DeepIP vs ipQuants: how they compare in 2026

Every DeepIP module is model driven. Drafting turns an invention disclosure into claims, specification and abstract, and the review module checks claims for antecedent basis, dependency gaps and section 101 risk. The prosecution module analyzes rejections and drafts responses with case law citations. Patentability, prior art retrieval, freedom to operate and invalidity analysis map claims against more than 120 million patents and non patent literature, and drawing generation turns sketches and method steps into formal figures. DeepIP combines an OpenAI model hosted on Azure with proprietary models built for patent work. Without the models, the Word add in has nothing to do.

The models drive a core capability, and the agreement shows what sits underneath them. The terms divide the platform into three parts. The Qthena Digital Cockpit is for review, annotation and management of published patent documents. Analytics and big data features let a user query ipQuants' proprietary datasets and statistics without uploading their own content. Generative AI functionality, currently AskQthena, handles analysis, summarization, drafting and interactive queries. Only the third is generative. The first two are a document workspace and a statistics product that would still work without the models, and the company's original pitch was data rather than generation, built on EPO examiner, opposition and appeal member insights. Recent product work has gone into the generative layer, with named skills for drafting, prior art comparison, invention disclosure and drawing generation. Even so, it is a layer on a working platform, not a product that disappears without it.

The office action module drafts responses with case law citations from its citation engine, and prior art retrieval ranks references by relevance with the citation shown for each. Freedom to operate and invalidity conclusions link to the claim or prior art text that supports them, and Modern Times Legal's founder describes quoted citations linked to their sources. Retrieval is semantic, across more than 120 million patents and non patent literature. DeepIP says its models go through testing for factual accuracy with patent expert feedback, but publishes no accuracy figure, test set or error rate.

The published limits are candid, and none of them is a measurement. The company states that Qthena's drafting skill does about 80 percent of the work with the user finalizing, and that drawing generation reliably completes around 90 percent. It says it held both skills back until quality was adequate and expects higher figures as models improve. It also lists failure modes it attributes to other tools: broken geometry, wrong perspective, missing edges and incorrect part definition. Those are completion estimates, not accuracy figures. No test set, evaluation method or error rate is published, and nothing states how the percentages were reached. The terms disclaim accuracy directly: generative output is probabilistic, may not always be accurate, complete or appropriate, and may not be relied on as a sole source of truth. The sources are published patent documents and the company's own datasets, but no retrieval method is described.

Inside Microsoft Word, the product works as an assistant. Drafts, review flags, office action arguments and freedom to operate opinions arrive in the document, where attorneys comment, edit and track changes. The review module marks issues inside the claim text, and freedom to operate and invalidity conclusions link to the claim or prior art text behind them. DeepIP offers trials only to practitioners who draft and prosecute patents, and its terms leave the customer solely responsible for reviewing and validating every output. Nothing states what a module may complete without an attorney, or where its agentic prior art retrieval stops and hands back to a person.

A written commitment that the human decides, backed by real constraints in the agreement, short of published thresholds. The company states that the human is always in charge and decides each step, and that the drafting skill produces a first draft the user must finalize. The terms make that an obligation. The customer must evaluate output for accuracy and appropriateness, including through human review as needed. Output must not be relied on as a sole source of truth or as a substitute for professional advice, or used to make decisions with a legal or material effect on an individual. Review surfaces are real: the cockpit holds the documents, and drawings can be corrected conversationally, so a user can adjust reference signs and line work. What is missing is the threshold. The company says its team shows customers when AI generated drawings can be used, when they need correction and when they should not be used at all. That guidance is given during rollout and is not published.

Nixon & Vanderhye's Corey Hawse reports tasks that took 20 to 30 minutes now taking under five, and gains of 50 percent or more on the tasks where savings are sharpest. Schwegman, Lundberg & Woessner, with more than 100 practitioners, reports focused work rising from four to six hours a day to seven or eight. Philips saw about 20 percent better drafting and prosecution efficiency in a trial and now uses DeepIP for invention analysis, prior art, drafting and office actions. Dilworth IP chose DeepIP as its primary drafting system after two years of evaluating tools, and Wood IP and Greenberg Traurig are quoted by name. The figures are the firms' own estimates, and the case studies carry no dates. DeepIP reports more than 25,000 applications drafted and 40,000 matters assisted, and $40 million raised through a $25 million Series B announced on 3 March 2026.

ipQuants gives unattributed claims of scale in place of deployment evidence. It says Qthena is used by hundreds of corporate teams and law firms across the globe, without naming one. The one customer voice is anonymous, quoted only as a valued customer saying the product is for the smart user, with no firm, role or figures. No dated deployment, measured outcome or named reference is published. One partnership is documented by both parties, a different kind of fact from deployment evidence: Questel integrates Qthena into its own IP platform. The site navigation links a case studies page.

