Crosby closed a $20 million Series A in October 2025 led by Index Ventures, with participation from Bain Capital Ventures, Sequoia Capital, Elad Gil, Patrick Collison, and Cooley LLP.

The Series A followed a $5.8 million seed round announced in June 2025, which was led by Sequoia Capital with participation from other investors. The seed funding supported the company's initial launch and early customer acquisition efforts.

In total, Crosby has raised $25.8 million across these two funding rounds.

Crosby operates as an AI-powered law firm that delivers contract reviews through a Slack-native interface. Teams can message Crosby directly in Slack with an attached contract like an NDA, MSA, or other sales agreement, and receive professional legal advice typically within an hour.

Behind the scenes, Crosby's AI agents parse the document and compare every clause against a library of market-standard terms to draft redlines and clarifying questions. A licensed attorney then reviews the AI output, makes adjustments for edge cases, and signs off before any response is delivered.

This lawyer-in-the-loop structure is mandatory for every document, enabling Crosby to provide actual legal advice rather than software suggestions. The system maintains knowledge agents that remember each customer's preferences and fallback positions, automatically injecting these into future negotiations without requiring repeated instructions.

The platform also surfaces benchmarked market data from hundreds of deals, allowing business users to see where their negotiating position sits relative to industry norms. Crosby integrates with Slack, email, and CRM webhooks, with plans for a broader API that functions as the infrastructure layer for human agreements.

Crosby operates as a dual-entity structure with Crosby Legal Inc. building the software platform and Crosby Legal PLLC delivering licensed legal services. This hybrid model allows the company to provide bar-authenticated legal advice while maintaining the agility to ship software updates quickly.

The company monetizes through a per-document pricing model rather than traditional billable hours or SaaS subscriptions. Each contract review is priced as a fixed fee, typically around $400, which provides predictable costs for customers while capturing value from AI-driven efficiency gains.

Crosby's go-to-market approach targets high-growth companies that need to move routine sales contracts quickly. The Slack-native user experience means GTM and RevOps teams treat Crosby like another teammate rather than logging into a separate contract lifecycle management portal.

The business model scales through volume rather than seat expansion, with growth driven by customers processing more contracts as their businesses grow. The combination of AI automation with human oversight allows Crosby to maintain quality while achieving faster turnaround times than traditional law firms, typically delivering reviews in under four hours with many completed in minutes.

Robin AI represents the closest competitive model, operating with a UK/US dual-regulatory structure and offering a Word add-in copilot backed by a 2 million contract corpus with lawyers-in-the-loop oversight. The company has raised $43 million through Series B funding and focuses primarily on private equity and M&A transactions.

LawGeex operates an Israel/US hybrid model combining a patented review engine with staffed attorneys, marketing 94% accuracy and 80% time savings. Both competitors monetize through document-based or outcome-based pricing rather than traditional SaaS seat models.

EvenUp demonstrates the potential scale of fully-licensed AI firms in the litigation space, achieving billion-dollar valuations and proving investor appetite for regulated hybrid models that can provide formal legal advice.

Ironclad has rolled out AI Assist and Playbooks that provide one-click redlining against pre-approved clause libraries, leveraging its existing CLM footprint of over 1 billion contracts under management. Users still require in-house counsel sign-off, so Ironclad stops short of providing legal advice but bundles AI capabilities into existing CLM pricing.

Microsoft 365 Copilot offers contract review scenario templates that let procurement and finance teams self-summarize or compare drafts directly in Word and Outlook at zero incremental cost for existing enterprise subscribers. This commoditizes basic summarization and redline tasks that hybrid law firms currently charge for.

Harvey has achieved $50 million ARR with 400% year-over-year growth by leveraging large language models to disrupt traditional legal research dominated by Westlaw and LexisNexis. The platform targets both BigLaw firms and corporate in-house counsel across multiple AI-powered legal service areas.

Luminance reached $30 million ARR with 150% year-over-year growth through fully autonomous AI-to-AI deal-making capabilities and fast-deploying platform integration with Microsoft Word, handling end-to-end contract processes for both law firms and in-house teams globally.

Crosby's agentic AI already learns which redlines are least likely to create bottlenecks, positioning the company to extend into negotiation automation that could simulate alternate clauses and automate back-and-forth markups. This would move the firm upstream from review into active deal-making, tapping the $2.7-3 billion CLM negotiation segment forecast to triple by 2034.

Adding post-signature CLM capabilities like obligation tracking, renewal reminders, and benchmark analytics would capture value in execution-to-renewal phases where 55% of legal departments use CLM tools but still rely on manual follow-ups.

Vertical-specific templates for HIPAA-ready BAAs, ISDAs for fintech, and multilingual EU DPAs would enable monetization of higher-margin regulated niches underserved by generic CLM vendors.

Nearly 44% of corporate legal departments now deploy generative AI and face pressure to prove ROI, creating opportunities to position Crosby as a fixed-fee, SLA-backed alternative to hourly outside counsel beyond the current sales operations buyer persona.

BigLaw and regional firms adopting platforms like Harvey are seeking proven AI workflows with human oversight. White-labeling Crosby's review agents could transform potential competitors into distribution partners, expanding reach through established legal service channels.

The mid-market and enterprise general counsel segment represents significant expansion potential as these buyers seek to demonstrate measurable returns on AI investments while maintaining quality standards through human oversight.

The EU and UK markets favor hybrid models that maintain lawyers in the loop due to tight GDPR enforcement and the draft EU AI Act. Localizing models for German, French, and Spanish contracts would unlock a region representing approximately 30% of global CLM spend.

Early adopter firms in APAC like Clayton Utz are rolling out firm-wide generative AI, demonstrating appetite for contract-centric AI services in Australia and Singapore. This creates opportunities for expansion into English-speaking markets with established legal frameworks.

Native integrations with Salesforce, HubSpot, and DocuSign would embed Crosby deeper into existing business workflows, reducing friction for international expansion while leveraging familiar enterprise software ecosystems.

Model commoditization: As large language models become increasingly commoditized and accessible, Crosby's core AI capabilities may lose their competitive differentiation. The company's value proposition relies heavily on AI-driven efficiency gains, and if competitors can access similar AI capabilities at lower costs, Crosby may face pressure on both pricing and market position.

Regulatory constraints: Operating as a licensed law firm subjects Crosby to complex regulatory requirements across multiple jurisdictions, potentially limiting expansion speed and operational flexibility. Changes in legal practice regulations or professional liability requirements could significantly impact the company's hybrid business model and cost structure.

Human oversight bottleneck: While the lawyer-in-the-loop model provides quality assurance and enables legal advice delivery, it also creates potential scaling constraints. As contract volume grows, Crosby must hire and manage licensed attorneys across jurisdictions, which could limit the margin benefits of AI automation and create operational complexity that pure software competitors avoid.