Juristat vs Triangle IP: how they compare in 2026
Juristat and Triangle IP both turn public USPTO prosecution data into analytics on examiners, art units, cost and outside counsel, with AI layered on top. Juristat serves patent firms and corporate IP teams with prosecution strategy and office action tools, while Triangle IP runs an invention pipeline and predicts art units from draft claims. Juristat's lead is evidence and connection. Named people at firms such as Harness IP and Sterne Kessler describe their use, one reporting thirty to sixty minutes saved per case. Its Data Layer feeds firms' own AI through Model Context Protocol. Triangle IP's lead is openness about price and data. It charges a flat $50 a month per organization, sells its predictor alone for $5, keeps a free tier, and says submitted invention text is discarded once a prediction is made. The agreement governing each product sits in separate terms.
Which one fits
Choose Juristat if
- You want examiner and prosecution analytics with named peers behind them. Juristat analyzes more than ten million USPTO applications for examiner behavior, cost forecasting, appeals and outside counsel scorecards, and names people at Harness IP, Sterne Kessler, Orrick and Barnes & Thornburg describing their use.
- You want to feed prosecution data into your own AI. Juristat's Data Layer supplies its structured patent data to a firm's AI systems through Model Context Protocol, and Sterne Kessler's technology leaders are quoted on using it in their stack.
- You want office action and IDS work supported. Juristat's Office Action Strategy Briefs and OAR prepare responses for the practitioner, and its IDS product generates and audits information disclosure statements by traversing patent family trees.
Choose Triangle IP if
- You want to price the whole tool before a demo. Triangle IP charges $50 a month or $500 a year flat per organization with no per user fees, sells its Predictor alone for $5 a month, and keeps a free tier capped at 25 active cases.
- You want to know where a draft is likely to be examined. Triangle IP's Predictor reads an invention summary or draft, returns ranked art units and CPC codes with confidence levels mapped to historical allowance rates, and discards the text once the prediction is generated.
- You run an invention pipeline across divisions. Triangle IP's TIP Tool captures and scores disclosures on a board, tracks applications with USPTO status updates and prosecution timelines, and keeps each portfolio isolated with its own users and permissions.
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 analytics dashboards, examiner statistics, cost forecasts and appeals benchmarks are computed from USPTO data, and Juristat has sold them for more than a decade. AI-Powered Insight, the AI in OAR and IDS, and the Data Layer for customers' own AI sit on top of that analytics platform.
The models drive one real capability inside a workflow product that would run without them. Without machine learning, the TIP Tool is still a working board where invention disclosures are captured, scored, merged and moved through stages, with portfolio views, family trees, prosecution timelines, status updates and export. The models power the Predictor, which analyzes claim language against public USPTO prosecution data and returns ranked art units and CPC codes. It is not a minor attachment either: it is sold as a product at five dollars a month, sits in the main navigation, and feeds the patentability score the platform uses to rank ideas. The examiner and counsel analytics beside it are statistics drawn from USPTO records, not model output.
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.
Answers come quantified and backed by sources instead of guesses, from an AI built for patent work, grounded in Juristat's USPTO dataset and trained on live USPTO data. The underlying dataset is stated at more than ten million applications and 12.7 billion data points. No accuracy figure, test set or evaluation for the AI answers is published. The citations are to USPTO records, not case law.
The Predictor is never validated in public, though what it shows the user is substantial. Each prediction comes with a confidence level and its historical allowance rate, and the source is named as the USPTO's public prosecution data. No accuracy figure, test set or error rate is published, and nothing says how often a predicted art unit turns out to be the assigned one. The nearest statement is a case study claiming a 30 percent rise in allowance rate at an unnamed company.
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.
Administrators manage roles, thresholds and alert policies so teams and outside counsel follow the same playbook, and users can set rules and alerts to enforce prosecution policy. The platform returns exportable briefs and dashboards rather than filed documents. OAR prepares office action responses for the practitioner, and the IDS product gathers and generates statements for review. No threshold at which any output is acted on without a practitioner, and no route back after a wrong answer beyond the user's review, is published.