All customer data counts as confidential information under DeepIP's terms, which recognize that it may include material covered by attorney client privilege and keep the confidentiality duty on it indefinitely. The terms bar training on customer data, require model providers to keep it confidential and apart from other customers, and set out its destruction after termination. DeepIP lists section 203 of the German Criminal Code, the professional secrecy provision, beside ISO 27001, SOC 2 Type II and GDPR. Users and organizations are kept separate, and no matter level wall within a firm is described.

The published agreement makes substantive commitments, and privilege is not addressed. Section 15 defines confidential information to include customer content, customer information and generative AI inputs and outputs generated for the customer, so what a patent attorney puts into the tool is contractually confidential. Section 15.6 names the LLM providers and states that customer input and output are not used to train or improve their models. Identifying metadata such as email and IP addresses is not sent, access is through paid enterprise APIs, and abuse monitoring is off by default for at least one named provider, so prompts are not scanned. Section 15.6.2 leaves content under customer control until the customer deletes it, and section 9 commits to permanent deletion of all customer data on termination. Privilege and work product are not addressed anywhere. Nothing describes separation between customers or between matters inside a firm's own workspace, on a product built around shared project views and collaboration.

Not a law firm and not an attorney, DeepIP gives no legal advice, its terms state. Outputs and templates are tools for operational support, not guaranteed accurate, and the customer stays solely responsible for reviewing them and for advising its own clients. No attorney client relationship arises with DeepIP or its staff, including staff with patent backgrounds and the experts who run product sessions. DeepIP offers trials and demos only to practitioners who draft and prosecute patents, and tells inventors to consult patent attorneys. Duties of competence and supervision, and limits by jurisdiction, are not addressed.

A real published position on the advice line, with no engagement with professional conduct rules. The terms state that no legal advice is intended or offered by ipQuants in making the platform, its content or any tools, features or support available, and disclaim liability for decisions taken in reliance on any of it. Restrictions on how output may be used come with it. Output may not be relied on as a sole source of truth or as a substitute for professional advice, the customer must evaluate it including through human review, and output about an individual must not be used for decisions with a legal or material effect on that person. The public material is consistent: the company says the human is in charge at each step and does not claim the tool replaces skilled drafting. What is absent is the professional layer. No bar or patent office conduct rules are named, no ethics guidance is referenced, and no jurisdiction limit is drawn. Nothing addresses a representative's supervision or competence duties when a machine drafts a claim set or figures for filing.

An AI management system certified to ISO/IEC 42001:2023 is listed on the trust center, with a 2026 certificate available through an access request. The trust center's controls include board oversight briefings, control self assessments and tested continuity plans. DeepIP says its models go through testing and validation for factual accuracy, with a feedback loop to patent experts, but publishes no test method or result. No accountable owner for the models is named, and nothing is disclosed about whether output quality differs across technical fields or patent offices.

No governance position of any kind is published. There is no responsible AI page, principles statement, accountable owner or function, testing regime before release, management system or certification such as ISO 42001. Nothing addresses uneven output, which here would bear on performance across technical fields, drawing types and the languages of patent documents. The company does publish a quality philosophy: it withholds a skill until it is useful, and it does not tie itself to one model provider. That is product judgment, not a governance framework, and it names no reviewer, criteria or results. Its abuse monitoring setting is a confidentiality control. The site navigation and footer carry no governance page.

DeepIP encrypts data in transit with TLS 1.2 or later and at rest with AES 256, restricts access to production systems and databases, and requires multifactor authentication for remote access. Its trust center lists ten subprocessors with their roles and regions. The terms require zero data retention at the model provider and an opt out from provider abuse monitoring wherever the provider offers them. Customer data is stored only in the territories named in the order form and can be exported on request during the term. It is destroyed within 30 days of a final export, or after termination when no export is asked for within 8 days, with a destruction certificate on request. No incident notification commitment or breach timeline is published.

