act on.

- No feedback loop: survey requesters and review exceptions weekly to improve.

Actionable Next Step

Run a 14-day pilot: pick three request types, stand up one intake form per type, integrate Slack/email, and enable AI suggestions with human review. Measure cycle time, SLA adherence, and deflection. Keep what works; tune what doesn’t.

The Bedrock of Trust and Growth

When intake flows through a layered, AI-powered system, legal becomes a proactive force for speed, alignment, and trust. Sandstone delivers strength through layers, crafted precision, and natural integration—so every request, triage, and decision compounds into institutional knowledge. That’s how Legal Ops scales support without adding headcount, and how legal moves in harmony with the business.