The product advises and the person decides, and almost none of that is written down. The machine does not act: it returns predicted art units, codes, confidence levels and allowance rates, and a person chooses whether to amend the claims. Nothing published describes that division, a threshold below which a prediction should not be relied on, a review point between a prediction and a drafting decision, or what happens when a prediction proves wrong. Permissions by portfolio govern who sees a case, not who checks the model. The closest published limit is a scope statement about a different feature: the tool is not a substitute for an attorney's formal docketing system.
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.
The pricing page attributes quotes by name and title. Ray Millien, chief executive of Harness IP, states thirty to sixty minutes saved on average per case with Juristat OAR. A patent attorney states three new applications cover the cost of Juristat, and Sterne Kessler's chief information officer states a partnership of more than five years. Orrick, Quarles, Polsinelli, Lewis Rice, McDonnell Boehnen Hulbert & Berghoff and Barnes & Thornburg are quoted by named people. The vendor's own figures, a sixty percent return on OAR in the first year, a 32 percent IDS cost reduction and ten to twenty percent annual cost reduction, are unattributed. No figure carries a date or method.
One figure and one anonymous customer are published, with no method. A case study is headed as a 30 percent increase in patent allowance rates for a leading global tech company. It describes a firm that could not tell which innovations to back, used examiner allowance rates and typical rounds of prosecution to forecast cost and difficulty, and questioned whether its counsel had the right record in the relevant art unit. It does not give the company, period, portfolio size, baseline, or how the increase was measured. No customer is named anywhere else on the site: there are no logos, named references or dated deployments, and the reviews the vendor points to sit on a third party software directory.
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 analytics and solutions pages state industry best security standards, constant monitoring and clear privacy practices, and the AI-Powered Insight page describes role and threshold administration. The Terms of Use and a Secureframe trust center are linked from the footer. Nothing on the product pages addresses training use, retention, privilege or work product, or names the model providers. Much of the product's input is public USPTO data, but OAR and IDS handle the customer's own prosecution files.
For the Predictor, invention text is used only while the prediction runs and then discarded, not stored or reused. Around it sit general assurances on encryption, US hosting, access by role and portfolio isolation. The product terms and privacy policy sit behind the login. The published agreement governs the website only and treats material posted through its interactive features as nonconfidential.
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.
No advice line or supervision statement appears on Juristat's product pages. The product is sold to patent attorneys and agents and to corporate IP teams, and the AI-Powered Insight page frames outputs as answers and briefs for practitioners. No jurisdiction limit beyond the USPTO scope is named.
The Terms of Use say the information on the site is for general information only, that the vendor does not warrant its accuracy, completeness or usefulness, and that reliance is at the user's own risk. Nothing says the output is not legal advice or addresses an attorney client relationship. Nothing addresses the supervision question the product raises: a prediction about art unit assignment is used to reshape claim language before filing. Patent practitioners and enterprise IP teams are addressed directly, and so are individual inventors and startups.
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.
Juristat publishes material on evaluating AI tools and on separating hype from practical reality, and states its AI is built for IP and grounded in trusted data. No responsible AI framework, ISO 42001 or equivalent, testing results before release, accountable owner, or statement about uneven output across art units or examiners is published.
No governance position is published about the model. Nobody is named as accountable for it, nothing describes what is tested before a change to the Predictor ships, no retraining cadence or data cutoff is stated, and no principles page exists. The bias question is concrete here. The model learns from historical USPTO assignment and allowance patterns, it is sold on the point that some art units grant at 1 percent and others at 98, and its stated purpose is to steer applications toward the favorable ones. Whether its predictions hold evenly across technology areas, applicant sizes or drafting styles, and what happens when historical patterns encode something a user would not want to optimize toward, is not addressed. The Predictor page, FAQ, help center, Terms of Use and footer were checked.
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.
Roles, thresholds and alerts are administered by the customer, and Juristat states industry best security standards and constant monitoring. No retention period, deletion commitment, subprocessor list or incident notification practice is published. A Secureframe trust center, a privacy policy and Terms of Use are linked from the footer.
