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netLex

netLex is a contract lifecycle platform for company legal teams and the sales, procurement and finance staff working with them. Founded in 2014 in Belo Horizonte, Brazil, it combines document templates, negotiation, approval workflows, signatures, storage and reporting. Its native OpenAI integration drafts or revises clauses from prepared and custom prompts, with administrators controlling activation and reviewers deciding which changes to retain.

The product also describes Creation Agent for converting existing agreements into templates, Review Agent for applying a company's clause playbook, and Management Agent for extracting portfolio information. Newer capabilities are accompanied by a FrontRunners early access program, while an announced MCP connection lacks a separate release confirmation. Salesforce and HubSpot can supply the fields used to generate agreements and display their progress.

netLex serves customers across many countries, with support in Portuguese, English and Spanish. Its public privacy policy prohibits using AI inputs for model training but retains platform backups for five years. Pricing normally follows user numbers and access profiles, with implementation and a defined amount of document automation included. Additional custom work requires a quote.

Capability grades

All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.

BB on AI CentralityThe models are the engine of a core capability, layered on a product that would still function without them as a document or workflow system.

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.

netLex combines a contract lifecycle platform with AI for clause drafting, review, extraction and questions about agreements. Its OpenAI integration lets users simplify, translate or revise clauses with prepared or custom prompts. Review Agent compares incoming contracts with the customer's playbook, while Creation Agent turns an existing document into questionnaire fields and variables. Management Agent extracts dates, parties, amounts and obligations for portfolio monitoring.

Those capabilities sit within a wider system of templates, approvals, negotiation, signatures and storage that can operate without generation. The June 2026 agent announcement also describes an early access program; creating templates from a description alone was still forthcoming.

Source: Vendor Published
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

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.

Review Agent compares clauses with a company playbook and explains departures from its standards. netLex also describes questions about contracts and attachments, including inconsistencies between the main agreement and a commercial appendix. These are useful sources of context, but the product materials do not demonstrate an openable citation for each answer or a method for validating cited legal authorities. No reproducible accuracy test, sample size or breakdown of missed risks is published.

The terms explicitly warn that AI responses may be inaccurate, incomplete or unsuitable. A reviewer therefore has to compare proposed changes with the agreement and applicable law before relying on them.

Source: Vendor Published
BB on Autonomy and Oversight ModelA written commitment that the models work alongside a supervising lawyer, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.

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 must enable the OpenAI functionality before users can access it, and customer policies govern its use. A reviewer can accept, edit or reject suggested wording, with the final contract remaining under human control. netLex describes additional approval steps for important negotiation changes and a Review Agent configured against the customer's clause rules and acceptable limits. Its July 2026 explanation distinguishes automated actions from human decisions in the history.

The precise uncertainty level that stops an agent, mandatory escalation triggers and the procedure for undoing an erroneous downstream action are not published. The terms require users to assess AI results before adopting them.

Source: Vendor Published
BB on Operational and Outcome EvidenceReal deployment evidence with substance, short of full attribution or measurement: a named customer without figures, or figures without the named customer.

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.

Gupy provides a named example of deployment with operational figures. In netLex's September 2026 account, Gupy simplified its commercial amendment language, introduced defined approval responsibilities and connected Salesforce before measuring changes in the first months. Average amendment completion fell from 38 to 25 days, while legal response time fell from 1.58 to 0.31 day. Amendments signed without customer changes increased from 16% to 60%.

The account attributes the improvements to a combined process and integration project, not an isolated AI intervention. Exact observation dates, document counts and an independently reviewed measurement protocol are absent, limiting comparisons with other organizations.

Source: Vendor Published
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

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 privacy policy states that inputs supplied to netLex AI will not train the model, and the product description says drafting and review data are not retained by the AI service. Access controls use roles, corporate authentication and customer permissions. netLex describes agents as unable to reach information beyond the current user's access, with a separate customer environment. Contract storage nevertheless has its own lifecycle: deleted user records can leave name and email history, and backups remain for five years.

