C
Caseflood
Caseflood is an AI intake platform, sold with an advisory engagement, for plaintiff and consumer law firms that run their own intake teams. The firm's reps handle every conversation inside Caseflood's workspace. They are supported by predictive dialing, AI texting and immediate response to new leads, live AI call guidance, case capture against the firm's own qualification rules, retainers in one click and call summaries prepared by AI.
Leaders get evidence at the level of each call, analysis of missed cases, coaching tools and a way to ask Caseflood how intake is performing. Caseflood configures the platform with the firm and helps diagnose and improve its intake and marketing operation over the following months. The company is backed by Y Combinator. Pricing is not published.
Caseflood, head to head
Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.
Alternatives to Caseflood
Other products that do the same kind of work as Caseflood, and what each one does.
- IIntakerIntaker is a cloud intake and client relationship management platform for law firms, built around website chat that qualifies leads around the clock.
- SSimplyConvertSimplyConvert is an intake, client relationship and case management platform for plaintiff and mass tort firms, founded by a mass tort lawyer, covering first contact through intake, filing…
- LLawmaticsLawmatics is a client relationship management and marketing automation platform built for US law firms, founded in 2017 by a team including practicing attorneys and a cofounder who…
- PPerspective AIPerspective AI replaces static intake forms with adaptive conversations led by AI, marketed as Intelligent Intake and positioned as structured capture rather than a chatbot.
- CCase StatusCase Status is a client communication layer for law firms. It sits on top of the case management system a firm already runs rather than replacing it.
- KKalindaKalinda is an AI intake agent for personal injury law firms from a San Francisco company founded by Sayan and Sohil Bhatia, two former AI researchers, and part of Y Combinator's Summer 2025 batch.
Capability grades
All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
AI drives much of the work inside an intake operation that people run, and the company is explicit that the people stay on the calls. Caseflood's AI makes dialing decisions on proprietary dialing infrastructure, texts leads to get them on the phone, prepares reps with what the caller already said, offers real time guidance that a rep can refresh mid call, captures and qualifies case details, handles the follow through after the call, and answers leaders who ask what is happening in the intake team and what to do next.
An optional personalized voicemail is offered separately. The FAQ answers the question of whether clients will talk to an AI voice agent with a plain no: the firm's reps hold the human conversations. The company also sells itself as much on expertise as on software, with a hands on engagement that audits the operation, configures the platform and coaches the team. Remove the models and a dialer, a call workspace, retainer tools and dashboards would still run.
Citation Accuracy and Hallucination Disclosure
Whether the vendor publishes measured accuracy on citations and assertions, grounds output to primary sources, and says plainly what its system does when it does not know. Legal has a documented public record of fabricated citations reaching filed briefs, so an untested claim of accuracy is not evidence.
Caseflood cites no law. The relevant accuracy questions are whether the guidance a rep reads during a call is sound, whether the case details the AI captures match what the caller said, and whether its qualification judgments sort leads correctly, because a lead wrongly screened out is a case the firm never signs. The site's own pitch counts cases turned down too soon and leads marked with the wrong status among the losses it fixes, which makes those error rates the natural measure of the product.
Nothing is published on the accuracy of guidance, captured details, qualification or call summaries, and no test, sample or error rate is described. The one control mentioned is that reps can review and lock captured information before it moves on.
Autonomy and Oversight Model
What the system decides on its own, what a lawyer must approve, and whether the vendor documents where the review point sits. A tool that drafts under review and a tool that files without one are different products and different risks.
People hold the conversations and the firm writes the rules. Caseflood's FAQ says the firm's intake reps handle every human conversation while AI supports dialing, texting, preparation, guidance during calls and follow through. The firm defines the cases it wants, the matters that need attorney review, its referral relationships and how it wants to communicate. Reps can review and lock captured information, and firm judgment stays central to qualification and representation decisions.
Leaders get a view of where cases are lost and coaching tools for reps. The design is silent on the AI's own outbound work. It texts leads to get them on the phone and handles follow through after calls. Nothing says what those messages may say, whether a rep approves them, how often a lead may be contacted, or when the AI must stop and hand the lead to a person.
Operational and Outcome Evidence
Named, dated evidence that the product works in production at real firms or legal departments. Case studies with figures and identified customers count. Unattributed testimonials and launch announcements do not.
Named firms with specific results, on the clients' own account. The home page features Schuerger Shunnarah Trial Attorneys, a firm of more than 200 employees across 22 states. It reports about 300 more cases signed a month from the same demand and 50 fewer cases lost after signing each month. Video from cofounder Robert Schuerger and two intake reps accompanies it, and one of the reps signed 23 cases in her first week.
Lawrence & Associates, with more than 50 employees across two states, reports a rise from 60 to 140 cases signed a month, and Justin Lawrence says speed to lead fell from about ten minutes to two seconds. The Schuerger Shunnarah story also credits Caseflood with hiring and training ten reps, turning a lemon law division into referral income and advising on marketing vendors, so the results reflect the engagement as a whole, not the software alone.
