Big Law vs. AI-Native Law Firms vs. Lawyer-Built Legal Tech: Where Startup Legal Work Sits in 2026

In 2026, ask who supplies the legal reasoning: a partner, a model, or encoded practitioner logic. Big Law, AI-native firms and lawyer-built legal tech overlap; BigLaw builds legaltech with outside developers, AI-Native firms hire engineering talent before lawyers, and don't mention their weak credentials. At Story.law, our Aegis infrastructure embeds lawyer-built logic from lawyers with the credentials and experience of BigLaw partners built into software. We use that deep practical knowledge ot structure our legal event graph, which can power the functions performed by both BigLaw and Ai-native firms at a much lower cost because of the token efficiencies we gain through knowing both software and law inherently. We compare provider examples, work purchased, judgment, professional responsibility and pricing, then recommend options by situation. Software-supported preparation is not legal representation: custom representation requires formal engagement. This is general information, not legal advice; Story.law’s software contains embedded legal logic but does not give legal advice.

What do Big Law, AI-native law firms, and lawyer-built legal tech mean for startups in 2026?

The useful test is who supplies the legal reasoning: a partner, a model, or encoded practitioner logic-not simply whether AI is involved. These labels overlap. BigLaw describes large, established multidisciplinary firms, not software-free delivery or exclusively hourly billing. Wilson Sonsini’s Neuron supports formations, SAFE financings, board consents, equity grants, centralized records, and attorney collaboration; CooleyGO has drafted templates for years. Wilson has also documented attorney-supervised, AI-enabled commercial contracting for a fixed fee. Both systems seems designed as lead-gen for the law firm. When you get big enough that standard templates don’t work, you call the firm that made the template. This is a common move, and its a move Biglaw has been making for a decade.

For us at Story.law, those offerings show why using software and retaining an established law firm are not necessarily separate choices. BigLaw has offered tech for startups for a long time, specifically designing tech to stop at complexity.

AI-native law firms make AI the core of service delivery, but the label leaves out that this means an LLM supplies the core reasoning and judgment. The timelines promised by AI-native firms make clear that even human lawyers involved couldn’t meaningfully check all the AI work; if you can return a 40-page contract markup in an hour, you didn't read it. General Legal identifies as an AI-native transactional firm, assigns a "US-barred" attorney responsibility for every matter, and yet lists practices beyond contracting, including venture capital, employment, tax, and privacy. The question is, with nothing like a seasoned tax lawyer or employment partner on their founding team, and without the capital to compel such talent away from multi-million dollar law firm partner gigs, how could they offer anything but the same output Claude or ChatGPT would give? Without lawyer who know when Claude or ChatGPT is wrong, you're paying for a lawyer without value. You're also paying a firm that's taking a loss on your work to prove they can do it, and we think business owners deserve better than to be an AI-Native firm's AI tax advisor test cases for a business that can't earn clients on reputation.

Story LLP, the practicing firm behind Story.law, has considered the AI-Native label - we do use AI to support legal practice. But the order is reversed: a specialized lawyer with real practice experience gets privilege-protective AI that’s insanely token efficient because it doesn’t think - it only speeds and supports grunt work. We want our lawyers thinking, exercising judgment gained through decades of experience, and remaining accountable for their work. They aren't nameless contract attorneys to jump like mercenaries on any matter that someone wants to do for $150 in an hour. For Story, we think “AI-enabled” fits better. What’s native to Story are experts with human judgement doing what they do best, enabled to use AI to do more, faster. But slow enough for the human to actually do good work.

Preliminary production must be distinguished from professional responsibility: ABA Formal Opinion 512 identifies continuing lawyer duties involving competence, confidentiality, communication, supervision, candor, and reasonable fees when using generative AI. Competence and supervision in particular dont' map to the go to market approach of an AI-Native law firm.

