Tangibly vs Tradespace: how they compare in 2026
Tangibly and Tradespace both help companies manage intellectual property with AI, but they are rarely weighed against each other because they handle opposite forms of protection. Tangibly finds and governs trade secrets a company keeps confidential, while Tradespace captures inventions and runs the patents that publish them. Tradespace publishes how its AI is built. Each customer gets a dedicated model instance with no data passing between them, answers are grounded in retrieved data with citations, and models run on Azure OpenAI in Northern Virginia. It names Georgia Tech, the University of Texas and the FDA among customers. Tangibly's lead is its contract. Its subscription agreement treats customer content as confidential, requires notice before answering a subpoena, caps renewal increases at 7 percent, and indemnifies customers against intellectual property claims over the service.
Which one fits
Choose Tangibly if
- You need to identify and protect trade secrets. Tangibly's AI analyzes a company's patents and internal documents to surface likely trade secrets, links each result to its source, and keeps a registry with owners, review cycles, access controls and acknowledgments.
- You may need to prove reasonable measures in a dispute. Tangibly keeps time stamped records of trade secret assets, access, training and partner agreements, and sells case validation, damages assessments and non recourse litigation funding through a partnership with SIM IP.
- You want confidentiality and notice in the contract. Tangibly's subscription agreement treats customer content as confidential, requires prompt prior notice of any subpoena or regulatory demand, and returns or destroys content on request. It states SOC 2 Type II for security and confidentiality.
Choose Tradespace if
- Your inventors never fill in disclosure forms. Tradespace's Create module turns slide decks, specifications, flow charts and audio into disclosure packages, draws ideas from Slack, Gmail and Notion, and attaches prior art and market assessments before committee review.
- You worry uploaded inventions could count as disclosure. Tradespace gives each customer account its own model instance with no data passing between instances, trains on customer data only on request, and hosts on Azure in Northern Virginia.
- You want patent prosecution at a known cost. Tradespace offers flat fee prosecution through a vetted network of outside firms, prepares a first application at no charge, and runs docketing, annuities and licensing in the same platform.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. 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.
The models drive discovery inside a governance platform that would still work without them. Tangibly's AI analyzes patents and internal documents to surface likely trade secrets, groups them and links each result to its source. The registry, ownership and review cycles, access management, acknowledgments, partner agreement tracking, training and audit records are governance workflow a team could run without the models.
The base is a system of record: docketing, annuity tracking and maintenance cost modeling, portfolio reporting, workflow routing and electronic signature assignments, none of which needs a model. The AI adds disclosure packages generated from decks, specifications, flow charts and audio, invention reports on use cases, prior art and competitive advantage, and patent drafting acquired with Paragon. It also adds a docketing assistant that summarizes office correspondence and suggests responses, and licensing analysis that finds likely licensees and builds claim charts. Tradespace says the AI is built into the architecture rather than added on, and a press announcement describes a secure system of record combined with drafting technology.
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.
Accuracy is asserted, not measured. Discovery results point back to the source documents so a team can check what was flagged and why, but no detection rate, error rate or test is published. Case validation estimates the likelihood of success in a dispute, and nothing published shows how well those predictions have performed.
Asked on its own AI page how it prevents hallucinations, Tradespace states that it uses retrieval augmented generation to limit responses to actual data and provides citations for responses, alongside guardrails intended to keep generated content grounded in fact. The Paragon acquisition announcement describes the drafting technology as offering transparent traceability to source materials so that teams can verify every claim, citation and technical detail. No accuracy figure, benchmark, evaluation or test set is published. The one number attached to output quality comes from a customer rather than the vendor: the Director of IP at UT Austin is quoted saying the platform gets his team 60 to 70 percent of the way there, the equivalent of a first draft. That figure is a testimonial rather than a measurement. The guardrails are described as state of the art without further detail.
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.
Review is asserted, and little mechanism is described. The platform page says AI discovery results are linked to source material so teams can validate what is sensitive and why. No review workflow, approval step, threshold or limit on how AI output may be used is described.
Prosecution work runs through senior attorneys in a vetted network, and the platform page names attorney review and workflow approvals as stages. Inside the product, the customer can build no code rules for disclosure routing and patent committee review, which is a configurable approval path a firm sets for itself. The docketing assistant is described as capturing office and counsel correspondence, summarizing it, creating the resulting deadlines and suggesting responses, so the system generates docket deadlines on matters where a missed date can be malpractice, and nothing published states whether a human confirms a created deadline before it enters the docket. No published material states what any module completes without review, where the checkpoint sits for a customer using the software without the attorney network, or what happens when the system is uncertain. No agreement of any kind is published, so no review obligation appears in any document.
