Cypris is an R&D and IP intelligence platform sold by IP Web, Inc. of New York City. It unifies patent and scientific data: 198 million patent documents from over 150 countries, 341 million research papers from 274,000 journals and repositories, 125 million indexed chemical compounds with structure search, and market and regulatory sources, connected by a proprietary ontology. AI agents cover technology scouting, literature review, competitive intelligence, prior art, regulatory research and white space analysis, retain project context and can be configured to a team's own methods.
The Knowledge Management product lets a company search its internal documents alongside the external data. Research Briefs are written by the vendor's own analysts, with each subscription including a set number of reports and briefs a month. Integrated Intelligence exposes the data to a customer's own Copilot, Claude or ChatGPT through an MCP server and API. Models come from OpenAI, Anthropic and Google and are metered as AI credits.
Buyers are corporate R&D and IP teams, among them Johnson & Johnson, Yamaha, Oerlikon, NASA and Los Alamos National Laboratory.
Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.
Other products that do the same kind of work as Cypris, and what each one does.
All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.
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.
The platform is organized around agents and priced by model usage. The site leads with AI agents for every stage of the R&D process, built for technology scouting, literature review, competitive intelligence, prior art, regulatory research and white space analysis, with agents that retain project context and can be configured to a team's own methods. Semantic retrieval across the data runs through a proprietary ontology rather than keyword matching.
The agreement makes the metering explicit: AI credits are allocated annually and consumed per session at a rate reflecting the processing cost of the model chosen. Remove the models and a large licensed database remains, which is what the vendor positions itself against. The human side is separate: Research Briefs are written by the vendor's analysts, and the site calls them built for decisions where accuracy matters too much to leave to AI alone.
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.
Every AI output is described as anchored to source citations, and the published comparative study makes that checkable. It states its method, names the date, preserves the outputs, gives the verbatim queries, and says the patent numbers and assignees were checked against USPTO Patent Center and WIPO PATENTSCOPE. The study also discloses that the vendor commissioned it and has a commercial interest, and records a place where its own tool fell short, failing to fully separate two related bodies of work.
No measurement of the platform's own precision or recall against a gold standard is published: the study counts what competitors missed rather than what Cypris misses. The agreement runs the other way, disclaiming any warranty that results will be accurate, complete or error free.
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.
Agents are published as executing research workflows across large datasets in parallel, generating deliverables and monitoring continuously, which is autonomy over research rather than over a client matter. Against that, the vendor sells Research Briefs as human in the loop work written by trained analysts, and frames them as being for decisions too important to leave to AI alone. That is a statement about a different product, not a checkpoint in the automated one.
Nothing published describes what an agent decides on its own, at what point a person reviews an agent's output before it informs an investment or filing decision, or what the system does when its evidence is thin. The agreement is silent on oversight, and the vendor reserves the right to change the available models at any time.
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.
Customers are named across three industry sections with what each uses the platform for: Johnson & Johnson for cross domain research intelligence spanning materials science and pharma, Yamaha for scouting emerging technologies and landscaping suppliers, Oerlikon for monitoring compound activity and tracking competitive filings across global patent offices. Government and research customers named elsewhere on the site include NASA, the US Air Force and Los Alamos National Laboratory.
Two testimonials carry a name and title, Chuck Wright, Corporate R&D Manager at NOV, and John Parks, Senior Footwear Innovation Developer at Brooks Running, each with a published customer story. Scale is given as hundreds of R&D teams and thousands of researchers. The strongest figure is that work which took weeks now takes days, with no baseline, period or method behind it.
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.
In the published agreement, confidentiality is mutual, covers information whether or not marked confidential, restricts disclosure to employees with a need to know, and survives five years after disclosure, with trade secrets protected for as long as the law protects them. On termination the receiving party must return or destroy every copy and certify the destruction in writing. Compelled disclosure requires written notice to the other party first and a reasonable effort to obtain a protective order.
