Operationalizing Playbooks: AI‑Driven Intake and Triage as the New “Must‑Have”


Modern legal teams don’t fail for lack of expertise—they stall for lack of operational clarity. Across the teams we advise, 60–80% of requests still land via email or chat without the context needed to act, and knowledge from past matters rarely makes the next decision faster. That’s costly friction for a function built to move with the business.

Sandstone was built for this moment: the legal ops platform and knowledge layer that turns playbooks, positions, and workflows into a living, AI‑powered operating system. When intake and triage become muscle memory, legal stops being a bottleneck and starts compounding knowledge—layer by layer.

Why Intake Is Still the Bottleneck

If you can’t see the work, you can’t improve it. Ad‑hoc requests arrive in every format, missing key facts like counterparty, risk tier, jurisdiction, or due dates. Counsel spends cycles clarifying instead of deciding. Work queues fragment across inboxes. Leaders lack visibility into demand, throughput, and risk.

The result is a double tax: slower cycle times for the business and a growing shadow backlog for legal. Worse, decisions live in people’s heads or scattered documents, so the same issues get re‑adjudicated. Without an operating layer, knowledge evaporates instead of compounding.

The Legal Front Door, Upgraded

A modern front door is more than a form. It’s a guided experience that:

- Collects the right data up front with dynamic questions.

- Triages requests by risk and complexity.

- Routes work to the right lane: self‑service, playbook automation, or expert review.

- Captures the decision in a structured way so the next similar request is faster.

With Sandstone, AI agents sit behind the front door as co‑pilots, not gatekeepers. They read context from email, Slack, or a portal; enrich missing metadata; match the request to the right playbook; propose a recommended path; and document the outcome—so intake becomes action, not admin.

The Framework: Intake → Triage → Routing → Measurement

Operationalize in four layers:

1) Intake

- Standardize request types (e.g., NDA, vendor onboarding, marketing review, DPAs).

- Use smart forms or Slack shortcuts to capture mandatory fields: counterparty, template, governing law, PII/PCI flags, dates.

- Ingest email threads; let an AI agent extract entities, dates, and attachments.

2) Triage

- Apply risk rules from your playbooks (e.g., non‑mutual NDA with logo clause → medium risk).

- Auto‑assign SLAs by tier; set approval matrices based on spend, data, or geography.

- Flag edge cases for counsel with a pre‑read summarizing issues and precedent.

3) Routing

- Self‑service: Offer approved templates and policy snippets when risk is low.

- Automation: Let an AI agent propose redlines aligned to your positions, with guardrails and human‑in‑the‑loop.

- Expert review: Route to the right lawyer or specialist with full context, not a blank page.

4) Measurement

- Track cycle time by request type and risk tier.

- Monitor auto‑resolution rate, SLA adherence, rework/rollback, and data completeness.

- Convert decisions into reusable positions; update playbooks continuously.

On Sandstone, each pass through the loop strengthens the knowledge layer. Your “institutional memory” isn’t a wiki; it’s the operating fabric where decisions live and improve the next one.

Implementing in 30–60 Days: A Practical Plan

- Map the top three workflows by volume (most teams start with NDAs, vendor onboarding, and marketing claims).

- Codify playbooks: Accept/fallback positions, escalation rules, and risk flags. Keep them modular.

- Configure the front door: Smart forms, Slack shortcut, email capture; enable SSO and requester profiles.

- Connect systems: CLM for templates, procurement for vendor data, privacy registers for data categories.

- Define triage thresholds: What’s truly self‑service? Where do you want AI to propose vs. finalize?

- Pilot with one business unit; publish SLAs and a simple request guide.

- Instrument dashboards from day one; review weekly and tune playbooks.

An AI agent example: For NDAs, it classifies mutual vs. one‑way, detects governing law and venue, proposes redlines to non‑negotiables (assignment, publicity, injunctive relief), and auto‑routes signature when within policy. Counsel only sees exceptions.

The Impact: Speed, Visibility, and Trust

Teams that operationalize intake and triage see consistent gains:

- Faster cycle time: Low‑risk matters close in hours, not days.

- Higher auto‑resolution: A growing share of work never hits a lawyer’s queue.

- Cleaner data: Every request carries the metadata you need to report and improve.

- Better alignment: Business partners know where to go, what to expect, and when to escalate.

Just as important, each decision compounds into your knowledge layer. Playbooks stay current because they’re used in the flow of work. Leaders get a clear picture of demand and risk. Trust grows when legal moves at the speed of the business—with guardrails.

Actionable Next Step

Pick one high‑volume workflow and run a two‑week “front‑door sprint.” Define the minimum required fields, set triage thresholds, and route low‑risk items to self‑service or AI‑assisted automation. Measure baseline cycle time and auto‑resolution; review weekly and iterate.

Key Takeaways

- Intake isn’t a form problem; it’s an operating system opportunity.

- AI agents excel at enrichment, triage, and first‑draft redlines—within your guardrails.

- Measurement closes the loop: What gets tracked gets faster and safer.

- Start small, ship quickly, and let knowledge compound.

Sandstone was crafted for this work: strength through layers, precision fit to your processes, and natural integration with how your team already operates. When your front door is powered by a living knowledge layer, legal becomes the bedrock of speed, alignment, and trust. Ready to operationalize intake and triage? Learn how to build your front door on Sandstone.