Published policy covers most of the ground. Under the terms, customer content stays under customer control until the customer deletes it, and on expiry or termination ipQuants permanently deletes all customer accounts, data and information. Data sent to LLM providers is anonymized, sent over encrypted paid enterprise APIs, kept on a minimized basis in line with those providers' policies, and not used to train them. Each party must promptly tell the other of any unauthorized access to or disclosure of confidential information. Availability carries a 99 percent uptime commitment, with fourteen days' notice of scheduled maintenance and prompt notice of unscheduled downtime. The gaps are specific: retention on the provider side states no period, and no encryption specification, access control model or audit logging is described. An Information Security Policy and a data processing addendum are linked without a login in the site footer.

Under its April 2026 terms, DeepIP warrants professional performance and a service free from reproducible errors against its documentation, with repair, replacement or termination as the remedy. It defends and indemnifies customers against third party claims that the service infringes intellectual property or trade secrets. DeepIP may then procure rights, modify or replace the service, or end the agreement and refund unused prepaid fees. Liability is capped at the fees paid in the prior 12 months, with confidentiality, intellectual property and indemnity claims outside the cap and consequential damages excluded. DeepIP warrants cyber liability and errors and omissions insurance of at least $5,000,000 per occurrence. The terms disclaim the accuracy of AI output and leave its review to the customer, and free trials carry a $1,000 cap.

ipQuants publishes a real position, with an indemnity from the vendor and a low cap. Section 11.2 commits ipQuants to defend and indemnify the customer against third party claims that authorized use of the platform infringes intellectual property rights, covering damages and costs finally awarded by a US or European court. Its remedies are procuring the right to continue, modifying the platform, or ending use with a prorated refund. Named exceptions cover customer alteration, unauthorized combination, use in an unauthorized region and claims arising from customer content. That indemnity is the customer's exclusive remedy for infringement. Section 12.1.1 commits to 99 percent uptime, and section 12.2 offers dedicated SLAs to enterprise customers. Against that, section 13 provides the platform as is, disclaiming all implied warranties including accuracy. Section 14 caps cumulative liability at the lesser of five thousand euros or twelve months of fees, expressly including claims about generative AI output. There is no warranty on output, no insurance position, and no indemnity for the accuracy of what the models produce.

Microsoft Word is where DeepIP runs, so drafting, review, office action, freedom to operate and invalidity work happen in the document with comments and tracked changes. DeepIP integrates with docketing and IP management systems and offers a REST API for custom integrations. The prosecution module retrieves USPTO and EPO file documents in one click and indexes them with OCR. No docketing or IP management system is named, and what moves between DeepIP and those systems is not described. DeepIP reports 20 percent higher adoption and 40 percent higher usage for its embedded approach than for standalone tools.

One documented connection into a system a firm may already run, and no documentation an implementer could use. Questel integrates Qthena into its own IP management platform, and both companies have published the arrangement, so a firm already on Questel can reach the product there. Otherwise the platform is reached at its own application domain, and the terms allow authorized distributors to market and provide access. Everything a practice would need to plan a deployment is absent. No document management integration is named, so nothing addresses iManage or NetDocuments. Nothing addresses Word, Outlook or an IP docketing system, no API or developer documentation is published, and nothing describes what data moves, in which direction or on what trigger. The terms restrict automated access, prohibiting robots, AI agents and crawlers from the platform or its content, which bears on programmatic integration. The navigation also has feature pages for workflow automation and collaboration.

SaaS is the default for DeepIP, with an on premises data deployment available through the order form. Customer data is stored and processed only in the territories the order form names, and does not leave them without the customer's written consent. Its cloud hosts, Microsoft Azure and Google Cloud Platform, and its model provider, OpenAI, each run in the United States or the EU. Schwegman, Lundberg & Woessner chose DeepIP after a security review of its Azure deployment in the United States. No architecture or support terms are published for the on premises option.

Cloud delivery is clear, and neither tenancy nor region is stated. The terms define the platform as a suite of online applications at a named application domain and its subdomains, and no on premises or self hosted option is offered. Nothing states whether the platform is single or multi tenant, and no dedicated or isolated option appears. No region is named for storing or processing customer content, and no residency commitment is published, though the named LLM providers operate across multiple regions. The only geographic facts published are corporate and contractual: a Schaffhausen address, Swiss governing law, mediation seated in Schaffhausen and fees in euros. None of them locates the data. An Information Security Policy and a data processing addendum, which would normally cover tenancy and residency, are linked in the footer.

