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

On many in-house teams, 30–50% of matter cycle time disappears into intake and triage—collecting context, routing work, and chasing attachments. That hidden tax drains focus from higher-value counsel and slows the business. The faster path: AI-driven intake that classifies requests, fills gaps, and routes with confidence, turning legal from a bottleneck into connective tissue.

The Hidden Tax of Manual Intake

Manual intake looks deceptively simple: a form, an email alias, a Slack ping. But each request triggers follow-ups, context hunting, and ad hoc handoffs that create delays and audit gaps. Inconsistent triage means variable risk and frustrated stakeholders.

When intake is standardized and automated, you shorten time-to-first-touch, raise completeness, and enforce the right playbook every time. That’s the foundation for scale—especially for lean teams balancing volume with complexity.

What AI Triage Actually Does

AI triage is not a chatbot bolted onto your inbox. Done right, it’s an agent that:

- Classifies requests by matter type (NDA, DPA, marketing promo, vendor onboarding, employment, litigation hold).

- Detects missing context and asks targeted follow-up questions automatically.

- Applies policy positions and playbooks (approved terms, fallback positions, escalation rules).

- Routes to the right owner based on expertise, geography, risk, or workload.

- Creates and updates system records (ticketing, CRM, matter management) with a clean audit trail.

On Sandstone, these agents sit on your knowledge layer—playbooks, positions, and workflows—so every intake, triage, and decision compounds into better guidance next time.

How To Get It Right: A 5-Step Playbook

1) Map demand and define “complete.”

- Identify your top 8–10 request types and their required fields (e.g., counterparty, governing law, data flows, deal value, timeline).

- Build a routing matrix: when to self-serve, when to route to legal, when to escalate.

2) Author your playbooks and positions.

- Capture approved terms, redlines, and fallbacks for each request type.

- Define risk thresholds, exceptions, and sign-off paths. Keep it plain-English and decision-oriented.

3) Train the AI agent with guardrails.

- Connect to your knowledge layer (policies, templates, prior matters) and restrict sources.

- Set confidence thresholds, mandatory human review points, and escalation triggers.

4) Integrate where work happens.

- Intake through Slack/Teams, email, or web forms; sync with Jira/ServiceNow, Salesforce, and your matter system.

- Enforce SSO and permissions; ensure documents live in your approved DMS/CLM.

5) Iterate weekly on signal and outcomes.

- Review escalations and low-confidence cases; refine prompts, fields, and playbooks.

- Add automation gradually (e.g., auto-approve low-risk NDAs before tackling DPAs).

Example: A sales rep submits a partner NDA via Slack. The agent extracts counterparty, entity, and term; checks template fit; fills missing fields; and auto-approves within SLA. If the request references data processing or non-standard jurisdiction, it routes to privacy counsel with a pre-filled brief, saving cycles and reducing risk.

Metrics That Matter (and How To Report Them)

Track these KPIs to prove impact:

- Time to first response: target <1 hour for business-facing channels.

- Intake completeness rate: >90% of requests arrive “decision-ready.”

- Auto-classification accuracy: 95%+ on top request types.

- Auto-routing rate: 60–80% without manual intervention.

- Cycle time by matter type: 30–50% reduction in median.

- Deflection to self-serve: % resolved via templates/guides without attorney touch.

Report improvements by business unit and matter type to spotlight where automation unlocks revenue and reduces friction.

Common Pitfalls (and How To Avoid Them)

- Over-customizing forms → Standardize a core set of fields; let the agent ask follow-ups contextually.

- AI with no guardrails → Define sources, confidence thresholds, and human checkpoints.

- Ignoring change management → Launch with 2–3 high-volume workflows; train requesters in Slack/Teams.

- No audit trail → Create matter records automatically with decisions, versions, and owners.

- Siloed tools → Integrate email, chat, CRM, ticketing, and DMS so data flows without copy/paste.

One Practical Next Step

Pick three workflows—NDA, vendor onboarding, and marketing review. For each, define required fields, a simple routing matrix, and SLAs. Stand up an AI triage pilot in Slack/Teams with guardrails and success thresholds (e.g., 70% auto-routing, 40% faster time-to-first-touch in 30 days). In Sandstone, this takes about a week when your playbooks and integrations are in place.

Build the Bedrock for Speed and Trust

Intake is where knowledge either compounds or evaporates. With AI triage anchored to your playbooks and positions, legal becomes the connective tissue—moving with the business, not behind it. Sandstone turns those layers into a living operating system so every request strengthens your foundation, accelerates outcomes, and builds trust at scale.