The public terms do not directly promise preservation of attorney privilege or explain how model provider access affects work product protection.

Source: Vendor Published
BB on UPL and Professional Responsibility PostureA real position is published on advice versus tooling, short of full treatment: commonly a disclaimer without the supervision and competence dimension, or silence on jurisdiction limits.

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.

netLex is aimed at legal departments and the business teams working with them on company agreements. Its terms require users to assess the relevance, accuracy and suitability of AI results before adopting them for any purpose. They also state that AI cannot replace necessary human, legal, technical or professional analysis. The drafting interface supports this division by leaving acceptance or rejection of suggestions with the user.

However, jurisdictional limits on automated legal opinions and a detailed account of lawyers' competence or supervision duties are not supplied. Corporate staff can initiate contracts and requests without being lawyers, making the configured approval route significant.

Source: Vendor Published
CC on AI Governance and Bias DisclosureResponsible AI principles are published without a mechanism, a testing regime, or anything a buyer could audit.

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.

netLex publishes principles for AI use in contracts: company playbooks, access permissions, traceable decisions and final human approval. It describes logs that distinguish automated decisions from human actions and presents these controls as part of its own design. That establishes an AI governance position, but not a full account of how the vendor tests its models. No named owner for model risk, release evaluation protocol, bias assessment across languages or results across contract types are supplied.

The Information Security and Compliance Committee oversees security and privacy; its existence alone does not show accountability for uneven legal output or model behavior.

Source: Vendor Published
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

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.

The privacy policy separates user data, customer agreements and AI inputs, and names the purposes for processing them. Users' personal data are deleted when their account or the customer contract ends, with limited identity history retained and backups kept for five years. Customers direct deletion of third party personal data in agreements. At termination, extraction is through REST APIs returning base64 content, so the customer needs its own conversion and storage capability.

Published safeguards include encryption, role permissions, annual external penetration testing and an incident response team. A deadline for notifying customers of a breach and precise AI service retention exceptions are not supplied.

Source: Vendor Published
CC on AI Liability and RecourseLiability is addressed only through a standard limitation clause that disclaims the exposure the product creates.

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.

The August 2025 terms place responsibility for AI results on the user and disclaim accuracy, completeness and suitability. They expressly exclude netLex's liability for decisions, actions and omissions arising from use of AI functionality. Separate provisions also disclaim losses from errors in generated agreements and third party service failures. If netLex is nevertheless held liable, the stated ceiling is the amount the customer paid for the platform during the preceding twelve months.

No published AI output indemnity, professional liability insurance commitment or compensation mechanism for a harmful clause is provided. A negotiated software license may contain additional provisions unavailable in these public user terms.

Source: Vendor Published
AA on Practice Systems Integration DepthDocumented, verifiable integrations into the systems legal work already lives in, with the depth described: what syncs, in which direction, and what a firm must configure.

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.

Salesforce and HubSpot integrations map CRM properties to variables in netLex contract templates. Customer identity, commercial amounts, payment terms, dates and opportunity stage can feed the agreement; the configured stage triggers generation. Contract creation history and the information used remain visible inside the CRM. Legal teams prepare the approved templates and the customer configures the field mapping and trigger.

Gupy describes using this process for commercial amendments. netLex also supplies Slack notifications, directory authentication, signature connections and a REST API, with netLex Connect supporting custom input and output flows. Its announced MCP interface still lacks a separate public release confirmation.

Source: Vendor Published
BB on Deployment Model and Data ResidencyDeployment model is stated clearly with partial residency detail, or residency is offered without the processing location being addressed, or the tenancy model is stated on its own with no residency detail 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.

netLex runs on AWS and lets customers choose storage in the United States, Europe or South America. The privacy policy identifies the United States, Ireland and Brazil as contractual locations for storage or processing. It separately permits subcontracting and sharing with providers in other countries, including the United States. A selected repository region therefore does not establish that every AI request stays there.