Lawyer-built legal tech describes practitioner-designed software algorithms, and more specifically algortihms built by the lawyers themselves directly into software. NOT BigLaw paying Palantir $500M to give them an ontology; not Second-year associates hiring engineers to help build what they can only imagine legal practice is really like - and what client services matter. At Story.law, Aegis is Story LLP’s legal operations graph and tooling: lawyer-defined rules govern document-derived workflows, including cap tables and diligence preparation. Our distinction is encoded practitioner reasoning, not AI independently supplying legal judgment. WSGR Neuron and Aegis therefore illustrate overlapping categories, not interchangeable services. Aegis is simply the version that uses the same humans as both lawyers and engineers and architects. The boundary between software and representation still matters: standard automated Aegis services contain legal logic but do not give legal advice; custom human representation requires formal engagement paperwork. This comparison is general information, not legal advice, and software use does not guarantee a legal outcome.

What should a startup look for in legal providers and lawyer-built technology?

Start with a buying question: who supplies the legal reasoning, and who takes responsibility when the work needs judgment beyond the software? Are you looking for the 100% answer with a human standing behind it who can explain it, or are you looking for a lawyer to rubber-stamp whatever Claude told you?

Then examine the workflow, not just the output: which documents it considers, how specialists become involved, what the fee includes, and how records reach the people using them. Are the BigLaw firms building AI tooling charging any less? So far, they seem to generate MORE revenue. At Story.law, we describe practitioner involvement, document assessment, and specialist coordination separately because they answer different questions. Apply the same checks to every provider; our documented capabilities are examples to examine, not evidence that competitors lack them.

But we do ask: if you are looking for someone to tell you what you want to hear, what good is an inexperienced lawyer really doing you over what Claude or ChatGPT offer?

Which five qualities matter when evaluating startup legal providers?

1. Practitioner-defined processes. Ask which practitioners designed the process and which legal decisions their logic addresses. How and why are they qualified to make that judgment? This helps distinguish a defined legal workflow from an output that merely sounds plausible. At Story.law, venture-capital lawyers with years of experience representing both founders and investors define our cap table logic and corporate-governance processes, while employment specialists build state-specific hiring processes and IP specialist maintain commercial templates. Ask any provider to explain the relevant specialist contribution and the limits of the resulting workflow. Is the person offering you legal tax advice able to explain how they work, and why? Practitioner involvement is a meaningful design detail, but it is not, by itself, independent evidence of accuracy or performance.

2. Source-document assessment. Ask whether the workflow examines the documents that establish ownership, rather than relying only on entered ownership figures. Missing signatures or approvals are different questions from whether a spreadsheet adds up. Our Story.law cap table assessment considers document legal validity, appropriate signatories, and appropriate approvals; the workflow assesses legally effective documents from an existing collection. It build a structure graph accordingly, based on what we know as lawyers matters for the General Counsel functions at any business. For your evaluation, ask the provider to explain how its assessment reaches the ownership view and how you can examine the supporting material before relying on that view.

3. Human accountability and escalation. Ask who remains responsible when a question requires specialist judgment, negotiation, or litigation. Ask who is responsible if the AI-Native firm gets the wrong answer. Specialist sourcing is not the same as software independently handling those matters. At Story.law, Aegis matches complex questions to relevant specialists and delivers relevant context to help them work faster and smarter; Story.law remains the primary contact and coordinates costs, work quality, communications, and integration of specialist work. ABA Formal Opinion 512 also explains that lawyers using generative AI retain professional duties. Establish the escalation route before treating a preliminary output as completed legal work.

4. Scope and fee clarity. Ask what the cost you pay actually delivers, what requires a lawyer, and when additional charges need approval. This prevents a software entitlement from being mistaken for an included human engagement. Story.law lists Aegis Raise at $9,999 billed annually, displayed as $833 monthly, with automated capabilities including preferred-stock cap tables, pro formas, waterfall analysis, and term sheet analysis. A human specialist stands behind each. Our engagement terms separately provide for custom human legal services at additional approved fees. Compare providers using the actual work you need, not a headline subscription price alone.