Submitted text is addressed specifically, and the rest is generic. The Predictor discards invention text once a prediction is generated. Encryption, US hosting and access control by role are stated, along with secure document exchange inside the platform to keep drafts out of email. No retention period for anything held in the platform, subprocessor list, or incident response or breach notification practice is published, and the privacy policy that governs the product sits behind the login. Deletion runs the other way, and the vendor says so: patent applications cannot be permanently deleted, only archived, and archived records stay in the system with their linked ideas, tags and analytics.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
No liability position is published on Juristat's product or pricing pages. A Terms of Use is linked from the site footer. Pricing is by custom quote under an order the vendor does not publish.
Liability is handled by a website disclaimer, and the document that would govern the product cannot be read. The published Terms of Use exclude damages of any kind under any legal theory arising from use of or inability to use the site, direct and indirect alike, except for the vendor's gross negligence or willful misconduct. Everything is supplied as is with all warranties disclaimed, and indemnity runs one way, from the user to the company. Arbitration is available at the company's sole discretion, so it is optional for one side only, under Colorado law and in Colorado courts. Nothing addresses the loss this product could cause, claim language reshaped toward an art unit on a prediction that proves wrong. No indemnity, warranty, service credit, insurance or service level commitment is offered.
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.
The Data Layer offers Model Context Protocol access so a firm's own AI systems can draw on Juristat's structured patent data, with Sterne Kessler's chief information officer and chief operating officer quoted on its use in their AI stack. The AI-Powered Insight page states the product complements rather than replaces the system of record with analytics, AI answers, dashboards and exportable briefs. The workflow automation FAQ describes IDS output delivered to a designated inbox and OAR working without logging into new tools. No docketing or document management integration is named with what syncs in which direction.
Real mechanisms are described, and no named system. A law firm or docketing system can send weekly asset reports or data feeds by email for processing, the vendor's team helps with manual imports at onboarding, and portfolios export to spreadsheet. USPTO status is pulled weekly by default, or daily where outside counsel grants access to a dedicated USPTO customer number through an attorney sponsorship arrangement. Single sign on is supported, and deep links let a case be dropped into an email or chat. The vendor says it deliberately avoids Outlook, Adobe and DocuSign integrations to move teams away from email workflows. No document management, matter management, billing or electronic signature system is named as a connection, and no API 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.
Juristat is a SaaS platform with a hosted application. No hosting provider, region, residency option or tenancy model is stated.
The region is stated and the tenancy is not. The vendor says data sits on secure cloud hosting on servers in the United States, and the Terms of Use state that the owner is based in Colorado and the site is for use only by persons located in the United States. No statement covers how customers are separated from one another: shared or dedicated infrastructure, a private option, a region choice for buyers with data elsewhere, or a cloud provider. Separation is described only inside an account, by portfolio. No processing location is stated for the prediction models as distinct from storage.
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.
The footer's Privacy and Security link resolves to a trust center hosted on Secureframe, and the analytics page states industry best security standards and constant monitoring. No standard, auditor, coverage period or access tier is named on Juristat's own pages.
No independent security attestation is published, and none is claimed. There is no security page or trust center, no SOC 2, ISO or penetration test reference on any page including the Terms of Use, and nothing offered on request. The strongest published phrase is encryption described as enterprise grade, which describes practice rather than anything a third party has examined. The navigation and footer were read to the end, and one search for an attestation returned nothing from the site. This records what is published, not a finding about the vendor's actual security.
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.
The AI is built for IP, trained on live USPTO data and grounded in Juristat's dataset, and the Data Layer supplies structured data to customers' own models. No provider, model, inference location or commitment to notify customers of changes is named.
The training data is named, and the model is not. The vendor says its predictions come from its own machine learning models trained on the USPTO's public prosecution data, comparing claim language against public patent records to produce ranked art units and codes with confidence levels. Nothing on the site depends on an outside large language model, so questions about a third party model provider do not arise. Not published: architecture, model version, the date of the training data or how often the model is retrained, where inference runs, or any commitment to tell customers when the model changes.