Backups are geographically distributed, without a separate public map of their locations. The native AI integration is with OpenAI, but its processing geography is not tied to each customer region. No customer hosted deployment option is described.

Source: Vendor Published
BB on Security Certifications and Trust CenterCertification is real and stated, short of accessible evidence: a named standard without scope, date, or a way to obtain the report.

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.

netLex states that it holds ISO 27001:2022 certification and obtains SOC 2 Type I and Type II reports through recurring audits. The reports are available by request under a nondisclosure agreement. The public security description also specifies annual external penetration testing, static code analysis, component vulnerability analysis and separation of development, test and production environments. Production data are excluded from development and testing.

These are more specific assurances than an infrastructure badge alone. However, the public text does not identify the SOC auditor, report observation period or exceptions. AWS's separate certifications should not be treated as independent coverage of every netLex AI function.

Source: Vendor Published
BB on Model Supply Chain DisclosureThe supply chain is partly disclosed: providers named without change notification, or architecture described without the providers.

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.

OpenAI is identified as the provider behind netLex's native AI drafting and revision features. The privacy policy explains that the integration uses the OpenAI API, and the published supplier list also names OpenAI API and ChatGPT alongside AWS and other service providers. It does not identify a current model version for each agent or specify how those agents route tasks among models. Nor does it map OpenAI processing to the customer's selected storage region.

Customers receive notice of privacy policy changes, but a distinct commitment to advance notice of model substitutions is absent. Newer agent features therefore need more detailed supply chain terms.

Source: Vendor Published
BB on Commercial TransparencyReal pricing is published for part of the range, with enterprise tiers withheld, or the unit and structure are stated without the figure.

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 monthly subscription normally depends on the number of users and their access profiles. It includes implementation and automation of an agreed number of documents; additional document automation is priced according to project complexity. Native integrations, including electronic signature connections, are included, while integrations needing special configuration receive a separate project price. This explains the charging structure without publishing a per user rate, minimum contract value or an AI consumption allowance.

A quote must distinguish ordinary platform access from any agent entitlement or usage charge. Public materials do not settle renewal increases, termination charges or the total cost of a large migration.

Source: Vendor Published
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

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.

netLex serves company legal, sales, procurement, finance and operations teams through contracts, powers of attorney, legal requests and related corporate records. Named customers include Ambev, Blip and Isaac, with Gupy illustrating commercial amendments generated from a CRM. Its templates and playbooks can cover supply agreements, employment contracts, confidentiality agreements and services contracts. The interface is offered in eleven languages and service is available in Portuguese, English and Spanish.

Use in more than sixty countries describes geographic adoption, not verified legal coverage in each jurisdiction. The product does not publish an exhaustive set of supported laws, exclusions or a separate law firm matter management offering.

Source: Vendor Published
Sources on file

8 public documents

The public pages on file for netLex, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.

Pricing

Custom quote

  • netLex does not publish a price.
  • Your monthly fee normally depends on how many people use it and what access they have.
  • Setup and automation for an agreed number of documents are included.
  • Extra automation and custom connections cost more, and the quote needs to specify AI access.

Monthly subscription normally based on user numbers and access profiles; no public rate or AI allowance.

Implementation: Subscription includes implementation and automation of an agreed number of documents. Additional automation and specially configured integrations are quoted by complexity.

Confidentiality and data terms: Not stated

Note: Native integrations are included. Public materials do not give an AI usage charge, minimum commitment, renewal increase or termination schedule.

Legal Signals

What each signal means

A signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.

Confidentiality and Privilege

Client Data in Training

Can material a lawyer puts into this product be used to train a model?

Never, in policy only

A public policy or trust page states no training on customer content, with no matching term located in the published agreement.

netLex's privacy policy expressly says that data supplied to its AI functionality will not train the model. It identifies the OpenAI API as the integration used for drafting and reviewing clauses. This is a published policy promise, rather than a separately supplied negotiated AI agreement. The prohibition concerns AI inputs; it does not erase ordinary contract storage, user history or the five year backup period. The policy does not provide model specific audit results or an enforcement mechanism against every underlying provider.