ISO 27001:2022, SOC 2, ISO/IEC 42001:2023 and GDPR all appear on the trust center. It offers the 2026 ISO 27001 and ISO 42001 certificates, the 2026 SOC 2 Type 2 report and a penetration test through an access request, and shows an engagement letter openly. Its control list covers production access, multifactor authentication, network segmentation, firewall review, background checks and tested continuity plans. DeepIP's security program follows NIST 800-53 Moderate and the NIST Cybersecurity Framework, with outside penetration tests and vulnerability assessments. Auditor names and examination periods sit inside the reports, which open after the access request.

No independent security attestation is published: no SOC 2 report of either type, ISO 27001 or ISO 42001 certificate, penetration test summary, named auditor, examination period or certification claim, and no trust center. ipQuants publishes an Information Security Policy as a footer link that needs no login, which is a policy it publishes itself, not an independent examination. Nothing on the site claims an audit, so there is no unsupported badge and no attestation either.

DeepIP uses an OpenAI model hosted on Microsoft Azure, sends no data to OpenAI's own infrastructure, and has Microsoft's abuse monitoring switched off under its Azure agreement. Its terms name OpenAI, Azure OpenAI, Google Cloud Vertex AI, Amazon Bedrock and Azure AI Foundry among the providers it may use. Each must contractually bar training on customer data and keep that data confidential. OpenAI, the language model provider, runs in the United States or the EU. No model or version is named for any module, and the terms commit to no notice when providers change.

The providers and models are named, and notice of change is expressly reserved. The agreement itself names the LLM API providers as OpenAI, Microsoft Azure OpenAI and Google Gemini, and describes paid enterprise API access with anonymized transmission and no training on customer content. Public material names specific models: the company says it defaulted to GPT-4o and has defaulted to Gemini 2.5 since January 2025, and expects to move again as newer models arrive. Notice of change is what fails, and deliberately. The same statement says the product is not tied to one model and the company can switch at any time, so a customer has no committed notice before the model reading its patent documents changes. Two limits apply. The model names sit in a blog post dated November 2025, not on a maintained model page, so whether they are still current is not clear. And no provider is named for hosting or infrastructure outside the model layer.

Subscriptions are sold by the seat, on monthly or annual terms that renew automatically, and the terms put the fee on the subscription page or an order form. A self service trial opens with a card on file and no charge before it ends. Price rises at renewal need 45 days' notice on annual plans and 20 days on monthly ones, and prepaid fees are not refunded on early exit. No seat price, tier or volume rate is published.

The commercial structure is published in detail, and there is no figure anywhere. There is no pricing page and every route to a number is a demo request, but the terms set out the shape of the deal. Subscriptions are per user, and one subscription covers one named user and may not be shared. Billing is annual in advance in euros, invoices are due in fourteen days, and fees cannot be canceled or refunded. The subscription renews automatically unless canceled with sixty days' written notice, and the number of user subscriptions cannot be reduced during a term. Overdue amounts accrue interest at one percent per month, and taxes are excluded. Section 6 adds that accessible reports and downloads are limited by subscription tier and fair use, with limits that can change without notice. The unit, term, currency and commitment are public; tier names and every rate are not.

DeepIP serves law firms and in house patent teams, and limits trials and demos to practitioners who draft and prosecute patents; inventors are not offered access. It shapes drafts to the formal rules of the USPTO, EPO, CIPO, CNIPA, DPMA, INPI, IPO, JPO, KIPO and UKIPO, and to PCT filings. Modules run from invention disclosure and patentability through drafting, drawings, review and office actions to freedom to operate, invalidity and portfolio work. Chemistry and life sciences drafting handles Markush structures, stereochemistry, experimental data and ST.26 sequence listings, with further pages for mechanical, ICT and biology work. DeepIP reports more than 500 law firms and in house teams as customers, across 25 jurisdictions.

ipQuants publishes five named use cases: patent workflows, research and science workflows, technology and IP strategy, legal marketing and business development, and remote work. It names corporate IP teams and law firms as users. Patent coverage is specific by jurisdiction, with skills built around EPO and USPTO examination and analytics covering patent offices in Europe, the United States and Germany. It also offers examiner and opposition and appeal member insights, which exist only where the underlying decision data does. Nothing states which jurisdictions are not covered, no firm size is addressed, and nothing says whether trademark, design or litigation work is in or out. The marketing and business development use case sits beside the patent depth without any statement of how far it extends.