The customer owns all right, title and interest in its data, and the vendor's carve out extends only to data derived from monitoring use of the service. Around that sit tenant isolation, row level security for the most sensitive data, least privilege access, background checks and audited access. No subprocessor list is published, no data processing addendum is referenced, and nothing treats the disclosure risk that unfiled invention material carries.
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.
The agreement disclaims all warranties and states specifically that no warranty is given that results will be accurate, complete or error free. Nothing says the output is not legal advice, nothing addresses an attorney client relationship, and nothing addresses who should review a freedom to operate assessment before a company acts on it. The output is legal in character: per patent freedom to operate risk ratings, novelty and prior art assessment, and white space identified for new filings.
On audience, Cypris says two different things. Product surfaces address IP teams, a patent committee and IP counsel directly. The vendor's own comparison writing says the platform is built for researchers rather than IP attorneys and points readers to other tools for prosecution and IP legal work. Both are the vendor's own words.
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.
The site argues at length that general purpose models cannot do patent intelligence, citing training data limits, the closure of the web to crawlers and the absence of ontological frameworks for claim scope, prosecution history and assignee normalization. It commits to being model agnostic and to updating its ontology continuously. Nobody is named as accountable for model behavior, and nothing describes what is tested before an agent or ontology change ships.
No disclosure addresses whether coverage or ranking differs across technology domains, languages or patent offices. No evaluation of the platform's own coverage gaps is published.
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.
Cypris publishes encryption in transit and at rest from the interface to the storage layer, HTTPS with modern TLS, hosting on major cloud infrastructure with network and data segmentation, firewalls and automated threat detection, least privilege production access that is regularly reviewed, row level security for the most sensitive data, multifactor authentication and single sign on, employee background checks, annual penetration testing by independent firms and continuous vulnerability scanning.
Data is stored within United States borders with no offshore routing. Customer data is never used to train models and is not shared with model providers for training. No retention period is published for prompts, outputs or uploaded documents, no subprocessor list is published, and the agreement carries no breach notification commitment, so what happens after an incident is unaddressed.
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.
The agreement gives the customer an indemnity against third party claims that the service infringes or misappropriates US patents, copyrights or trade secrets. It comes with stated conditions, two exceptions and the vendor's right to modify, replace or terminate if it cannot cure. The customer indemnifies the vendor for negligence, unauthorized use and unapproved combinations. Liability is capped at fees paid in the twelve months before the claim, for both the infringement indemnity and the agreement as a whole.
Consequential, incidental and punitive damages are excluded, along with loss of data and breach of data or system security. A wrong answer is not covered: the warranty section disclaims any assurance of accuracy or completeness, so a freedom to operate assessment that misses a blocking patent carries no recourse. No insurance or service level is published.
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.
The agreement treats API and Model Context Protocol access as part of the service rather than an add on. Integrated Intelligence connects a customer's own Copilot, Claude or ChatGPT to the patent, scientific, chemical, regulatory and market data, with prebuilt stage gate agents or custom agents built around the customer's workflows, and the vendor describes enterprise API partnerships with OpenAI, Anthropic and Google.
Journal access runs through a named third party with published terms: the Cypris Journal Connection links a customer's existing journal subscriptions through OpenAthens single sign on, with the OpenAthens flow down terms incorporated by reference. Single sign on is supported with leading identity providers. The vendor says integrations into electronic lab notebooks and enterprise tools are expanding, and no developer documentation is published.
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.
The platform is built and operated in the United States, with infrastructure across datacentres, hosting and operations based in the US, and Cypris states there is no offshore data routing, with no exceptions. All data is stored within US borders. Tenant isolation is described as by design, with customer data logically separated between tenants and row level security applied to the most sensitive data, hosted on major cloud infrastructure with network and data segmentation.
The company describes itself as headquartered in the US with US investors and leadership, and the agreement carries export control obligations and the federal commercial item clauses that government buyers need. No single tenant, private or on premises deployment is published, no cloud provider is named, and a buyer outside the United States has no region to choose.
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.
