Unlocking Legal Throughput: Why AI-Powered Intake Changes Everything

Roughly 65% of in-house legal work still arrives as unstructured requests—email threads, Slack pings, hallway asks. That noise hides priorities, drains capacity, and slows the business. The fix isn’t more forms; it’s smarter intake: centralized, AI-powered, and wired into your playbooks so every request strengthens your legal foundation.

The Visibility Gap That Drags Cycle Time

When requests live in inboxes, legal can’t see the full picture: what’s urgent, what’s blocked, or where the same question was answered last quarter. Work skews toward whoever shouts loudest. SLAs (service-level agreements) slip because triage happens ad hoc, and knowledge walks out the door when people change roles.

The result is predictable: reactive support, fragmented decisions, and escalating risk as teams reinvent answers to the same issues. For mid-sized and enterprise organizations, that visibility gap is more than a workflow nuisance—it’s a trust problem. Business leaders can’t plan when legal work is opaque.

Why AI-Powered Intake Changes Everything

Centralized intake is necessary but not sufficient. The breakthrough comes when an AI agent sits at the front door and turns unstructured requests into structured work tied to your positions and processes. The agent:

- Classifies requests by type (NDA, vendor review, marketing claim, product counsel) and urgency.

- Extracts key entities (counterparty, effective dates, data types) from attachments and links.

- Maps the request to your playbook positions and precedents, surfacing the right clause, fallback, or policy.

- Routes to the right owner or queue and creates linked tickets in systems like Jira, Salesforce, or procurement tools.

- Drafts first-pass responses—status, required inputs, or redlines—so counsel focuses on judgment, not admin.

This is the core idea behind Sandstone as a knowledge layer: layered data, modular workflows, and decisions that build on each other. Intake is not just a form; it’s the entry point where every triage decision compounds into institutional knowledge.

Practical Impacts You Can Measure

Teams that move from inbox-driven triage to AI-powered intake typically report three shifts within a quarter:

- Faster cycle times: Standard agreements (e.g., NDAs) move from days to hours when an agent pre-classifies, validates required fields, and applies approved positions.

- Higher accuracy and consistency: The same playbook drives every decision, with transparent fallbacks when risk changes. No more divergent answers to the same question.

- Clearer workload visibility: Real-time dashboards show volume by request type, owners, blockers, and SLA compliance. Capacity conversations are grounded in data, not anecdotes.

Common workflows that benefit first:

- NDAs and DPAs: Auto-classify, extract parties and jurisdiction, generate approved templates, and apply standard redlines.

- Vendor reviews: Ingest security questionnaires, flag sensitive data types, trigger the right privacy and procurement steps, and track approvals end to end.

- Product counsel: Parse feature requests, map to known risk positions, and surface past decisions so guidance stays aligned across launches.

When intake is connected to your playbooks, every resolution enriches the system. Next time, similar requests start at 80% complete instead of 0%.

A 14-Day Starter Plan You Can Actually Run

You don’t need a reorg to see value. Pick one high-volume workflow and pilot AI intake:

1. Choose the lane: NDAs or vendor reviews offer fast wins with clear rules.

2. Codify the playbook: Document approved positions, fallbacks, and escalation criteria in plain language. Define “must have” fields.

3. Set up intake: Route all requests through a single front door (form or Slack-to-intake connection). Keep it simple.

4. Deploy an AI agent: Configure classification, entity extraction, and routing. Connect to your document repository and ticketing tools.

5. Measure what matters: Track volume, time-to-first-response, time-to-resolution, and SLA adherence. Set baselines from last quarter.

6. Iterate weekly: Review exceptions, tune playbook rules, and expand to a second workflow once you hit a stable cadence.

On Sandstone, this looks like a living operating system: the agent triages, applies your positions, proposes next steps, and logs every decision so knowledge compounds instead of disappearing.

One Action You Can Take This Week

Stand up a single intake “front door” and route all NDA requests through it for seven days. Use an AI agent to classify and require three fields (counterparty, governing law, effective date), then apply your standard NDA playbook before anything hits counsel. Measure the delta in time-to-first-response.

The Bedrock of Trust and Growth

Legal becomes a growth engine when work is visible, predictable, and fast. AI-powered intake doesn’t replace judgment—it protects it, by removing the friction that keeps counsel in their inbox and out of the business. With Sandstone as your modern legal ops platform and knowledge layer, every intake, triage, and decision strengthens your legal foundation. That’s how you scale lean teams, uphold SLAs, and earn the trust that lets the company move with clarity and confidence.