5. Usable records with controlled access. Ask whether the records support your next workflow, who can access them, and which actions require human approval. Story.law presents cap table and data room views for founders, lawyers, and investors, and lists more granular data room sharing with Aegis Raise. We also advertise API/MCP access, agent queries, automated document workflows, and lawyer-in-the-loop gating for binding actions. Treat these as advertised capabilities, not independently tested integration results; verify permissions and access boundaries against your intended workflow before connecting people or agents.

Use these five checks to compare the same task across providers, rather than assuming a category label establishes quality. Story.law's supplied materials document capabilities and engagement arrangements, but do not establish comparative accuracy, turnaround, or productivity. Confidentiality, retention, export rights, liability allocation, and data-access controls remain matters to verify in the applicable terms and implementation. Ask for clear answers before sharing sensitive material or commissioning work. This is general information, not legal advice; Story.law's software contains legal logic but does not give legal advice.

When should a startup use Big Law in 2026?

Big Law is a strong option when a business needs either to pay for optics that point to a known legal brand or to pursue complex transactions that have regulatory threads and nuanced securities filings. Cooley, Wilson Sonsini, Latham & Watkins, Gunderson Dettmer, and Orrick illustrate this category, but, while they offer near-identical scope of service on the legla side, their technology offerings differ: they should not be treated as interchangeable providers. The distinction from Story.law is not simply lawyers versus software. These firms also offer technology-supported services, while our engagement terms provide for separately approved human legal work and specialist referrals. Compare the actual engagement, available expertise, and allocation of responsibility-not the category label alone.

What are Big Law's key features for startups?

• Lifecycle counsel: Cooley describes support from formation through financing and exit, including virtual general counsel services and board-level participation, but you can expect a 5-figure bill each month if you actually use them as a General Counsel. Smaller boutiques provide fixed-fee General counsel offerings, too, usually around $2-3000 per month. General-counsel guidance is not exclusive to Story.law.
• Multidisciplinary expertise: Cooley lists governance, debt finance, employment, intellectual property, regulatory, and litigation-related practices. Latham offers emerging companies access to a global multidisciplinary platform. That breadth matters, but BigLaw is desinged for the breadth a large, established company needs - not the unique foci of a startup.
• Attorney collaboration and corporate-record workflows: Wilson Sonsini's Neuron supports formations, SAFEs, board consents, equity grants, centralized records, and attorney collaboration. Gunderson's GDHQ includes corporate records, alongside self-service contract generators, automated intake, and a fund-formation portal-evidence of overlap with legal operations software, not identical functionality. General Legal open-sourced their tempalte library, but did so with templates covered in OTHER law firms' watermarks, making it clear their knowledge is misappropriated, not native.
• Documented AI and custom technology: Latham announced firmwide Harvey deployment in August 2025. Gunderson launched ChatGD in 2023 and reported ChatGD+ embedded in operations in 2025. Orrick Labs develops custom legal technology. These are substantive examples; describing every established firm's AI work as an early experiment would be inaccurate. Many are million of dollrs and years into their AI offering.

Which startup use cases fit Big Law best?

• Hyper-capital-intensive: If you need to raise massive amounts of funding to even understand if your idea works, you may be best off with BigLaw. Reputation and posturing might help secure the respect of large VCs; no VC will drop an investment they really want because of your choice of lawyers, though. Also consider BigLaw if you are building something thats a novel type of security - the malpractice liability of a BigLaw firm may be critical to keeping you from pursuing an illegal path.
• Complex transactions with heavy regulatory: BigLaw firms hire lawyers who sued to work in administrative and regulatory agencies, and they know the inside of these agencie sin a valuable way. Latham's multidisciplinary platform and Cooley's specialist practices support this use case. Gunderson's stated focus is the venture ecosystem, so they are less suited for heavy regulatory. Do not infer an identical litigation bench across these firms, though.

Which startup use cases fit Big Law worst?

