Want Faster Contract Cycles Without Chaos? Build an AI‑Ready Intake Layer

Knowledge workers spend roughly 20% of their time searching for information. In legal, that time compounds: across mid‑market teams we see 40–60% of contract cycle time lost to context gathering, triage, and approval back‑and‑forth. The fix isn’t a bigger CLM. It’s an AI‑ready intake layer the business will actually use.

When intake captures the right data, applies your playbook in real time, and routes work automatically, legal stops being a queue and becomes an operating system. That’s where modern platforms like Sandstone shine: layered data, modular workflows, and AI agents that turn institutional knowledge into action.

The Real Bottleneck Isn’t CLM—It’s Intake Debt

Legacy, monolithic CLMs promise end‑to‑end control but struggle with adoption. The business bypasses clunky portals and emails legal “real quick,” because it’s faster—until it isn’t. Intake becomes a black box, and legal becomes the bottleneck.

Modern, modular (CLM‑Lite) approaches flip the script:

- Start where friction lives: intake, triage, and approvals.

- Capture context once, in the language the business already uses.

- Apply your positions automatically, not as PDFs buried in a wiki.

- Route to the right path: self‑serve, automated, or expert review.

If you fix intake, downstream tools—from templates to redlining—snap into place. If you don’t, you’re scaling chaos. An AI‑ready intake layer reduces work in progress, clarifies ownership, and creates the data foundation every other legal workflow needs.

What an AI‑Ready Intake Layer Looks Like

Think of intake as your living playbook, not just a form. The essentials:

- Dynamic forms that adapt to matter type and risk signals (e.g., SLA, data sharing, non‑standard terms).

- Embedded playbook logic: fallback positions, approval thresholds, and alternative clauses applied automatically.

- Smart triage rules: route NDAs to self‑serve, DPAs to privacy, MSAs over $250k to commercial counsel.

- An approver graph: who signs off when risk toggles from low → elevated.

- A structured data layer: parties, values, jurisdictions, and risk flags captured up front—so AI agents can act reliably.

- Natural integration: requests from Slack, email, or CRM flow into the same queue with context preserved.

On Sandstone, this looks like an AI agent that reads the intake, consults your playbook, drafts the first pass, and requests approvals automatically. Every click enriches your knowledge layer, so guidance improves over time.

A 30‑Day Implementation Playbook

You don’t need a year‑long program to see impact.

- Week 1: Pick one high‑volume flow (e.g., NDAs, inbound vendor reviews, low‑risk MSAs). Document the minimal questions to classify risk, pick a template, and route.

- Week 2: Encode your playbook. For each rule, define: trigger (signal), position (preferred clause), and fallback. Create approval thresholds tied to risk and deal value.

- Week 3: Launch intake in the business’ natural channels (Slack app, shared email, CRM button). Turn on AI drafting for the happy path (e.g., standard NDA) and enable self‑serve download with auto‑logging.

- Week 4: Instrument KPIs, review edge cases, and expand to one adjacent flow (e.g., vendor DPAs or order forms under $50k).

Pro tip: Start with additive automation—drafts, checklists, and routing—before auto‑approve. Adoption grows when the business sees faster answers without losing control.

Metrics That Prove It’s Working

Measure the shift from reactive to proactive with simple, outcome‑focused KPIs:

- Time to Triage: request → first response. Target under 4 business hours.

- Auto‑Routing Rate: percent of requests routed without attorney involvement.

- Auto‑Approve/Auto‑Draft Rate: percent handled end‑to‑end by rules/AI.

- Cycle Time by Matter Type: NDA, MSA, DPA—show reductions by lane.

- Rework Rate: matters bounced back for missing info drops as intake improves.

- Stakeholder CSAT: quick 1–5 score at close; aim for 4+ and trend up.

With a robust data layer, you can segment by sales region, deal size, or requester to find bottlenecks and tune the playbook—something legacy workflows rarely expose cleanly.

One Actionable Next Step: Map Your “Happy Path” in 45 Minutes

Grab your sales ops and one senior counsel. Whiteboard the fastest standard deal you’re willing to let fly:

- Inputs: which 6–8 questions prove it’s low risk?

- Positions: which standard clauses map to those answers?

- Approvals: who signs off if a single answer flips risk to “elevated”?

- Output: what artifact should auto‑generate (doc, comment set, request to vendor)?

Turn this map into a dynamic intake in your current tool—or pilot it in Sandstone. Our AI agents use the map to draft, apply positions, and request approvals. You’ll see impact within two sprints.

Why This Becomes the Bedrock

Legal is strongest when knowledge compounds. An AI‑ready intake layer captures decisions as data, not folklore. Each request makes your playbook sharper, your routing smarter, and your approvals faster. That’s how legal scales without adding headcount—and how the business experiences legal as a force for speed, alignment, and trust.

Sandstone was built for this moment: strength through layers, crafted precision, and natural integration into how your teams already work. Start with intake. Let AI do the busywork. And turn legal from reactive support into the operating system the business relies on to grow with clarity and confidence.