The figures are labeled client reported with individual results varying, and none is dated or tied to a stated measurement period.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Caseflood handles the first conversation between an injured or accused person and a law firm, which is where a prospective client's confidential facts first enter the firm's records and where the duty of confidentiality to prospective clients attaches. No customer agreement, product privacy policy or data processing terms are published. The only privacy document, updated 17 September 2026, covers the marketing website: it discloses PostHog session recordings that can capture form text before submission and RB2B visitor identification, with an opt out and respect for Global Privacy Control.
Nothing addresses who can see call recordings and captured case details, whether they are used to train models, how long they are kept or how firms are separated from one another. The notice is candid about the website; the product it sells has no equivalent.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
Firm judgment is written into the product design, and the professional responsibility questions around it are not addressed. Caseflood's FAQ says the firm decides which matters need attorney review and that firm judgment stays central to qualification and representation decisions. Because reps rather than an AI voice hold every conversation, the prospect is always speaking with a person, which removes a common disclosure problem for intake tools.
The questions around the conversation remain open. Nothing states that Caseflood gives no legal advice, although its live guidance tells reps what to ask and say to a prospective client. The AI texts leads directly, and nothing says whether those messages identify themselves as automated or how they comply with consent rules for automated texts and calls. Nothing addresses call recording consent across the 22 states one client operates in, or the attorney advertising and solicitation rules that apply to rapid outbound contact. No customer agreement exists to allocate any of this.
AI Governance and Bias Disclosure
Published governance over model behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
No AI governance position, accountable owner, testing before release, or finding on how the qualification guidance treats different callers or case types is published. The company describes configuring the platform with each firm and refining it over the first two months, with results observed against starting goals in the third. That is an operating cadence rather than a governance program. The question is concrete here.
An AI that decides whom to dial first, suggests which leads qualify and flags cases turned down too soon can treat callers unevenly by language, accent, age or type of injury, and nothing says whether anyone checks. The engineering cofounder's stated conviction that sales should remain human is a design principle, but no policy, review or measurement follows from it.
AI Safety and Data Stewardship
Retention, deletion, access control, and what happens to prompts and documents after they are processed. Whether the vendor states its subprocessors and its incident practice, or leaves the buyer to assume.
Nothing is published on how call recordings, texts and captured case details are encrypted, who at Caseflood or its engineering team can access them, how long they are kept, how they are deleted when a firm leaves, which subprocessors handle them, or how and when a firm would be told of a breach. The platform processes injury details, medical history and criminal allegations for firms with tens of thousands of leads a year, and none of those stewardship commitments is in writing.
The website privacy notice shows the company can write clear disclosures, naming its analytics and visitor identification providers and explaining how to opt out, but it covers only the marketing site. Caseflood's FAQ says integrations pass only what should go downstream, which is the single stewardship statement about the product.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
No customer agreement is published, so nothing states Caseflood's liability, warranties, service levels or recourse. The FAQ describes the relationship as both software and an ongoing engagement, with Caseflood diagnosing the operation, configuring the tools, executing changes and assessing results. The case study credits it with hiring and training reps and advising on marketing spend. That makes the allocation of risk more consequential than for software alone.
If guidance leads a rep to turn away a viable case, or automated texts breach calling rules, a firm cannot tell from the public record whether Caseflood shares any of the consequence. Every route to a contract runs through a free intake audit call, so the terms exist only in private.
Practice Systems Integration Depth
How deeply the product reaches into the systems legal work already lives in: document management such as iManage and NetDocuments, Word and Outlook, contract lifecycle management, matter management, e-billing, and court filing systems.
Integration is described as a service performed at setup rather than a set of named connections. Caseflood's FAQ says it connects the intake workflow with the firm's lead sources, case systems, documents and partner processes, and that the mapping is done during the first week of the engagement, including what should be passed downstream and which tools reps need inside the call workspace. Reps work in that workspace with everything the caller has already said, and signing the retainer happens inside the product.
For plaintiff firms, whose leads arrive from many vendors and whose signed cases move into case management systems such as Filevine, Litify or CasePeer, the connections are the product's spine, and none is named. There is no integrations page, no list of supported lead sources, CRMs or electronic signature tools, and no statement of what moves in which direction. A firm learns what connects only during the audit.
Deployment Model and Data Residency
Where the software runs and where the data sits. Multi tenant cloud, single tenant, private deployment, on premises, and whether region of residence is a published option or an enterprise conversation.
No hosting provider, region, tenancy model or deployment option is published. The product is plainly cloud delivered, a dialer and call workspace that reps log into, configured with each firm during the first week of an engagement. Beyond that the record is empty. A firm cannot learn where its call recordings and prospect data are stored, whether its data sits alongside other firms' in shared infrastructure, whether any processing happens outside the United States, or whether a dedicated environment is available to a large firm.
The company page describes its engineering cofounder's background building contact center systems for banks, telecom operators and insurers, the kind of buyers who ask these questions first, which makes the silence more notable rather than less. For clients operating in as many as 22 states, where the data lives is the question most likely to come from a firm's own clients, and the public record gives it no answer.