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 customers and endorsements are published, without measured results. The site quotes Mike Renaud, Chair of Mintz's Intellectual Property Division, on the firm's work with Tangibly, and Davis Fundi Ireri, R&D Manager at Sentara Group, on centralizing proprietary innovations, and features an Oxa case study. A quote on case validation is attributed to 'Ray Miller, Partner' with no firm named. Investor quotes from SIM IP and Wipro Ventures are endorsements, not customer evidence. The claim of faster trade secret discovery carries no basis.
Home page logos include Georgia Tech, the University of Texas at Austin, the FDA, Enveda Biosciences, Unity, UNT Health and Raytheon. The security page adds Northrop Grumman, the Department of Defense and the Department of Energy, and says the DoD and DOE were founding customers. Two figures attach to named customers. UNC Charlotte is described as clearing a three year technology backlog and posting 100 new case submissions in a few months. Chun Kuo, Director of Intellectual Property at UT Austin, says the platform gets his team 60 to 70 percent of the way there and that without it he would need budget for more staff. Video case studies exist for Woodward and UNC Charlotte. A company announcement cites more than 440,000 patents managed for over 80 organizations, including 75 percent of top US research universities. Nothing is dated, and no figure carries a method or measurement basis.
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.
The published agreement has a real confidentiality article, and it is silent on AI. Customer Content is treated as the customer's confidential information, to be used only to perform the agreement, with notice before any legal demand and return or destruction on request. Case validation work is done under NDA where appropriate. Which model providers, if any, process customer content is not stated, and privilege is not addressed.
A hub and spoke design gives each customer account a separate model instance, and Tradespace says no data ever moves from a spoke model to the hub or another spoke. It addresses novelty as well as secrecy: uploaded data is not treated as a public disclosure and cannot be discovered by a third party. Training is opt in, off by default and only on explicit request. Model handling is disclosed, with Azure OpenAI Service named and Microsoft's data protection addendum linked. Nothing says how long disclosures, drafts or office correspondence are kept or what happens when a customer leaves. Privilege and work product are not mentioned, although the platform is sold to general counsel, chief legal officers and law firms. There is no published agreement, privacy policy or data processing addendum to hold any of these commitments.
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.
A short disclaimer sits against marketing that reads like advice. The Master Subscription Agreement says Tangibly is not engaged in providing legal advice, and the case validation FAQ says it complements counsel rather than replacing attorneys. The consulting service, however, is marketed as expert legal guidance, and case validation offers general counsel and CEOs an estimate of their likelihood of success. Nothing addresses who reviews those assessments or the supervision duties of the lawyers who rely on them.
Nothing published addresses professional responsibility. The home page, platform overview, Create, Manage, Enterprise AI and Security and Privacy pages, the counsel network page and the footer carry no statement that output is not legal advice, nothing on who may use the platform or under what supervision, no reference to verification duties and no jurisdiction statement. There are no terms of service or privacy policy where such a statement could sit. Tradespace markets a full service patent practice combining software with patent attorneys from a network of outside firms. Nothing says who the client is, whether an attorney client relationship arises with Tradespace or only with the network firm, how conflicts are cleared across firms serving competing portfolios, or who bears the duty of candor on a filing the platform helped draft.
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 or testing before release is published, and nothing reports how discovery or outcome predictions perform across industries, document types or case profiles. Checks covered the site and both legal documents.
No governance material is published on the home page, platform overview, Create, Manage, Enterprise AI and Security and Privacy pages or in the footer. There is no responsible AI page, framework or set of principles, no person or function accountable for model behavior, no account of what is tested before a model or module change ships, and no certification such as ISO 42001. The closest statement is a claim that the AI has state of the art guardrails to keep generated content grounded in fact, which names no guardrail and describes no testing. SOC 2 Type 2 through Vanta is an information security attestation, not AI governance. Nothing addresses uneven output, though the disclosure module scores inventions and the licensing module ranks assets, and both shape which inventions get filed and which patents get licensed.
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.
Security controls are published, and retention, subprocessors and incidents are not. The security page describes AWS hosting, encryption in transit and at rest with keys in AWS Key Management Service, optional multifactor authentication and security training, and the platform offers SSO and audit logs. No subprocessor list, retention period for uploaded documents or incident notification commitment is published.