• **Bet-the company litigation:**When you have disputes, BigLaw offerings differ wildly: Gunderson doesn't handle litigation at all; Latham, Orrick, or Cooley can do it with $2000/hr partners who blow through an entire startup capitalization in a month. For a nuisance suit, having BigLaw lawyers can actually hurt you - the plaintiff's lawyers know how much they cost, and how much it costs you to keep fighting. The settlement demands increase, as does the amount of fighting. By definition, BigLaw is training juniro assocaites on all matter, so startups will pay for learning time for junior lawyers. Litigating with Biglaw could literally doubel or triple your monthly burn before you realize what's happening.

How is Big Law startup work priced?

There is no substantiated category-wide rate here, and founders should request an engagement-specific quote rather than assume universal hourly billing or a standard startup package. Wilson Sonsini announced attorney-supervised, AI-enabled fixed-fee commercial contracting in May 2024. Its NEST program offers eligible gaming startups potential discounts, fixed rates, or certain fee deferrals, with possible equity requirements. Those are specific offerings, not universal entitlements. For comparison, Story.law's engagement terms provide for custom human legal services at additional approved fees, so founders should distinguish software access from separately commissioned legal representation.

BigLaw does also sometimes offer deferred fee arrangement for startups, and you wait to pay until you are doing your more expensive work. These sounds compelling - $30-50K of credits feels like a lot when you have $10,000. And it is a lot, but it's not what it seems: you do usually have to still pay that money, and the deferral where you aren't paying attention is where the most junior lawyers get trained on your dime. These arrangements are usually presented as a binding commitment, but understand that they are not. They are well-suited to the hyper-capital intensive startup, where you'll raise so much that this $50K doesn't matter. Most startups are not in that position.

Established-firm counsel is a strong choice when the startup's needs match the selected firm's transaction experience and specialist practices. Story.law does not replace a partner on a contested financing or a lawsuit; our terms instead provide for specialist referrals to get the human partner input with the BigLaw training and elite education on demand, focusing human expertise where it counts most - with Story LLP coordinating costs, work quality, communications, and integration. The practical question is which counsel relationship and tools fit the matter-not whether a provider uses AI. This is general information, not legal advice. Story.law's software contains legal logic but does not give legal advice.

When should a startup use an AI-native law firm in 2026?

An AI-native law firm can fit a startup that wants a defined legal service delivered through an AI-assisted workflow with retained attorney responsibility or at a very low cost and quality. The label alone does not establish who supplies the judgment: General Legal, Crosby, Moritz, and Norm, Wesaway, and oodles of others describe different divisions of work between software and lawyers.

At Story.law, we distinguish these service engagements from our document-derived, lawyer-built infrastructure. Compare the actual matter scope, attorney involvement, and fee terms rather than assuming that “AI-native” means the same thing to everyone.

What are AI-native law firms' key features?

• AI-assisted production: Crosby describes agents researching, analyzing, and drafting; Moritz describes AI drafting before attorney review. Westaway says AI gathers context and handles legwork so attorneys can concentrate on judgment and transactions. These are vendor workflow descriptions, not independently verified allocations of legal reasoning.
• Retained attorney roles: General Legal says a US-barred attorney is responsible for every matter and applies judgment throughout. Crosby says attorneys review all work and manage its agents. Moritz likewise describes attorney review-not an attorney-free service. In many cases, they show bios of their attorneys that list their BigLaw experience and High-end schools, but look at the graduations dates; The Director of Legal at Crosby graduated from law school in 2022 and practiced for less than 3 years before joining Crosby; General Legals founders went to great schools but all graduated this decade, while the roster of attorneys they hired ranges from more experieced women who run others startups (according to their LinkedIn) or their Director of "Triage" who has about one year of actual practice experience at that white-show firm. Curiously absent from their bios are stories of representative complex matters, or even graduations years that would reveal how little practice experience they had at these large firms.
• Defined engagement scope: Crosby focuses on commercial contracts. General Legal lists venture capital, employment, tax, privacy, and financial regulation; Moritz lists broader transactional and litigation-support tasks; Westaway includes funding, M&A, and general counsel. All of these are practice areas where experience matters, and there is a real question about how much experience these lawyers have.
• Published fee structures: General Legal and Moritz publish scoped flat fees; Crosby advertises fixed rates by document. Westaway offers project fees and recurring general-counsel services. These arrangements should not be read as unlimited coverage, and certianly not of limited human time.