The vendor states it maintains SOC 2 Type II compliance, independently audited each year, with continuous controls monitored across availability, security and confidentiality. It points buyers to a trust center at a stable address where evidence of compliance is available. The portal shows SOC 2 marked compliant and lists more than fifty named controls across product, data, network, application, endpoint and corporate security.
It also lists more than 38 named policy and procedure documents, including access control, asset management, acceptable usage, endpoint security and data protection, behind a button to request access. Annual penetration testing by independent firms is stated separately. No audit period, auditor or subprocessor list is published, and there is no way to confirm from outside that a request is fulfilled.
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.
Cypris states that agents run on models from OpenAI, Anthropic and Google, describes the platform as model agnostic and multi model against competitors locked to one provider, and refers to enterprise API partnerships with all three. The agreement makes the arrangement concrete: AI credits are allocated annually by subscription value and each model consumes them at a rate reflecting its processing cost, so model choice is a priced variable.
Customer material is not shared with third party model providers for training. Nothing is published at version level: no model identifiers, nothing on which model serves which agent, and no statement of where inference happens. Instead of a change commitment, the vendor reserves the right to adjust available models, credit allotments and costs per prompt at any time.
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 is published anywhere. There is no pricing page in the navigation or the footer, and the only route is a demo request. The published agreement sets out the structure. Fees are set in an order form, seats are counted as named authorized users with a cap stated in that form, and the initial term runs at least a year and renews automatically unless either side gives forty five days' notice. Late payment carries 1.5 percent monthly interest.
Three consumption units are defined. AI credits are allocated annually by subscription cost and consumed per model session, expiring at the end of the year. Research paper credits are valued one to one with US dollars for buying closed access papers. Research entitlements are capped at one report and two briefs a month. None of it is attached to a number.
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.
Materials and chemicals teams get intelligence at compound level linking patent filings, scientific literature and regulatory data, with prior art search, freedom to operate analysis, competitive monitoring and chemical structure mapping, and Oerlikon is named. Industrial and manufacturing teams get technology landscaping, patent analytics, supplier scouting and literature review, with Yamaha named. Life sciences and pharma teams get deep patent family analysis, citation tracking, clinical and scientific literature review and pipeline monitoring, with Johnson & Johnson named.
Buyer types run from Fortune 100 companies to government agencies and national laboratories, and the agreement carries the federal commercial item clauses that public buyers require. No statement says where the platform does not reach, whether by right, jurisdiction or workflow.
The public pages on file for Cypris, 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.
Prompt and Output Retention, Third Party Request and Subpoena Notice, Bar Guidance Alignment and 1 more
Read Sep 20, 2026
Primary Law Corpus Provenance, Good Law Verification, Refusal and Uncertainty Behavior
Read Sep 20, 2026
Client Data in Training, Ethical Walls and Matter Segregation
Read Sep 20, 2026
Court Disclosure Support
Read Sep 20, 2026
Outside Counsel Guideline Readiness
Read Sep 20, 2026
Cypris publishes no price, plan or rate, and its site has no pricing page. Prices are quoted after a demo. The published agreement gives the structure. Fees are set in an order form. Seats are counted as named authorized users, with a cap stated in that form. Three consumption units are defined. AI credits are allocated annually by subscription cost, consumed per model session, and expire at the end of the year. Research paper credits are valued one to one with US dollars for buying closed access papers. Research entitlements are capped at one report and two briefs a month.
Implementation: Not stated.
Note: Under the agreement, the initial term runs at least a year and renews automatically unless either side gives forty five days' notice. Late payment carries 1.5 percent monthly interest.
Google's Gemini 4 Argon is now in the model picker in Cypris Q, Cypris's agentic research layer. Cypris says its internal testing found Argon beat Gemini 3.1 Pro on every question it tried and matched Claude Opus 5.5 at slightly lower cost, with answers about three times longer. It recommends Argon for white space analysis, competitive intelligence and technical landscape research.
A 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.
Can material a lawyer puts into this product be used to train a model?