Tradespace publishes AES 256 encryption of all data at rest; single sign on through Okta, Microsoft and Google, with others on request; SOC 2 Type 2 maintained through Vanta with a linked trust center; hosting on Microsoft Azure with all servers in the US Northern Virginia region; and a dedicated model instance for each account. No retention period or deletion practice is stated for any data. No subprocessor list exists; Microsoft is identifiable as the cloud and model route and no other processor is named. No incident or breach notification practice is published. Tradespace publishes no terms of service, privacy policy or data processing addendum, the documents where retention, subprocessors and breach notice usually sit.
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.
Liability is handled through a standard limitation clause. The Master Subscription Agreement caps each party's liability at the fees paid in the prior twelve months, or $1,000 if none, and excludes indirect damages. It warrants that the service performs substantially as documented, and indemnifies the customer against US patent, trademark and copyright claims and claims that Tangibly misappropriated trade secrets in building the service. Nothing addresses discovery results or case assessments that prove wrong.
Nothing published says who bears the loss when output is wrong, because no agreement of any kind is published. The footer has no legal section: no terms of service, privacy policy, acceptable use policy or data processing addendum. No liability cap, indemnity, warranty, service level or insurance position is published. The one commercial promise is about satisfaction, not liability: on a first filing, if the customer is not happy, Tradespace will not file and the materials are the customer's regardless. The platform holds unfiled invention disclosures for defense contractors, federal agencies and research universities.
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.
Integrations appear as logos, not documentation. The trade secret platform page shows a row of integration logos, one of them Microsoft Azure, and answers the question of which integrations are supported by inviting buyers to meet its experts. What connects, in which direction and with what configuration is not described.
The named connections point at the systems inventors use rather than those lawyers use. Tradespace names Slack, Gmail and Notion as sources it mines for ideas, and describes capture from pull requests, call recordings, schematics and design documents. For enterprises, the platform states support for integrations with CRM, CLM, ERP and other IP systems through APIs and connectors, with secure two way data exchange, naming the direction of flow. The Manage module describes integrations with annuity providers and with patent offices that capture maintenance events, deadlines and correspondence automatically. Single sign on runs through Okta, Microsoft and Google. No connector list, named IP management or docketing system, API reference or developer documentation is published.
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.
Cloud hosting and tenant isolation are stated, and no storage region is. The security page says the platform runs on Amazon Web Services, with each customer's data kept separate through tenant isolation. The Master Subscription Agreement notes only that content may leave the United States if a user accesses it from abroad. No region choice or other deployment option is described.
Each customer account gets a dedicated model instance in a hub and spoke design, with no data moving between instances, and Tradespace ties private instances to avoiding public disclosure, the specific legal risk in patent work. Hosting is Microsoft Azure, with all servers stated to be in the US Northern Virginia region. There is no choice of location. No other region, European option, on premises or customer cloud deployment is offered, so a customer with residency obligations outside the United States has no published path. Nothing separates processing location from storage. Customers include research universities and multinationals filing in Europe and Asia.
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.
A named attestation with scope is claimed, without a report route. The security page says Tangibly is SOC 2 Type II compliant for the Security and Confidentiality criteria, and that the platform undergoes routine internal assessments and independent audits by outside firms. No auditor, report date or way to obtain the report is published, and there is a security disclosure form for reporting vulnerabilities.
Tradespace says it works with Vanta to maintain SOC 2 Type 2 compliance and links directly to a trust center, a route to controls rather than a badge. Security is described in specifics elsewhere: AES 256 at rest, named single sign on providers and a stated server region. The company says it meets these standards for clients including Northrop Grumman, Raytheon, the Department of Defense and the Department of Energy. No auditor is named; Vanta automates compliance and is not the auditor. No report date, coverage period, scope or trust services criteria are published, and the access level for the report is not stated. No penetration testing program is described.
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.
Proprietary AI is claimed without saying what sits underneath. Case validation is described as using proprietary AI, and discovery as AI built for the purpose; no model, model provider, hosting location for inference or change notification is published.
The provider is named and the models are not. Asked which models it uses, Tradespace describes a model agnostic approach and says that by default it uses Microsoft Azure to access OpenAI Services, linking to Microsoft's published data privacy terms for that service. That tells a reader whose infrastructure and model family sit underneath and points at the applicable data protection terms. Inference runs on Azure with servers in the US Northern Virginia region, and the hub and spoke design means the instance is dedicated rather than shared. No model or version is named, the model agnostic claim comes with no list of alternatives, and there is no commitment to notify customers when the model or provider changes, which matters because the architecture is built to make swapping models easy.