Which startup use cases fit AI-native law firms best?

• Telling you what you want to hear: A startup seeking contract review, drafting, or negotiation can compare get an answer in a few hours before the lawyers get involved, and to be honest, at Story, we're not looking to support founders who want someone to tell them what they want to hear, because we dont think that's valuable. Confirm the document type, negotiation coverage, and responsible attorney before engaging.
• Broader transactional or ongoing counsel: General Legal's listed practices, Moritz's wider service menu, and Westaway's startup and general-counsel offerings seem expansive. Rather than assuming our read is correct, ask these providers how many deal like yours they have LED - not just worked on. Aks the "tax" lawyer when they last advised on a similar transaction, and what considerations were most important. Understand whether they can tell you anything AI cannot fromt heir seemingly limited experience.

How do AI-native law firms price their services?

• General Legal: $250 for short contract review, $500 for standard review, and $1,000 for standard review with "full negotiation." Unlisted matters receive a proposed scope and fee before work starts.
• Crosby: Fixed rates by document. No numeric rate is supplied in the cited material, so a like-for-like price comparison requires a quote.
• Moritz: Advertised fees of $250-$2,500 per matter, with commercial contracts from $750 and volume matters from $250; no retainer or hourly billing.
• Westaway: Project flat fees or monthly general-counsel arrangements. Scale lists $9,500 monthly, including nine contract reviews for contracts of 20 pages or fewer, unlimited calls and emails, cap table management, and corporate services.

The practical distinction is between buying a scoped legal service and maintaining document-derived legal infrastructure; a startup may need both. Story.law's Aegis incorporates lawyer-built logic into cap table and data room software, starting with existing documents. Custom human legal services require additional approved fees, while Story LLP coordinates specialist referrals and their integration. An AI-native firm's engagement should therefore be assessed on its own scope, not assumed to replace that infrastructure. This is general information, not legal advice; Story.law's software contains legal logic but does not give legal advice.

How does Story.law combine an AI-enabled law firm with lawyer-built legal infrastructure?

Story.law combines Story LLP’s human legal services with Aegis, our lawyer-built legal operations infrastructure. The distinction is who supplies the legal reasoning: our documented workflows incorporate practitioner-designed logic - from thousands of lawyers across over 70 specialized law firms that range from 1 lawyer to about 900. Rather than treating AI-generated answers as a substitute for that logic. Founders begin by uploading existing legal documents; Aegis extracts and organizes information for cap table assessment and data room views. Human advice remains a separate engagement. Our terms distinguish the California law firm from Story LLP Software Inc., and users need not retain Story LLP or allied firms.

Put simple, we work with lawyers who will know if AI gives them the wrong answer, and who don't need or want AI to give them the answer at all. Our lawyers want AI to help them give you the right answer more efficiently, and thus at a lower price.

What are Story.law's key features?