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.
Juristat's pricing page offers a customized estimate through a four question request. It describes a Solo tier for a single practitioner at one price, with analytics and Data Layer MCP access, and frames value as ten to twenty percent of IP costs saved. The Solo tier has its own page on the resources subdomain. No per seat figure or term appears on the pricing page itself.
Pricing can be read in full from the site, as set out in the pricing structure: a flat platform rate per organization, a separate Predictor rate, a free plan that never expires and a trial that needs no card. Only a custom plan for extra portfolios is quoted on request. Implementation costs nothing extra for annual subscribers.
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.
Role pages address general counsel and heads of IP, patent attorneys and agents, legal operations, IP strategists, corporate finance and IP law firms. Use cases span forecasting, portfolio management, prosecution strategy, cost savings, competitive intelligence, outside counsel management, business development and workflow automation. The data is stated as the complete USPTO dataset, more than twenty years of patent data and a hundred million applications tracked. The USPTO scope is the stated limit, and no foreign office coverage is claimed.
Four customer segments have their own pages, and the functional limits are stated directly. The segments are startups, enterprise, individual inventors and patent practitioners, and the product is built for the corporate side of patent work: inventors, product and engineering teams, company IP staff and the outside counsel they invite in. Coverage is US patent prosecution. International filings can be cataloged, tagged and tracked, but allowance rate prediction and examiner analytics cover the US only. Cost analysis does not work for foreign filings at all, and the vendor calls this a gap across the industry and says it does not oversell capabilities it cannot deliver accurately. Firm size and type on the practitioner side are not described, and government or university technology transfer use is not addressed.
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?
No published material addresses whether customer content trains models. The AI-Powered Insight page states the AI is trained on live USPTO data, which is public record, not customer content. The Terms of Use and the Secureframe trust center, both linked from the footer, were not available to read.
No agreement governing the product could be read, so no training position can be established. The Terms of Use on the website, last modified 11 July 2021, govern the website by their own words, permit personal noncommercial use only, and name two further documents as part of the agreement: a Privacy Policy at an address behind the application login, and an End User License Agreement that is not published anywhere. Neither could be reached, and one search returned nothing.
The website terms say nothing about model training. Discarding Predictor text is a retention rule, not a training one. Whether anything held in the wider platform is used to train or improve the models is not addressed on any readable page.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Questions to the AI, generated briefs and uploaded prosecution files are kept for no stated period. The analytics page states clear privacy practices without a period.
For the Predictor, the retention window is zero. The FAQ says the tool does not store, retain or reuse invention text entered or uploaded: content is processed only at the moment of the request to compare against existing records and predict the Group Art Units, and once the prediction is produced the data is discarded and not saved. The rest of the platform keeps everything, since applications can only be archived, not deleted. No retention period is published for anything else, and the privacy policy that would cover it sits behind the login.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Juristat maintains its own permission model. The AI-Powered Insight page states that administrators manage roles, thresholds and alert policies across teams and outside counsel, and custom dashboards are described as unique to an account. Nothing describes how one client's prosecution files are walled from another's within a firm account or how the AI respects those permissions, and no document management system's access model is inherited.
Separation inside an organization is described in real terms. Portfolios are the unit: each runs as a separate world with its own users, cases and settings, so one division cannot see another's data, and a standard plan carries three with custom plans for more. Permissions follow two tiers, an owner or super administrator with rights across every portfolio and portfolio administrators who manage users, cases and settings within their own.
Roles reach the individual: inventors see only applications they are associated with, while managers, administrators and prosecutors can archive more widely. Outside counsel are invited into specific cases rather than given general access. Separation between customers and any conflicts mechanism for screening a named person from a matter are not described.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Customers have no stated right to be told when a third party demands their data. The Terms of Use and privacy policy are linked from the footer.
Disclosure is addressed, and no notice attaches to it. The Terms of Use reserve the right to disclose a user's identity or other information to any third party claiming that posted material violates their rights. They say the vendor will cooperate fully with any law enforcement authority or court order requesting or directing disclosure of the identity or other information of anyone posting material through the site, and ask the user to hold the company harmless for actions taken in such investigations.