Source: Vendor PublishedOs dados fornecidos não serão utilizados para treinar o modelo.As of Oct 16, 2026Evidence

Prompt and Output Retention

How long does the product keep what a lawyer typed, and can that be set to zero?

Disclosed fixed window

A specific retention period is published and the customer cannot change it.

The AI product description says drafting and review data will not be stored, while the general privacy policy retains platform records under a separate schedule. User deletion or contract termination removes user personal data, subject to limited name and email history; backups persist for five years. Customers can request removal of third party personal data from agreements. These provisions distinguish transient AI processing from saved contract content, but do not enumerate provider abuse monitoring exceptions or a separate schedule for agent conversation histories.

Source: Vendor PublishedA deleção não se aplica aos backups, que serão mantidos por 5 anos.As of Oct 16, 2026Evidence

Ethical Walls and Matter Segregation

Does retrieval respect the firm’s ethical walls, or can the model read across them?

Own model, documented

The product maintains its own permission model, documented, requiring the firm to keep it aligned.

netLex describes AI permissions tied to the current user's profile and says agents cannot access data beyond what that person can see. It also describes a separate customer environment, with role permissions and corporate authentication supporting access control. This is a product permission model for corporate contracts, rather than inheritance of a law firm's document management system permissions. The materials do not describe adverse party conflicts, lateral hire screening or an administratively tested ethical wall between separate legal client matters.

Source: Vendor Publishednão acessa dados além do que cada pessoa pode verAs of Oct 16, 2026Evidence

Third Party Request and Subpoena Notice

If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?

Disclosure addressed, notice absent

Published terms or policy address disclosure to authorities or in response to legal process, and no commitment or reservation regarding customer notice is located anywhere. The vendor has told the customer that data can leave and has said nothing about whether the customer hears of it.

The privacy policy permits disclosure in situations required by law or judicial decisions. It does not promise advance customer notification of a subpoena, an opportunity to contest the demand or a regular transparency report. A separate notification provision concerns a data subject asking netLex to delete information: the customer is notified so it can instruct the processor. That deletion procedure should not be read as notice of government access. The user terms also allow netLex to report suspected unlawful activity to authorities.

Source: Vendor PublishedEm casos específicos previstos em lei ou por força de decisões judiciais.As of Oct 16, 2026Evidence
Accuracy and Authority

Primary Law Corpus Provenance

Where does the law in this product come from, and does the vendor have the right to use it?

Not addressed

No located public material identifies the corpus behind the product’s answers.

The AI features work with customer contracts, attachments, clause playbooks and internal policies. They are not accompanied by an identified collection of licensed case law, statutes or commentary. OpenAI is named as a model provider, but the provider name does not establish the legal sources or licenses behind any generated proposition. Questions about company policy and departures from approved contract wording can have a useful internal reference base. They do not carry a published promise of comprehensive, current legal authority for a jurisdiction.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Good Law Verification

Does the product tell you when the authority it just cited has been overruled?

Not addressed

No located public material addresses whether authority is checked for subsequent history.

netLex's clause review compares agreements with customer standards and can suggest revised wording. No citator integration, case treatment service or automatic validation of whether a cited decision remains good law is described. Its requirement that users assess AI accuracy before adoption is a general review obligation, not a documented legal authority validation workflow. A team using generated legal opinions would still need an external research source to assess authority, subsequent treatment and relevance to the law governing the contract.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Refusal and Uncertainty Behavior

What does the product do when the answer is not in the corpus?

Not addressed

No located public material addresses what the product does when it cannot ground an answer.

Review Agent flags departures from a configured playbook and explains their severity, while Intake Agent is described as routing complex requests to appropriate people. Neither description specifies when a model declines to answer because support is missing, how uncertainty is communicated or what happens when contract clauses conflict with its assumptions. The terms warn that results can be inaccurate and require human assessment.