A public policy or trust page states no training on customer content, with no matching term located in the published agreement.
The security page answers the question directly: asked whether Cypris uses customer data to train AI models, the answer is no, and the commitment extends to searches, interactions and data, covering both training its own models and sharing with third party model providers for training. The published Terms of Service contain no training clause at all, in either direction. What the agreement does give is ownership, stating that the customer owns all right, title and interest in its data, with the vendor's carve out limited to information derived from monitoring use of the service. The commitment therefore has no contractual remedy, and the vendor can amend the agreement by posting revised terms.
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.
How long anything is kept is not addressed. Nothing Cypris publishes states a retention period for prompts, agent outputs, saved searches, uploaded documents or the internal project material the Knowledge Management product is built to hold, and nothing describes deletion on request during the term. On termination each party must return or destroy the other's confidential information and certify it in writing. That covers material exchanged between the parties rather than the working data a team accumulates in the platform over years.
No retention commitment sits beside the promise not to train on customer data. The product's stated purpose is accumulation, with intelligence that compounds across projects and institutional knowledge captured so it survives departing employees.
Does retrieval respect the firm’s ethical walls, or can the model read across them?
The product maintains its own permission model, documented, requiring the firm to keep it aligned.
Cypris states tenant isolation by design, with customer data logically separated between tenants and row level security enabled for the most sensitive data. Access to production systems follows least privilege principles and is reviewed regularly, multifactor authentication is enforced for all employees and administrators, employees are background checked, and access privileges are audited. Single sign on is supported with leading identity providers so a customer can apply its own controls.
Its trust center lists named controls for production system user review, production database access restriction and identity validation. Nothing published sets out separation inside a customer: how one project, division or research program is walled from another.
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Terms commit to notice where lawfully permitted. No transparency report located.
The confidentiality section permits disclosure to the limited extent required to comply with a court order or other governmental body, or as otherwise necessary to comply with applicable law, but only where the disclosing party has first given written notice to the other party and made a reasonable effort to obtain a protective order. The customer learns of the demand before anything is produced, and the vendor must itself try to narrow or block it rather than leaving that to the customer.
Because the clause runs both ways it binds the vendor as recipient of the customer's confidential information. No operational detail, named contact, stated timeframe or transparency reporting on how often demands arrive is published.
Where does the law in this product come from, and does the vendor have the right to use it?
Sources are identified without stating the license or rights basis.
Published counts are 198 million patent documents from more than 150 countries, 341 million research papers from 274,000 journals and repositories, and 125 million indexed chemical compounds with structure, synonym, trade name and vendor resolution. The site adds more than a million tracked news sources across more than 200 countries and over a billion live commercial, market and regulatory sources. Data is described as real time and taken direct from global patent offices, publishers and trusted sources.
Licensing is addressed at the edges. Research paper credits let a customer buy closed access papers, with the vendor stating it takes measures to comply with publisher copyright restrictions and passing publisher rights and restrictions through to the customer at purchase. Journal access runs through OpenAthens under incorporated flow down terms. No license basis is stated for the indexed data itself.
Does the product tell you when the authority it just cited has been overruled?
The vendor computes and surfaces subsequent history itself, with the method described.
The nearest equivalent to whether an authority is still good is whether a patent is still in force, and Cypris addresses it. The source named is the registers themselves: data is described as real time and taken direct from global patent offices, across more than 150 countries, with no commercial citator or third party status product anywhere in the path. The status is live rather than periodic, outputs carry current legal status alongside assignee and filing date, and continuous monitoring tracks changes across filings.
The vendor's published critique of general purpose models turns on exactly this, that they cannot verify whether a patent has been assigned, abandoned or subjected to terminal disclaimer since their training data was collected. That is status currency rather than subsequent treatment: nothing published tells a user that a claim has been narrowed in prosecution, challenged at the board or limited by a court, and the freedom to operate risk ratings are the platform's own assessment rather than a record of what has happened to a claim.
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer.