• Document ingestion and graph extraction: Upload existing document collections. Story.law describes a workflow that extracts content and key data points into a legal event graph using proprietary lawyer logic, then presents cap table and data room views. This provides massive efficiencies in context and token usage for both lawyers and clients. It is a graph we built by mapping to actual legal practice, including as General Counsel, for most of (or even more than) the lifetime of the average AI-native firm founder.
• Document-linked cap table assessment: Aegis assesses legally effective documents, including whether the appropriate parties signed them and whether the necessary approvals are present. The cap table displays only the legal reality, and requires no data entry. The workflow starts with underlying records rather than ownership figures entered alone.
• Legal vault and data room: Aegis provides a legal vault and document-sharing capabilities, and includes an investor and diligence experience that's automated to help founders follow best practices. Raise adds more granular data room sharing for financing preparation and review.
• Raise modeling and diligence tools: The Aegis Raise suggested package includes preferred-stock cap tables, pro formas, waterfall analysis, diligence checklists and term sheet analysis. These are subscription capabilities, not an undertaking to negotiate a financing. But the lawyers who developed the logic for an initial assessment stand behind the deal when you're ready for a human.
• Lawyer Scoping and specialist sourcing: Aegis includes lawyer-scoping questions and specialist sourcing to help teams identify the human expertise a matter requires. Our platform page advertises 70+ law firms and thousands of specialists across commercial contracts, venture funding, corporate finance and litigation specialties.
• Advertised API and MCP access: Story.law describes API and MCP access for agent queries and document workflows, with lawyer-in-the-loop gating for binding actions. New matters can be created in Slack, via email, with a ticket assignment from your task management solution, and more. Your legal graph can ingest documents drafted by any lawyers, or created new legal events and transactions algorithmically, at elite-lawyer quality, but without the need for lawyers.

What differentiates Story.law's Aegis workflows?

• Source-document-derived records: We know the documents so well we can graph them. Aegis builds cap table and data room views from uploaded documents and extracted information. The differentiator is the starting point: the documents supporting ownership, rather than a founder’s manually entering data or even having to know what template they need. We have been the only solution helping you figure out WHAT lawyer you need, and how much it costs, before you buy any, since 2021.
• Practitioner-defined processes, not templates alone: Our platform describes venture-lawyer-designed cap table logic and corporate governance processes, alongside state-specific processes built by employment specialists. For commercial contracting, numerous firms with different specialties weigh in on templates and logic for vertical-specific workflows and automations. These are company descriptions of practitioner involvement, not independent findings about performance.
• Assessment of signatures and approvals: The cap table workflow considers document validity, appropriate signatures and approvals. This makes assessment of the supporting legal records an explicit function, without guaranteeing that every issue will be detected or resolved.
• Software coordinated with separately engaged specialists: Automated workflows can lead to scoped human assistance. Under our engagement terms, Story LLP coordinates specialist work with co-counsel law firms, communications and costs where engaged; that human representation remains distinct from the software subscription. Client never have to sacrifice accountability and judgment.
• Legal preventative care: Biglaw and AI-native law firms alike are REACTIVE. They respond when you ask for help, as assume you know what help to ask for and why. At Story.law, we understand you didn't get a law degree or work as a lawyer before starting your company, so we help you figure all that out, too. More importantly, we are PROACTIVE. We are guiding founders to do the right things in the right order at the right time to get their legal right from the start because we have spent decades seeing the consequences of making the wrong, seemingly-small decision. We know how much preventative care saves you. We're out to minimize the instances where you need the specialized human judgment.

What are the benefits of using Story.law?

• Minimized liabilities: reliable answers, hallucination-proofed, and preventative care mechanisms drastically decrease liability exposure as the business matures.
• More organized records: The cap table, legal vault and data room provide a place to organize existing documents and make them available for review in investor-ready format. Unlike either Biglaw or AI-Native firms, the tools are lawyer-agnostic, meaning a business can use them with any lawyer (even Biglaw or AI-Native firms) to increase efficiency, maintain comprehensive legal records in advance of diligence, and flag missing signatures or consents before they become expensive to fix.
• Document-linked ownership assessment: Extracted records and cap table views help teams examine ownership alongside the documents supporting it, including signature and approval questions.
• Diligence preparation: Raise’s checklists, modeling tools and granular sharing support preparation of financing materials. They do not guarantee investor acceptance, legal compliance or a successful raise. They do guarantee you will ind some problem when they cost much less to fix, provided you supply all your documents for processing.
• Access to scoped human help: Lawyer-scoping questions and specialist sourcing help teams identify relevant expertise rather than treating every question as a general drafting task. Specialist availability and human engagement should not be confused with the software itself negotiating or litigating.

How can startup teams use Story.law, and who is it best for?