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.
The unit and structure of charging are in the published agreement, and no figure is. The subscription agreement sets a per user charge by default, annual billing in advance, a fee lock for the first term and a cap on renewal increases, as recorded in the pricing structure. No price, tier or minimum appears anywhere, and every route to a figure is a conversation with the team.
The charging model is stated with no number attached. Prosecution is sold for a flat fee, with the vendor saying the customer knows the cost before work begins, and the pitch is framed against hourly outside counsel, law firm markups and paying hundreds an hour for correspondence handling. There is a concrete free offer: Tradespace prepares a full first application at no cost and, if the customer is not happy, will not file, with the materials theirs regardless. An ROI calculator lets a customer model returns on its own portfolio. No figure, tier, seat price, subscription rate or unit is published for the software, and nothing says how the platform license relates to the flat prosecution fee or whether one can be bought without the other. The only route to a price is a demo request.
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.
A single practice area is covered and its buyers are named, without limits. The site is built around trade secrets, from identification and governance of reasonable measures to partner sharing and dispute preparation. It addresses corporate legal and IP teams, operational teams such as R&D, and law firms, with industry material on chemicals, medical devices and semiconductors. The jurisdictions and dispute types it does and does not support are not stated.
Six buyer roles have their own pages: IP leaders, tech transfer leaders, general counsel, chief legal officers, R&D leaders and corporate development. Five industries have pages: corporations, startups, universities, government and law firms, and four use cases are documented separately. The customer list spans a federal agency, defense primes, research universities and startups. Law firms appear as buyers alongside in house teams, although the product is also marketed as an alternative to outside counsel. No jurisdiction is stated, so nothing says whether the drafting and docketing modules handle European or international filings or only US practice, with a single US hosting region. No portfolio size is given, and trademarks and copyright are absent throughout without being excluded.
The 12 legal signals, side by side
Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
The Master Subscription Agreement and the Privacy Policy are published and neither says whether customer content is used to train Tangibly's models. The agreement grants Tangibly a right to use Customer Metadata, which it defines to exclude the content itself, to operate, improve and develop the service; that improvement right never names training. No page addresses training either way.
Training is opt in rather than prohibited, and the vendor says so. Asked on its AI page whether it trains on customer data, Tradespace says it does not by default and adds the quoted sentence, so training happens only at the customer's request. The security page says data is never used for training without written consent, which adds a written form to the mechanism. A third statement goes further: asked whether using the platform is a public disclosure, the vendor says flatly that customer data does not train any model, without the consent qualifier.
Read together, the position is opt in with written consent, and the flat sentence describes the default rather than adding a prohibition. No agreement, privacy policy or data processing addendum is published, so none of this is a contract term and nothing defines the consent mechanism.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The Privacy Policy keeps personal data as long as necessary to deliver the service and meet legal and business needs, with no period stated. The Master Subscription Agreement makes stored content available for retrieval for 30 days after an order ends and requires return or destruction of confidential information on request, subject to backups kept under normal policy.
Disclosures, drafts, prompts and portfolio records have no retention position of any kind. No period is stated for disclosures, generated drafts, prompts, office correspondence or portfolio records, nothing describes what happens to data when a customer stops using the platform, and no deletion route or export right is published. No retention setting is offered. Tradespace publishes no terms of service, no privacy policy and no data processing addendum, so the documents in which a retention position normally lives do not exist on the site.
What is published nearby concerns isolation rather than duration, with each account given a dedicated model instance and no data moving between instances, which addresses who can reach the data rather than how long it is kept.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Access is set in Tangibly's own permission model, maintained by the customer's administrators. Permissions by role limit users to what their responsibilities require, access to individual sensitive assets is managed, and acknowledgments are captured when confidential information is shared. Tenant isolation separates each customer's data. Nothing describes inheriting permissions from a document management system.
Asked how it keeps account data sent to AI models from being mixed, Tradespace describes a hub and spoke approach that provisions a separate instance of its hub model for each customer account, with the quoted result. It says no data is ever transferred from a spoke model to the hub or to any other spoke, so the flow of data is stated in both directions. The security page frames the same design against the key risk in patent work: with a private model per customer, uploaded data is not treated as a public disclosure.
The separation is between customer accounts, and nothing covers separation between matters or clients inside one account. None of it appears in an agreement, since none is published.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Prompt prior notice of any subpoena, order, investigative demand or regulatory request for customer content is committed in the Master Subscription Agreement, where legally permitted. Tangibly adds reasonable assistance, at the customer's expense, if the customer seeks protection. No transparency report is published.