They do not supply an abstention policy, confidence calibration or examples of a refusal when legal context is insufficient.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Fabricated Citation Record

Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?

None located

No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.

The Charlotin collection contained 2,191 cases at this review, with no whole word match for netLex in either the tool field or the full case material. That result is limited to reported incidents included in the collection and does not measure the product's error rate. netLex primarily supports company agreements and internal legal requests, and its terms explicitly acknowledge that AI results may be inaccurate. A lack of a named reported incident does not make a generated legal citation reliable.

Source: Operator VerifiedAs of Oct 16, 2026Evidence
Professional Responsibility

Bar Guidance Alignment

Has the vendor engaged in public with the ethics opinions its buyers are bound by?

Not addressed

No located public material engages with bar or ethics guidance.

The terms require users to evaluate AI output and preserve necessary human legal analysis. netLex also discusses privacy, access permissions and final approval by a legal team. It does not map these arrangements to a named bar association opinion, professional conduct rule or jurisdiction specific guidance on legal AI. Compliance with the LGPD and GDPR concerns data protection and does not establish professional responsibility alignment.

Lawyers remain responsible for applying the conduct rules that govern their practice and the particular use of generated work.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Billing and Fee Posture

Does the vendor address what happens to the bill when the work takes an hour instead of six?

Outside the fee relationship

The product does not touch a fee between a lawyer and a client. It operates before an engagement exists, or it is bought by a team that bills no client for the work. Savings claims aimed at the buyer’s own cost are recorded in the summary and do not make the row a savings claim, because no client bill is in the loop.

netLex is sold for a company's own contracting and internal legal operations. The published savings concern productivity, amendment cycle time and business process costs, with subscription charges generally tied to users and their access profiles. Those claims do not describe lawyers charging external clients for time saved by AI. No legal fee allocation, client technology surcharge or invoice narrative is offered. Gupy's measured legal response time is an operational service level within a business, rather than a disclosure of billable legal time.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Outside Counsel Guideline Readiness

Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?

Subprocessors listed

A current subprocessor or model provider list is published.

A published supplier list identifies AWS, OpenAI, Microsoft, Google, Zendesk, signature services and other providers. The privacy policy explains AI input treatment, international transfers, deletion and the five year backup exception. Security reports can be requested under a nondisclosure agreement. These materials give a corporate team information to supply when a client asks about its technology, but do not constitute a named outside counsel approval workflow. The supplier list does not assign locations or detailed processing functions to every listed company.

Source: Vendor PublishedOpenAI (API e ChatGPT)As of Oct 16, 2026Evidence

Court Disclosure Support

If a judge’s standing order requires an AI disclosure, can the product produce one?

Partial record

Some elements of the record are available, short of a document level export.

netLex describes version history, approval tracking and AI interaction logs that distinguish automated actions from human decisions. Its privacy policy provides a REST API route for exporting stored agreements and data when a customer contract ends. The public description does not specify an export joining each prompt, model version, response and lawyer review into a court disclosure record. Contract negotiation history can support internal reconstruction of a drafting decision, but it is not a published filing certificate or a complete account of AI assistance for a court.

Source: Vendor Publishedtoda sugestão ou decisão da IA tem logAs of Oct 16, 2026Evidence
Contact

Correct a record, or ask how something was graded

Every grade and every signal on this index is drawn from public sources and dated. If a record is wrong, out of date, or missing an artifact the index did not locate, send the source and it will be reviewed and the record redated. Vendors are welcome to submit documentation. Nothing on this index is for sale, including a listing, a placement, or a grade.

AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 462 vendors across 9 categories, each graded on the same 15 capability axes and recorded against 12 legal signals, from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 16, 2026
The AI Legal Index is an editorial reference. It is not a regulatory body, not a law firm, and nothing published here is legal advice or a recommendation to retain or avoid a vendor. Records are verified against published sources, bar guidance and public court records. Where a record reads not addressed, the material was not located in public sources on the date shown. See the Methodology page for evaluation standards and limitations.
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