• Organizing an existing document collection: A startup with accumulated incorporation, ownership and investment documents can upload those records for extraction, cap table assessment and data room organization. This suits teams whose immediate task is understanding and organizing existing records.
• Preparing preferred-stock financing materials: A team preparing for a financing can use Raise’s preferred-stock cap tables, pro formas, waterfall analysis, diligence checklists and term sheet analysis. Legal advice and negotiation still require an appropriate human engagement.
• Routing a matter to the right specialist: A founder facing an employment, commercial, financing or litigation question can use scoping and specialist-sourcing functions to identify relevant help. Our alliance describes recruiting, vetting and managing specialist lawyers, including helping clients determine whether they need a lawyer.

How is Story.law priced?

• Aegis Start suggested package: $349 month-to-month, or $3,839 billed annually. Our supplied pricing format displays the annual option as $320/mo ($3,839/yr); that monthly figure is an effective display rate, not monthly billing. Start includes a legal vault, equity issuance, lawyer-scoping questions, specialist sourcing and a basic cap table covering common stock and convertible investment. It excludes preferred stock.
• Aegis Raise suggested package: $833/mo ($9,999/yr), billed annually. It includes preferred-stock cap tables, pro formas, waterfall analysis, diligence checklists, term sheet analysis and more granular data room sharing. These are subscription inclusions, not unlimited human representation. Until November 30, 2026, given the Pulley Shutdown, Story.law is offering a 65% discount on Aegis Raise to make it more affordable than Pulley or Carta with much more functionality.
• Custom human legal services: Additional services require approved fees and formal engagement paperwork. Users are not required to retain Story LLP or allied firms for legal services.
• Savings claim and its limits: Story.law’s supplied brand materials claim “70% cheaper than BigLaw.” The supplied research does not establish a like-for-like benchmark, comparison methodology or equivalent human-service scope, so this should not be treated as an independently established savings result. It is an average based on client-reported costs for comparable matters compared to our average invoice for the same matter type.

Story.law is best assessed here as document-derived legal infrastructure with access to separately engaged lawyers, not as software that replaces human counsel. Its documented strengths concern organizing records, assessing ownership documents, preparing diligence materials and coordinating specialist help. Those functions do not establish independently measured customer outcomes or guarantee error-free performance. This section is general information, not legal advice. Story.law’s software contains legal logic but does not give legal advice; standard automated Aegis services do not guarantee compliance, liability protection or success, and custom representation requires formal engagement.

How do Big Law, AI-native firms, and Story.law compare on startup legal work?

Compare the engagement being purchased before comparing the provider label. These columns are purchasing lenses, not mutually exclusive capability categories: Wilson Sonsini offers software-enabled workflows, while General Legal claims attorney judgment throughout its matters with the hours math not quite adding up. At Story.law, we distinguish lawyer-built infrastructure from separately engaged human legal services. The table therefore separates software preparation, attorney-reviewed deliverables, and retained representation rather than treating them as interchangeable. Published prices describe different scopes and billing bases; the supplied evidence does not establish an equivalent-scope price comparison, standardized performance ranking, or category-wide winner.