Nothing commits to telling the customer that a demand has arrived, waiting before complying, narrowing what is produced, or helping with a protective order. No transparency report is published.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
The AI answers are grounded in Juristat's dataset of USPTO prosecution records, stated as more than ten million pending, abandoned and granted applications, more than twenty years of complete patent data and 12.7 billion data points, trained on live USPTO data. Nothing states the license or public record basis on which the data is obtained, or how often it is refreshed beyond the word live.
The source is named and public. The models are trained on the USPTO's public prosecution data, predictions compare submitted claim language with public patent records, and the analytics beside them, such as examiner allowance rates and office action counts, come from the same source. No licensing basis is stated, which for public prosecution data is unremarkable. Nothing says what period the training data covers, when it was last updated, or how often the models are rebuilt against newer USPTO outcomes.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Subsequent history checks have no place in this product. The product analyzes prosecution records and examiner behavior rather than citing case law, and the appeals module benchmarks outcomes on similar cases rather than reporting treatment. The product has no citator function.
The product cites no authority, so there is nothing for a citator to check. It predicts where an application will be examined and what the historical outcomes look like; no statute, regulation or case appears in its output. How current the model behind a prediction is remains unstated. Checked on 20 September 2026 across the Predictor page, FAQ and help center.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Where the dataset runs out, the AI's behavior is undescribed. The AI-Powered Insight page states answers are quantified and backed by sources rather than guesses, and no abstention path or confidence signal is described.
Uncertainty is shown as a number beside each answer, and nothing describes behavior at the edges. Every CPC prediction comes back in a ranked list with a confidence level, documented as showing how strongly the model links the submitted text to that code, and is plotted against its historical allowance rate. The art unit prediction works the same way, and the vendor notes that a fuller input, such as claims or a strong abstract, tends to give a more reliable result.
No threshold is published below which the tool declines to answer, and nothing says it flags text that is too thin or outside its training, or what a user sees for a technology area with little data. A cap of 10,000 words on input is documented, with excess text silently ignored.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record naming Juristat is on the public record, including the AI Hallucination Cases database maintained by Damien Charlotin. A District of Kansas order to show cause concerning patent counsel's use of unnamed generative AI tools does not name this product, and other sanctions involve general purpose chatbots. Juristat's output cites USPTO records rather than case law.
The AI Hallucination Cases database kept by Damien Charlotin holds no entry naming Triangle IP as the tool used. Triangle IP produces predicted art units, codes and probability analytics rather than legal text or authority.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No published material names an ethics opinion, bar rule or professional responsibility framework. Juristat publishes content for practitioners on evaluating AI tools and on billing with AI, which is commentary rather than guidance on professional duties.
No rule of professional conduct, ethics opinion or bar guidance is named, and professional responsibility is not engaged in general terms either. The product is sold to patent practitioners and individual inventors alike, and its purpose is to influence how claims are drafted before filing. The nearest material is a downloadable guide to hiring a patent attorney, which is practical advice on choosing counsel rather than anything about a practitioner's own duties. The Terms of Use, FAQ, Predictor and About pages and the footer were checked on 20 September 2026.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Law firms are a named buyer segment. Juristat has a resource called Work Smarter, Bill Smarter on how patent teams use AI, claims cost reductions of ten to twenty percent, and quotes named customers on minutes saved per case and price pressure from clients. Nothing on the pricing page or in the resources navigation records AI assisted work per matter or addresses fee disclosure.
The commercial argument is about legal fees, and none of it is about disclosure. A named use case is reducing outside legal fees: the platform forecasts prosecution cost, flags a case running over budget or taking too many rounds, and benchmarks the company's own counsel against examiner data. The vendor also describes an annuity feature it is building as far cheaper than paying through a law firm and an annuity service, though that feature is not yet available.
