Crosby

Crosby presents itself as an agentic law firm for commercial contracts: clients buy completed legal work delivered by attorneys using AI, rather than adopting another review interface.

Verified capabilities and evidence

The current homepage calls Crosby the AI Law Firm for Commercial Contracts and explicitly says buyers receive 100% completed work with no new features to learn. It profiles attorneys with experience in master service agreements, data-processing agreements, data-rights terms, SaaS, vendor and licensing deals, financing, M&A, and private funds. Vendor case studies claim one customer accelerated time to revenue and another received in 12 hours work that had taken a traditional firm six weeks. Those are first-party testimonials, not guaranteed turnaround times or independent comparative studies.

Workflow and differentiation

Crosby’s distinction is service delivery, not merely issue spotting in software. A business sends a commercial legal matter; Crosby combines technology with attorney execution and returns completed work. That may reduce change management because sales and operations teams do not need to learn another contract lifecycle interface. It changes due diligence: buyers should evaluate jurisdictional coverage, attorney responsibility, conflicts checks, engagement terms, professional liability, escalation, turnaround commitments, and work-product ownership—not only model accuracy. Legal judgment and business approval remain human responsibilities.

Pricing and total cost

No public fee schedule, per-contract price, subscription, minimum commitment, or overage policy appeared on the fetched homepage or pricing route. The only defensible label is custom or contact-based pricing. Ask for a dated proposal separating routine review, redlining, negotiation, bespoke drafting, specialist escalation, urgent turnaround, and out-of-scope work. Compare effective cost per completed matter and closed deal against outside counsel and internal review while controlling for complexity. Any unsourced monthly figure would be fabrication. Also clarify whether unused capacity expires and whether a pilot requires a longer engagement.

Pros, cons, and evidence gaps

The model can help a fast-growing company that needs outcomes but lacks enough in-house commercial counsel. Named lawyers and described experience make the human layer more visible than in a pure AI reviewer. Completed work could remove the burden of interpreting a machine checklist. The tradeoff is less self-service control: quality, speed, institutional learning, and cost depend on Crosby’s service team. Public material does not establish supported jurisdictions, service-level guarantees, integrations, audit exports, retention, or privilege procedures. Those points need written answers before sensitive contracts are uploaded.

Practical evaluation plan

Start with 15 agreements: five routine forms, five MSAs or DPAs, and five documents with unusual liability, IP, privacy, or data-rights language. Score issue recall against trusted counsel, redline acceptance, business-context accuracy, turnaround, internal handoffs, and total cost. Require attorney identification and an escalation route. Compare AI for sales teams guide for practice operations and Salesforce for revenue workflow. Use the AI security guide and AI governance guide when assessing confidential and privileged data.