How Legal Teams Automate Intake and Triage With AI
Most contracting delay happens before drafting begins. Here’s how AI agents turn legal intake into a fast, guided workflow that routes, resolves, and learns — without forcing the business to change…
Most in-house teams quietly lose more than half of contract cycle time in intake — not in redlines. Requests sit in inboxes, bounce between Slack and a portal, and arrive without context. The surprising part: a large share of these asks are repeatable and policy-driven. That’s why AI-powered intake and triage is becoming the highest‑leverage upgrade in legal ops.
The Bottleneck Is Intake, Not Review
Before anyone opens a document, legal is asked to decipher what the business needs, what template applies, whether procurement or privacy must weigh in, and who can approve deviations. In legacy ticketing or email workflows, that means manual back‑and‑forth and brittle forms. The result is slow acknowledgment, unclear SLAs, and invisible work.
Modern intake flips this. An AI agent meets requesters where they are (Slack, Microsoft Teams, email, a simple form), asks the right follow‑ups, and applies your playbooks in real time. Instead of “submit and wait,” the business gets immediate guidance: self‑serve when low‑risk, fast routing when specialized, and clear escalation when exceptions appear.
What AI Agents Do at Intake
AI intake isn’t a chatbot bolted on top of a queue. It’s a workflow layer that:
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Classifies the request (NDA vs MSA vs DPA) and identifies the counterparty, region, and deal context.
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Applies policy logic from your playbooks to recommend a path: self‑service, assisted, or attorney review.
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Generates and issues approved documents for low‑risk scenarios using current templates.
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Risk‑scores nonstandard asks (e.g., indemnity caps, data transfer issues) and triggers the right approvers.
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Orchestrates cross‑functional steps with procurement, InfoSec, and privacy without losing the thread.
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Logs structured data to your systems of record — contract lifecycle management (CLM), CRM, and ticketing — so nothing goes dark.
In Sandstone, those decisions don’t disappear after submission. Every intake strengthens the knowledge layer: positions, fallbacks, and outcomes are captured, so the next request routes faster and with more confidence.
A Workflow You Can Automate Today
Consider a vendor NDA and security questionnaire, a common drag on legal time.
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A salesperson pings a “Legal Intake” channel in Slack with the vendor’s name and use case.
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Sandstone’s agent detects it’s an NDA + security review, gathers missing details, and checks the vendor domain against an approved list.
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If the request matches policy (mutual NDA under $100k, no personal data processed), the agent issues the latest mutual NDA, sends it for e‑signature, and opens an InfoSec ticket with the right questionnaire.
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If the vendor insists on its paper or handles personal data, the agent flags privacy, assigns the right reviewer, adds a risk note (“standard DPA required”), and sets an SLA.
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All artifacts — request, decisions, template version, approver notes — sync to the CLM record and the CRM opportunity, building your audit trail automatically.
The business experiences speed and clarity. Legal preserves control and auditability without context‑switching or manual triage.
Guardrails That Make Automation Safe
Legal needs control more than novelty. Effective AI intake builds in guardrails:
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Source of truth: playbooks and positions live in a versioned knowledge layer, not in scattered docs.
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Human‑in‑the‑loop: high‑risk or out‑of‑policy asks route to attorneys with full context and a recommended next step.
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Permissions: role‑based access, SSO, data retention, and PII handling align with security standards.
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Transparency: every automated action has an audit log — who requested, what was generated, which rule fired, and why.
With these controls, automation reduces risk by enforcing consistency, rather than introducing it.
From Pilots to Program: Metrics That Matter
You don’t need to automate everything at once. Start where volume and repetition meet policy:
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Top request types: NDAs, vendor reviews, low‑value order forms, marketing permissions, simple renewals.
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Baseline metrics: mean time to acknowledgment, handoffs per matter, auto‑resolve rate, cycle time to signature.
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Targets: 1‑hour acknowledgment for all requests, 50–70% auto‑resolution for low‑risk NDAs, double‑digit reduction in total cycle time.
Pair intake with modular workflows in your CLM. Sandstone integrates naturally — it doesn’t force teams to change channels or templates. As decisions accumulate, your positions get sharper, exceptions shrink, and your data becomes a strategic asset.
Actionable Next Step
Run a 30‑day intake pilot:
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Map your top 10 request types and their entry points (email, Slack, forms).
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Convert one playbook (e.g., NDA) into explicit rules, fallbacks, and approvers.
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Configure an AI agent to greet, collect context, apply the playbook, and log outcomes to your CLM.
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Track acknowledgment time, auto‑resolve rate, and escalations. Review exceptions weekly and refine rules.
This focused sprint proves value, builds trust, and creates a reusable pattern for additional workflows.
The Bigger Picture: A Stronger Legal Foundation
When intake becomes intelligent, legal stops firefighting and starts compounding knowledge. Every triage decision, approval, and exception adds a layer to the system — stronger each week, like sandstone itself. The business moves faster with clearer guardrails. Legal scales without adding headcount. And the organization earns the thing that matters most in growth: trust.
Sandstone is the modern legal ops platform and knowledge layer that makes this possible. By turning playbooks into a living, AI‑powered operating system — with natural integration and crafted precision — intake, triage, and decisions become the foundation for speed and alignment across the company.
About Jarryd Strydom
Jarryd Strydom is a contributor to the Sandstone blog.