Disclosure to authorities or in response to legal process, and notice to the customer if a demand arrives, go unaddressed for a platform whose customers include three federal agencies. No terms of service, privacy policy or data processing addendum is published. The closest statement is that customer data is not publicly disclosed or discoverable by a third party, which concerns the architecture, not compelled disclosure.
Customers include the Department of Defense, the Department of Energy, the FDA and defense contractors, where government demands for records are foreseeable.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Case validation is said to use AI trained on trusted legal data and to compare a dispute with thousands of relevant sources, and those sources are not identified. The site's main pages were checked on 22 September 2026.
Tradespace states that its AI tools were trained on knowledge gathered from millions of publications, patents, product specs, licenses, and search reports. Two of those categories are public records in most jurisdictions, and three are not: product specifications, license agreements and search reports are ordinarily confidential or commercially licensed material, and nothing published states where they came from, on what basis they were obtained, or whether any of it originated with customers.
Tradespace separately states that it does not train on customer or account data without explicit request, and nothing reconciles the two. No database, publisher, patent office or data supplier is named, no jurisdictions are listed, no volume figure is given for any category, and no update cadence is stated. The platform separately consumes live patent office correspondence and prior art in operation, and nothing describes the provenance of that either.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Nothing addresses whether authority relied on in case assessments is checked for later history, as of 22 September 2026.
Whether prior art, patent status and licensable assets surfaced by the platform remain current goes unchecked by any described step. The question takes a particular form in patent work, and none of its forms is addressed: nothing states whether prior art returned in a disclosure evaluation is checked for currency, whether patent status and legal events are validated against office records when the Manage module reports on a portfolio, or whether the licensing module confirms that an asset it recommends for monetization is in force and unencumbered.
The docketing assistant does capture patent office communications and create deadlines from them, which is currency in the procedural sense, but nothing describes verification of what it captured. No treatment, status or validity signal is described.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Nothing describes what discovery or case validation does when the material does not support a conclusion. The main site pages were reviewed for this on 22 September 2026.
When the platform cannot ground an answer, nothing describes what it does next, and the user is shown no confidence, coverage or grounding indicator alongside any of its output. What is published constrains generation rather than describing behavior at its limits. Tradespace says retrieval augmented generation limits responses to actual data, citations are provided, and guardrails keep generated content grounded in fact.
The Create module flags missing information in an inventor's submission, which tells a user the input is incomplete rather than that the model is uncertain about an output.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database kept by Damien Charlotin holds no entry naming Tangibly as the tool used.
The AI Hallucination Cases database maintained by Damien Charlotin, and reporting drawing on it, record no court order, opinion or disciplinary record naming Tradespace, Tradespace, Inc. or the acquired drafting brand Paragon. This is a statement about the public record rather than a finding about the product. The tracker records fabricated citations in court filings, and this platform's outputs are patent applications, office action responses and docket entries filed at patent offices, so the forum that would surface an equivalent failure is the USPTO rather than a court, and its responses take the form of examiner objections, prosecution history consequences or an inequitable conduct allegation raised later in litigation rather than a published sanctions order. None of those is indexed anywhere comparable.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No material engages with lawyers' professional or ethical obligations or names any ethics opinion. The site pages, the agreement and the Privacy Policy were checked on 22 September 2026.
No public material on the home page, platform overview, Create, Manage, Enterprise AI, Security and Privacy and counsel network pages or in the footer engages guidance from any professional body governing the platform's users. Neither the USPTO Rules of Professional Conduct nor its guidance on AI in filings is named, no state bar opinion is cited, and nothing addresses the duty of candor on a patent filing or the competence and supervision duties of a practitioner relying on generated drafts and machine created deadlines.
Tradespace markets a full service patent practice through a network of outside firms and does not say how professional obligations are split between itself, the network firm and the customer.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The platform is a company's own trade secret registry and governance system, bought by its own legal and IP staff for internal work, so it does not sit between a lawyer and a billed client. Law firms appear as users of the separate case validation assessments, and nothing addresses how that work is billed.
Tradespace sells against the billable hour, calls itself an alternative to the law firm markup, tells buyers to stop paying hundreds an hour for outside counsel to summarize correspondence, offers flat fee prosecution with cost known in advance, and publishes an ROI calculator. The Manage module reports outside counsel spend. Nothing addresses how AI assisted work is recorded or disclosed, and no record of AI assisted work by matter is described.