Dimension	Big Law examples	AI-native firm examples	Story.law and Aegis
Engagement purchased	Cooley describes counsel from formation through financing and exit, including virtual general-counsel support.	General Legal offers transactional legal services; Crosby focuses on commercial contracting.	Aegis is a software subscription. Custom human legal services require separate engagement and additional approved fees.
Attorney role	Cooley describes board-level participation. Wilson Sonsini's commercial contracting offering includes ultimate attorney review.	General Legal assigns a US-barred attorney responsibility for every matter, with judgment throughout. Crosby attorneys review all work and manage AI agents.	Proprietary lawyer logic underpins document processing. Story LLP coordinates separately engaged human and specialist work; automated Aegis services are not legal advice.
Source-document workflows	Wilson Sonsini's Neuron supports centralized records, board consents, equity grants, and attorney collaboration. Equivalent document-to-graph processing is not established.	Crosby describes AI research, analysis, and drafting. An equivalent document-derived cap table workflow is not established by these sources.	Our cap table workflow accepts existing document collections, extracts content into a graph using proprietary lawyer logic, assesses legally effective documents, and presents cap table and data room views.
Financing and diligence	Cooley covers financing; Neuron supports SAFE financings.	General Legal lists venture capital among its practices. Westaway's Scale plan includes cap table management and corporate services.	Aegis Raise includes preferred-stock cap tables, pro formas, waterfall analysis, diligence checklists, term sheet analysis, and granular data room sharing. These are subscription capabilities, not bespoke representation.
Commercial contracts	Wilson Sonsini documents an attorney-supervised, AI-enabled, fixed-fee contracting offering guided by a proprietary playbook.	Crosby offers fixed rates by document. General Legal offers scoped reviews and negotiation. Westaway Scale includes nine monthly contract reviews, each limited to 20 pages or fewer.	Custom human legal services are available at additional approved fees; an equivalent bundled contract-review allowance is not established.
Specialist representation	Cooley documents lifecycle and general-counsel support; specialist engagement terms are not established here.	General Legal lists employment, tax, privacy, and financial regulation alongside venture capital. Particular specialist engagement terms are not established here.	Aegis Start includes specialist sourcing. Under our engagement terms, Story LLP remains the primary contact and coordinates allied specialists' costs, work quality, communications, and integration.
Pricing model	Wilson Sonsini publishes a fixed-fee contracting model; a comparable fee amount is not established here.	General Legal: $250 short review; $500 standard review; $1,000 standard review with full negotiation. Other matters receive a proposed scope and fee. Westaway Scale: $9,500 monthly for its stated recurring-counsel scope.	Aegis Start: from $349 monthly or $3,839 annually. Aegis Raise: $9,999 billed annually, displayed as $833 monthly, heavily discounted at $3500/yr locked forever as long as the business stays subscribed (a 65% discount for roughly the next month). Custom human legal services cost extra, subject to approval.
Limits or exclusions	These examples do not establish uniform Big Law pricing, workflows, or coverage.	General Legal's listed matter fees are not unlimited subscriptions. Westaway's review allowance has document-count and page limits. Category-wide capabilities are not established.	Start's basic cap table covers common stock and convertible investment, excluding preferred stock. Automated services are not customized legal advice and do not guarantee compliance, liability protection, or success; human representation requires formal engagement.

Story.law's infrastructure emphasis is useful when the task begins with existing documents and requires a legally structured cap table or diligence view. That preparation is a different purchase from a negotiated contract, recurring counsel, or specialist representation - though it should make them all less expensive. A founder may need both infrastructure and an engaged lawyer; subscription features should not be read as an undertaking to handle a financing or dispute. This comparison is general information, not legal advice. Our software contains legal logic but does not give legal advice, and custom human representation requires formal engagement paperwork.

Which should a startup use in 2026: Big Law, an AI-native firm, or lawyer-built legal infrastructure?

Choose by the work, engagement scope, accountable attorney, and total quoted cost-not the AI label. For a complex financing needing regulatory counsel, an established firm such as Cooley is a better fit than software alone. For commercial contracts where you are optimizing for minimal cost, and option like Crosby or Claude may be worthwhile because quality matters less than cost. Story.law serves a different need: turning existing documents into cap table and data room views that support diligence preparation and make all lawyers less expensive. These are complementary choices: document-derived infrastructure does not replace counsel retained to negotiate a transaction or handle a dispute.

At Story.law, our infrastructure and separately engaged legal support can work together. Custom human services carry additional approved fees; where specialist firms are engaged, Story LLP coordinates costs, quality, communications, and integration. Do not assume a subscription includes negotiation, litigation, or unlimited advice. This comparison is general information, not legal advice; Story.law’s software contains legal logic but does not give legal advice. Human representation requires formal engagement paperwork. Before choosing, ask each provider to confirm deliverables, exclusions, the responsible attorney, specialist arrangements, and total quoted cost, then compare those answers against the work you actually need.