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5 Plays to Turn Legal Intake Into a Growth Engine With AI Agents

Intake is where legal scale breaks. Use these five plays to transform messy requests into structured, self-service decisions—so your team moves faster with less risk and clear ROI.

Jarryd Strydom

September 23, 2025
What if you could cut response time on routine legal requests by 50% without adding headcount? For most in-house teams, intake and triage are the hidden tax on speed—endless emails, Slack pings, and missing context that drag cycle times and bury experts in repetitive work.
The fix isn’t a bigger form. It’s turning your knowledge into an operating system and your intake into decisions that compound. Here are five plays to make that real with AI agents on a platform like Sandstone.
  1. Map the Work, Not Just the Form
Before you automate, align on the work you actually do. Inventory your top request types (e.g., NDAs, vendor onboarding, marketing review, privacy questions). For each:
  • Define the outcome you want (approve, generate, escalate, decline, collect more info).
  • Sketch the decision tree: thresholds, required data, red flags, and “happy path” versus exceptions.
  • Clarify SLAs and who owns what (legal vs. business vs. cross-functional teams).
Treat intake as decision capture. A form that asks the right questions upfront—and routes based on answers—cuts rework. AI agents amplify this by following your decision tree, asking only what’s needed, and escalating when signals exceed your risk appetite.
  1. Codify Positions Into Reusable Blocks
AI is only as good as your policy. Move beyond static playbooks to structured positions—plain-language rules and pre-approved language the agent can apply:
  • Safe defaults: When to use standard templates, permitted edits, and non-negotiables.
  • Tiered risk: What changes at low, medium, and high risk (e.g., data categories, deal size, region).
  • Exception paths: Who approves deviations and what evidence is required.
In Sandstone, these positions are layered and versioned, so when a policy changes, every workflow instantly benefits. The agent cites the exact position it used, producing audit trails that build trust—and make compliance reviews boring (in the best way).
  1. Design the Agent Around Outcomes, With Guardrails
Design AI around outcomes, not documents. For each request type, define what the agent can do autonomously and when it must hand off:
  • Fully automated: Generate an NDA, route for e-sign, file to the repository, and notify the requester—no human needed.
  • Co-pilot: The agent drafts a data protection addendum, explains clause choices with citations to your positions, and requests approval for non-standard terms.
  • Escalation: If deal value, data sensitivity, or counterparty edits exceed thresholds, the agent packages context and sends it to the right lawyer with a crisp summary.
Guardrails matter. Require source citation from your knowledge base, constrain drafting to approved templates, and log each decision. With Sandstone’s knowledge layer, retrieval is precise and layered—your positions, templates, and prior decisions inform the next one.
  1. Meet the Business Where It Works
Adoption lives or dies on convenience. Bring intake to Slack/Teams, Salesforce, Jira, or your intranet—where work already happens.
  • Smart forms: Short, conditional questions based on request type and risk.
  • Identity and context: Pull requester role, account owner, region, and deal metadata automatically.
  • Auto-assemble packets: The agent gathers links to contracts, vendor profiles, security docs, and prior positions, so no one chases context.
Natural integration is a feature, not an afterthought. Sandstone slots into your existing stack, so the business doesn’t learn a new tool and legal doesn’t play traffic cop.
  1. Instrument, Iterate, and Prove ROI
You don’t need perfect. You need a fast loop. Baseline metrics, launch a narrow pilot, and expand with evidence.
  • Track: Time to first response, cycle time, first-contact resolution, deflection rate (no human touch), escalation ratio, requester satisfaction.
  • Prove value: Convert hours saved into dollars, quantify faster revenue recognition for sales contracts, and show risk reduction via fewer exceptions and tighter adherence to policy.
  • Expand: After NDAs, add vendor onboarding, marketing review, low-risk DPAs, and policy Q&A.
When every request is structured and every decision is logged, knowledge compounds. The result: fewer bottlenecks, cleaner audits, faster deals.

A Quick Pilot You Can Run Next Week

Pick NDAs. In two weeks, you can show real impact.
  1. Document your positions (signing authority, term, jurisdiction, mutual vs. one-way, redlines you’ll accept).
  2. Configure the agent to generate, route for e-sign, and file to your repository, with Slack notifications.
  3. Set guardrails: Auto-approve under thresholds; escalate on counterparty edits to confidentiality, IP, or governing law.
  4. Measure: Target >70% deflection (no human touch) and a <1-hour time to first response.
Why This Works—and Why Sandstone
Intake isn’t a form problem. It’s a knowledge problem. Sandstone is the modern legal ops platform and knowledge layer that turns playbooks, positions, and workflows into a living, AI-powered operating system. Every intake, triage, and decision strengthens your foundation—so knowledge doesn’t disappear; it compounds.
Built like its namesake, Sandstone delivers:
  • Strength through layers: Layered data, modular workflows, decisions that build on each other.
  • Crafted precision: Tools carved to your process contours, not generic bots.
  • Natural integration: A system that blends into how legal and the business already work.
The payoff is bigger than speed. When legal moves with clarity and consistency, trust grows. Deals close faster, risk is intentional, and the business stops treating legal as a queue—and starts seeing it as connective tissue for growth.

About Jarryd Strydom

Jarryd Strydom is a contributor to the Sandstone blog.