Tradespace mostly sells to the in house or university team that pays the bill, so its flat fee model addresses cost commercially rather than through disclosure. Law firms are a named buyer segment, and nothing addresses billing for them.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
Only AWS is named, as host, on the security page. The agreement, the Privacy Policy and the site pages carry no subprocessor or model provider list and no disclosure material for clients.
Asked which models it uses, Tradespace describes a model agnostic approach that by default uses Microsoft Azure to access OpenAI Services, and links to Microsoft's published data privacy terms for that service. A firm can tell a client which provider processes its content and point to the data protection terms. No subprocessor list exists, no other processor is named, and the model agnostic claim means the named default may not be what a given customer runs.
There is no data processing addendum, privacy policy or terms of service, so there is nothing to forward to a client; the SOC 2 Type 2 report behind the Vanta trust center is the only obtainable document, and its access level is not stated.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
The platform keeps timestamped records of trade secret assets, access and controls to support a party's own case, but nothing addresses recording or disclosing AI use in material put before a court. This reflects the site as read on 22 September 2026.
A patent office or tribunal asking about AI use would find no disclosure support, and no exportable record for each document of which model produced which passage, what was retrieved and who reviewed it is described. The platform holds much of the raw material. Citations accompany generated responses, the Paragon drafting technology is described as traceable to source materials, the docketing assistant captures all office and counsel correspondence for a case, and audit logs are listed among security controls.
None is presented as a record of model use. The duty of candor in patent prosecution attaches to what is submitted, and a platform that drafts applications, suggests office action responses and creates deadlines generates exactly what an inequitable conduct challenge would probe.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.
- AI Governance and Bias Disclosure
- Good Law Verification
- Refusal and Uncertainty Behavior
- Bar Guidance Alignment
- Court Disclosure Support
Product updates
The latest logged changes from each vendor, newest first, each linked to its source.
Tradespace
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Product / capability
Tradespace rebuilt how a technology is prepared for licensing so it no longer needs an invention disclosure: users can upload a document, paste a description, or both.
Source
In summary
Tangibly
Tangibly, from Tangibly, Inc. of Seattle, is a trade secret management platform for corporate legal and IP teams, law firms and the HR, R&D and security teams that handle confidential information. Its AI surfaces likely trade secrets from patents and internal documents. The platform keeps a registry with owners, reviews, access management, acknowledgments, training and time stamped records for disputes, alongside consulting, case validation and litigation funding. According to the AI Legal Index, its published agreement treats customer content as confidential and commits to notice before compelled disclosure, and it states SOC 2 Type II. It charges per user by default, annually in advance.
Tradespace
Tradespace, from Tradespace, Inc. of San Francisco, is an IP management platform running the patent lifecycle from invention capture through drafting, prosecution, docketing, annuities and licensing. It offers flat fee prosecution through a network of outside firms, with drafting technology from its 2025 acquisition of Paragon. According to the AI Legal Index, it gives each customer a dedicated model instance on Azure OpenAI in Northern Virginia, grounds answers with citations and states SOC 2 Type 2. It names Georgia Tech, the University of Texas, the FDA and Raytheon among customers. It prepares a first application free.
Questions buyers ask
Are Tangibly and Tradespace the same kind of product?
No. Tangibly manages trade secrets, which a company protects by keeping confidential, while Tradespace manages inventions and patents, which are protected by publishing them. Both are sold to corporate IP and legal teams and use AI to find what is worth protecting. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
Does Tradespace train AI on customer inventions?
Not by default. Tradespace states that it trains on customer data only if a customer explicitly requests it, and its security page adds that training requires written consent. Each customer account runs on its own model instance with no data moving between instances. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
What does Tangibly's agreement commit to?
Its master subscription agreement treats customer content as confidential information used only to perform the agreement, requires prompt prior notice of any subpoena or regulatory demand where lawful, and returns or destroys content on request. It caps liability at a year's fees, warrants the service performs substantially as documented, and indemnifies customers against certain intellectual property claims. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
How are Tangibly and Tradespace priced?
Tangibly's agreement charges per user by default, annually in advance, with renewal increases capped at 7 percent unless it gives notice. Tradespace sells patent prosecution as a flat fee, prepares a first application free, and offers an ROI calculator. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.
Three points to weigh. Tradespace publishes no terms of service, privacy policy or data processing addendum, so its training, isolation and security statements sit on product pages with no agreement behind them. Tangibly's agreement caps liability at a year's fees and says nothing on whether customer content trains its models. Tangibly's case validation sources are not identified. Neither vendor reviewed this page.