Security Certifications and Trust Center
Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.
No certification, audit report, penetration test or trust center appears anywhere on the current site, and the compliance claims made in a 2025 launch announcement are not repeated there. The company is well funded, announcing an additional $3.2 million round on its home page with Y Combinator among its backers, and sells to plaintiff firms whose intake calls routinely include medical details. No SOC 2 report or HIPAA posture is offered, and there is no published route to request one short of the intake audit call. A security review of Caseflood starts from nothing.
Model Supply Chain Disclosure
Which models sit underneath, whose they are, where they run, and whether the vendor commits to telling customers when that changes. A legal buyer inherits every dependency it cannot see.
No model, model provider, speech or voice provider, inference location or change notification is named. The company page says the platform is built to improve as AI models advance and that its team includes deep learning researchers, and the home page calls the dialing infrastructure proprietary, but nothing says which models write the texts, generate the in call guidance, transcribe the calls or produce the optional personalized voicemail.
The website privacy notice shows the company is willing to name providers, identifying PostHog and RB2B for its marketing site; no equivalent list exists for the product, where prospects' injury and case details are what the models process. A firm cannot tell whether a lead's account of an accident is sent to an outside model provider, under what terms, or whether that changes when the models advance.
Commercial Transparency
Whether a buyer can learn what this costs without entering a sales process: published rates, the unit being charged, what sits behind an enterprise tier, and what implementation adds.
No price, unit of charge, tier, setup fee or contract length is published. Every route in, from the header to each section of the home page, leads to a free 30 minute intake audit with the chief executive. The audit form asks for team size, monthly lead volume and monthly signed cases, which suggests pricing scales with the operation, but the site never says so. The offer is framed in outcomes instead, promising millions to tens of millions in additional attorney fee revenue.
The FAQ describes the product as software plus an ongoing engagement, so the cost of the platform cannot be separated from the cost of the consulting.
Firm and Practice Coverage
Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.
The buyer is described with precision, and the limits are implied rather than stated. Caseflood addresses firms already investing in leads and a dedicated intake team, and the FAQ opens by asking exactly that. Its tools are built for reps, intake managers and firm leaders, and its two named clients are plaintiff firms of more than 50 and more than 200 employees working across two and 22 states. The audit form lists the practices it expects to see: personal injury, workers' compensation, mass torts, medical malpractice, Social Security disability, employment, consumer law, criminal defense and immigration.
Its team page cites former Morgan & Morgan intake managers and an adviser whose referral platform serves more than 700 plaintiff firms, which reinforces the plaintiff focus. Nothing says who should not buy it. The audit form's smallest options, no intake staff and under 250 leads a month, suggest smaller firms are welcome, but no minimum volume or poorly suited practice is stated.
3 public documents
The public pages on file for Caseflood, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.
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caseflood.ai1 signal
Billing and Fee Posture
Read Sep 22, 2026
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caseflood.ai/product.html1 signal
Refusal and Uncertainty Behavior
Read Sep 22, 2026
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Fabricated Citation Record
Read Sep 22, 2026
Legal Signals
What each signal meansA signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
No customer agreement, terms of service or equivalent contract is published on any surface located, and no policy page states a position on training. Nothing is granted and nothing is withheld, so a client has no term to hold the firm to. Where a policy page does state a position, the row takes the matching policy value instead and the summary records that no agreement exists.
No customer agreement is published, and nothing on the home, Product or Company pages or in the website privacy notice states a position on training models with prospect or client data.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
No located public material states how long prompts and outputs are retained.
Nothing on the home, Product or Company pages or in the website privacy notice states how long call recordings, transcripts, texts or AI summaries are kept.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
No located public material addresses walls or matter level segregation.
Nothing on the Product page addresses separating matters or users within a firm's intake workspace.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
No term or policy on the home, Product or Company pages or in the website privacy notice addresses court or government requests for customer data.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
Guidance follows each firm's own qualification rules and playbooks, the Product page says; no legal corpus is identified.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
The product does not cite legal authority, and nothing on the Product page addresses checking authority for later treatment.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The vendor describes refusal or abstention behavior in public materials.
The Product page says qualification support gives the rep either a clear answer on whether the firm can take a case or a clear reason to send it for attorney review, under rules the firm defines. No published evaluation shows how reliably this happens.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
The AI Hallucination Cases database maintained by Damien Charlotin records no case naming Caseflood, and no court order, opinion or disciplinary record naming the product appears in the public record.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No located public material engages with bar or ethics guidance.
No material on the home, Product or Company pages engages with lawyers' professional obligations around AI assisted intake, solicitation or client communication, or names any ethics opinion.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.
The site promises millions to tens of millions in additional attorney fee revenue from better intake and cites cases signed per month. Nothing addresses how the service's cost relates to client fees.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
No located public material supports a client side disclosure obligation.
No subprocessor or model provider list and no disclosure material for clients is published on the home, Product or Company pages or in the website privacy notice.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
No located public material addresses court disclosure or verification certification.
The product supports intake calls rather than court filings, and nothing on the Product page addresses recording or disclosing AI use.