The vendor's comparative study identifies the central risk of general purpose models as producing incomplete outputs with high confidence, noting that at no point did any model indicate the boundaries of its knowledge or flag that its results represented a fraction of the record, and that the better the format the less likely a user is to question completeness. Nothing on the home, security or about pages, in the product summaries or in the Terms of Service says what Cypris does differently.
There is no confidence score on a result, no stated threshold below which an agent declines to answer, and nothing describing what a user sees when coverage in a technology area is thin. The freedom to operate risk ratings are classifications of the patents found, not statements of confidence in the search behind them.
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 Cypris, and the vendor's site, press and directory profiles record no finding that its output was fabricated or inaccurate in a proceeding, a regulatory action or a published account. This is a statement about the public record rather than a finding about the product. The relevant failure here would be a missed blocking patent rather than an invented one, since results are anchored to filings a user can open in USPTO, Espacenet or WIPO PATENTSCOPE.
The vendor's own published study records one shortfall in its output, an incomplete separation between two related bodies of prior work in a test landscape.
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.
Nothing in the Terms of Service or on the home, security or about pages or the footer engages professional or ethical obligation. No rule of professional conduct, ethics opinion or bar guidance is named, and the duty is not engaged in general terms either. The Terms of Service carry no statement that output is not legal advice and take no position on an attorney client relationship, offering only a disclaimer of warranties.
Freedom to operate risk ratings, novelty assessment and white space for new filings are legal determinations in substance. One page names IP counsel and a patent committee as recipients of that work, another describes the platform as built for researchers rather than IP attorneys, and the buyer is often an engineer.
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The product does not touch a fee between a lawyer and a client. It operates before an engagement exists, or it is bought by a team that bills no client for the work. Savings claims aimed at the buyer’s own cost are recorded in the summary and do not make the row a savings claim, because no client bill is in the loop.
No lawyer's fee sits in this product's path. The buyer is a corporate R&D or IP department licensing a subscription for its own internal use, with the agreement limiting access to authorized users who are the customer's own employees, contractors and agents. Nothing is billed on to a client, no outside counsel relationship is mediated, and the vendor's own commercial framing is about research throughput rather than legal spend.
What the agreement does publish about money runs to its own charges: fees set in an order form, annual terms renewing automatically, AI credits allocated by subscription value and consumed per model session, research paper credits valued one to one with dollars, and capped entitlements of one analyst report and two briefs a month. None of that bears on disclosing machine assisted work to a client or on how such work is billed.
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The material exists behind a sales conversation or an executed agreement.
The trust center publishes the certification, more than fifty named controls across product, data, network, application, endpoint and corporate security, and more than 38 named policy and procedure documents. All are obtainable through a request access route rather than a sales conversation. The security page answers the standard questionnaire directly on training, encryption, access, penetration testing, tenant separation and single sign on.
The agreement carries confidentiality, notice of compelled disclosure, US export compliance and the federal commercial item clauses a government buyer needs. There is no subprocessor list, no audit period or auditor, no data processing addendum referenced, and no breach notification commitment anywhere.
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.
Nothing published addresses disclosing the machine's involvement to anyone outside the company. No court or tribunal sits in this product's path. The nearest forum question, whether AI assisted prior art or freedom to operate work needs to be disclosed to a patent office or relied on in litigation, is not raised anywhere on the site. What exists is evidentiary rather than procedural. Outputs are anchored to patent numbers, assignees and publication dates that a practitioner can verify independently in USPTO, Espacenet or WIPO PATENTSCOPE, and the vendor preserved and published the outputs of its own comparative study.
Nothing describes an exportable record of how a conclusion was reached, nothing distinguishes an agent's determination from an analyst's in the Research Briefs product, and no format or guidance is offered for any proceeding.
Every grade and every signal on this index is drawn from public sources and dated. If a record is wrong, out of date, or missing an artifact the index did not locate, send the source and it will be reviewed and the record redated. Vendors are welcome to submit documentation. Nothing on this index is for sale, including a listing, a placement, or a grade.