Nothing addresses whether a practitioner using the Predictor should tell a client that machine prediction shaped the claim strategy, or how work assisted by it should be billed.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
No subprocessor list, model provider list or forwardable disclosure material is published on Juristat's product pages or footer. A Secureframe trust center is linked from the footer.
Little that a diligence checklist asks for is published. There is no subprocessor list, security certification, penetration test reference or data processing addendum, and nothing is available on request. The product privacy policy and end user license agreement are named in the Terms of Use but cannot be reached without an account. What can be read is narrow: the Predictor's discard rule, US hosting, portfolio isolation, and models the vendor built itself on public USPTO data.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
AI answers are stated to be backed by sources in USPTO records, and briefs are exportable, which lets a practitioner show the data behind a strategy. Nothing states that a record of the model used and the practitioner's verification can be exported. The product's outputs inform prosecution strategy rather than court filings.
Disclosing the model's involvement to anyone outside the company is not addressed. No court sits in this product's path, but applications shaped with the Predictor are filed at the USPTO, and whether machine help with claim strategy should be disclosed to the examining office is not raised. Inside the platform a record of sorts exists, since predictions can be rerun and case history cannot be permanently deleted. Nothing describes exporting that trail or marks a claim amendment made on a prediction apart from any other edit, and no format or guidance is offered for any tribunal or agency.
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.
- Good Law Verification
- Bar Guidance Alignment
- Outside Counsel Guideline Readiness
In summary
Juristat
Juristat, from Juristat, Inc. of St. Louis, Missouri, is a patent prosecution analytics and workflow platform built on USPTO data for patent law firms and corporate IP, legal operations and finance teams. It offers examiner analytics, cost forecasting, appeals benchmarking, portfolio management and outside counsel scorecards. An AI Insight feature answers plain language questions with source backed answers, alongside office action and IDS tools and a Data Layer for firms' own AI. According to the AI Legal Index, Juristat states customers among more than a third of the top hundred patent firms. Its terms and the price of its single seat Solo tier sit on separate pages.
Triangle IP
Triangle IP, from Triangle IP, Inc. of Colorado, is a patent pipeline and prosecution analytics platform. Its TIP Tool captures and ranks invention disclosures, tracks applications with USPTO status updates and timelines, and benchmarks examiners and outside counsel. Its Predictor uses the vendor's own models, trained on public USPTO data, to predict art units and CPC codes from draft claims. According to the AI Legal Index, Triangle IP publishes its pricing in full: $50 a month flat per organization, with a free tier. It hosts on US servers and discards Predictor text after each prediction.
Questions buyers ask
Juristat vs Triangle IP: which is better for patent prosecution analytics?
Both build analytics on examiners, art units, cost and outside counsel from public USPTO data. Juristat names firms such as Sterne Kessler as users and connects its data to firms' own AI. Triangle IP publishes its full price and a clear statement on what happens to invention text. Smaller teams that want to price a tool themselves can start with Triangle IP. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
What happens to text entered into Triangle IP's Predictor?
Triangle IP states that the Predictor does not store, retain or reuse invention text entered or uploaded, that content is processed only at the moment of the request, and that it is discarded once the prediction is generated. The wider platform keeps records: patent applications can be archived but not permanently deleted. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
What is Juristat's Data Layer?
It supplies Juristat's structured USPTO prosecution data, drawn from more than ten million applications, to a customer's own AI systems through Model Context Protocol, so a firm's assistants can use examiner and prosecution data directly. Sterne Kessler's chief information officer and chief operating officer are quoted on using it in the firm's AI stack. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
How much do Juristat and Triangle IP cost?
Triangle IP charges $50 a month or $500 a year flat per organization, sells its Predictor alone for $5 a month, and keeps a free tier capped at 25 active cases; more than three portfolios is quoted. Juristat prices enterprise use by custom quote and offers a single seat Solo tier at one price, published on its pricing page. 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. Juristat's terms of use and trust center may answer several of its gaps here. Triangle IP's product terms and privacy policy sit behind its login, and its published website terms treat interactive postings as non confidential. It states that patent applications can only be archived, not deleted. Triangle IP's only case study names no company. Neither vendor reviewed this page.