![Abstract legal ops workflow diagram showing layered AI intake and triage]

Legal Intake to Resolution with AI Agents: What Actually Works in 2025 (And What Doesn’t)

Gartner projected corporate legal’s spend on technology would triple by 2025—and the pressure has arrived. Yet in many enterprises, legal intake is still email threads and spreadsheets masquerading as process. The opportunity this year isn’t another portal; it’s a purpose-built AI layer that turns intake into decisions with audit trails.

Sandstone’s view: legal should be connective tissue, not a bottleneck. By layering playbooks, positions, and workflows into an AI-powered operating system, intake isn’t a queue—it’s the start of resolution.

Key takeaways

- Intake → resolution: The win is deflection and cycle-time cuts, not chat for chat’s sake.

- Purpose-built beats generic: Privilege, auditability, and workflow context are non-negotiable.

- Start narrow: NDAs and triage are high-ROI, low-risk entry points.

- Govern the model: Identity-aware RAG, guardrails, and audit logs reduce hallucinations.

- Measure ruthlessly: Track deflection rate, time-to-first-response, precision@k for routing, and stakeholder CSAT.

The Shift in 2025: From Portals to AI Intake

Portals alone don’t solve legal’s throughput problem; they just collect requests. What changed in 2025 is tooling maturity: reliable redaction, enterprise-grade model governance, and smoother integrations with Slack/Teams, Salesforce, Jira, and DMS (SharePoint, Box, Drive).

- Analyst consensus has moved past “can AI draft?” to “can AI execute safely with context and controls.”

- ACC surveys consistently rank contracting volume and responsiveness as top pressures—prime ground for automation.

- Security baselines (SSO, SCIM/Okta, DLP) are now table stakes in legal AI, not premium features.

Takeaway: It’s the year to replace intake forms plus manual triage with an AI agent that knows your policies, playbooks, and who can approve what.

What Actually Works Now (Use Cases That Stick)

Focus on constrained workflows where policy is codified and success is measurable.

- AI intake and triage: Parse requests from Slack/Teams/email; extract entities; map to matter type; propose the right path (self-service, template, or assignment). Identity-aware and permissioned.

- NDA autopilot with guardrails: Classify counterparty form vs. company form; apply playbook; auto-approve low-risk NDAs; escalate edge cases with a redlined draft and rationale. Full audit trail and retention.

- Clause selection and fallback sequencing: Pull from a curated clause library; suggest preferred/alternate positions with citations to policy and past decisions.

- Knowledge Q&A with citations: Answer “What’s our standard liability cap for SaaS?” with links to playbooks and recent approved language. No free-text hallucinations; always source-backed.

- Matter routing and SLA tracking: Auto-assign based on expertise, load, and region; set timers; nudge for missing inputs; update requestors via their channel of choice.

How Sandstone fits: Its layered knowledge model (playbooks + positions + past decisions) powers identity-aware RAG and action policies, so every intake strengthens the system—knowledge compounds instead of disappearing.

What Doesn’t (And How to Avoid It)

- Generic chatbots: Without legal context, they hallucinate and ignore privilege boundaries.

- RAG without identity: Serving “the right answer” to the wrong person is a data incident waiting to happen.

- Agents without workflow hooks: If it can’t generate tasks, route approvals, or push updates to systems of record, it’s just a novelty.

- Opaque redlines: AI that edits contracts without showing the policy basis or diffs erodes trust.

- Shadow logs: No immutable audit trail means no defensibility in audits or disputes.

Guardrail mindset: If you can’t explain “why this decision, for this user, from these sources,” don’t ship it.

Selection Criteria: A 7‑Point Checklist

Evaluate legal AI through a governance lens:

1. Security and identity: SSO/SCIM, role-based access, least privilege, tenant isolation.

2. Data governance: On-prem/VPC options, data residency, configurable retention/legal hold.

3. Model governance: Prompt logging, versioning, eval harness, red-teaming, reversible rollbacks.

4. Privilege and DLP: Privileged channels, automatic redaction, PII detection, secure sharing.

5. Accuracy controls: Source citations, confidence thresholds, human-in-the-loop for high risk.

6. Workflow integrations: Slack/Teams, email, Salesforce, Jira, CLM/DMS; bidirectional sync.

7. Auditability: End-to-end audit trail of prompts, sources, actions, and approvals.

If a vendor can’t demo all seven on a live use case, keep looking.

A Practical Rollout Plan (30–60 Days)

- Weeks 0–1: Baseline and scoping. Map top intake channels, define “happy path” for NDAs, capture current SLAs and volumes.

- Weeks 2–3: Configure AI intake and NDA autopilot. Connect Slack/Teams and email; ingest playbooks; set risk thresholds and approval paths. Launch to a pilot group.

- Weeks 4–5: Expand to triage and routing. Add matter types, auto-assignment rules, and Q&A against policies with citations.

- Week 6+: Measure and harden. Track deflection rate (target 30–50% for NDAs), time-to-first-response (sub-5 minutes), precision@k for routing (>90%), and stakeholder CSAT (4.5/5+). Iterate guardrails and positions.

Pro tip: Publish a simple “What the agent can do today” page to set expectations and drive adoption.

Risks, Privilege, and Governance: Non‑Negotiables

- Define privilege strategy upfront: privileged channels, labeling, and access controls by matter type.

- Keep humans in the loop where it matters: escalations for indemnity, data transfer, or regulatory clauses.

- Log everything: immutable audit trails for prompts, sources, redlines, and approvers.

- Align with privacy/compliance: DPA in place, vendor SOC 2/ISO 27001, DPIA where needed.

This is operational risk management, not a side project. Treat it like any critical system.

One Next Step

Run a two‑week NDA autopilot pilot. Use 50 recent NDAs, your standard playbook, and Slack-based intake. Measure deflection, cycle time, and accuracy. If results are strong, scale to MSA triage next. Download the Legal AI Intake & Triage Checklist to get started.

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Sandstone is the modern legal ops platform and knowledge layer that turns intake into resolution. Strength through layers, crafted precision, natural integration. See a live demo and learn how purpose‑built AI agents can make legal the connective tissue of your business.

Disclaimer: This article is for informational purposes and is not legal advice.

Author: Sandstone Editorial Team · Estimated read time: 6 minutes

Sources: Gartner, “Market Guide for Corporate Legal Operations Technology” (prediction on tripling spend by 2025); ACC CLO Surveys (contracting volume and responsiveness as top pressures).