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Neota Logic
Neota Logic is a legal automation platform that needs no code, from Neota Logic Inc. of New York, with group companies in London and Melbourne. It now positions itself as a governance layer for AI in corporate legal departments and law firms. Legal, compliance and risk teams build their own applications for intake and triage, contract generation, regulatory assessments, approvals and advice tools for clients. They build from process maps, decision trees and document templates, and connect to systems such as iManage, NetDocuments, SharePoint, Salesforce, DocuSign and Microsoft 365.
Its AI Task Node calls a model the customer has approved, through the customer's own Amazon Bedrock, Azure or other provider account. The model extracts, classifies, summarizes or drafts inside an otherwise deterministic workflow. Confidence is captured as a variable that can route work to human review, and every call is logged with the prompt, response, model, token count and approver. An MCP connection, in preview, lets AI assistants such as Claude call Neota applications for answers based on rules.
Neota states ISO 27001 certification, hosting on AWS or Azure in a region the customer chooses, and pricing per solution rather than per user.
Neota Logic, head to head
Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.
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Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.
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.
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 a core capability of a platform that would still work without them. The AI Task Node calls a model the customer has approved to extract clauses, classify requests, summarize and draft inside an otherwise deterministic workflow. Neota names contract review, matter triage and document summarization as its AI uses, and an MCP connection in preview lets AI assistants call Neota applications. Underneath is the platform for process, decision and document automation without code that the company has sold since 2010, which runs without any model.
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.
Grounding is documented, with each AI step traced to its source and checked by rules, but no accuracy figures are published. The AI Solutions page shows an extraction step that captures the clause and citation it relied on and attaches a confidence score. It validates the output against the customer's deterministic rules and escalates to a person when a check fails. It also describes the failure the design guards against: a fluent, confidently wrong answer from an ungoverned model. No accuracy figures, test results or failure rates for the AI Task Node itself are published.
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.
What the AI runs alone, what constrains it and how a person checks it are all published. The AI Solutions page describes the AI Task Node's modes (extract, classify, draft), each scored for confidence and logged. A decision gateway branches on AI confidence against a threshold the customer sets. Human review nodes must approve before the process continues or output reaches a client, and a drafted output is always checked downstream.
Neota's FAQ says the customer decides where review points sit and what happens when a check fails: routing to a named person, holding the matter or asking the requester for more. The August 2026 release says no model is ever invoked by default.
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 deployments have substance but no measured result. Six case studies cover Harneys, Fujitsu, Thommessen, Simonsen Vogt Wiig, Grampians Health and an unnamed firm's FCPA subscription service. Harneys built an application for launching funds, after which the firm introduced fixed fees and reports a higher pitch win rate. Fujitsu handles NDAs, DPAs and other agreements on a self service basis, Thommessen runs matter onboarding integrated with Salesforce, and Simonsen Vogt Wiig built a public guidance tool that won an award.
Grampians Health handles freedom of information requests, with letter readability improved from grade 8 to 12 to grade 3 to 4. None gives a before and after figure with a method, and the readability change reflects the customer's own rewriting. The home page claims more than $100 million of verified value with no basis. None of the case studies concerns the AI features.
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 confidentiality position is structural and published, but no customer contract is published and privilege is not addressed. Neota's FAQ says customer data is not used to train models because the customer connects its own model under its own provider agreement inside its own AWS Bedrock or Azure boundary, so existing provider protections stay in place. Application data is encrypted at all times and deleted when a session ends unless the site owner directs otherwise.
Access to applications is set by the customer down to who can see a matter. No customer agreement is published, and privilege and work product are not addressed.
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.
Neota states a real position on what the tool is, without guidance for the advice tools customers build for their clients. The Terms of Use tell users to have a qualified person review outputs before relying on them. Neota's FAQ says the model does the language work while the customer's rules decide the outcome, with the expert knowledge coming from the legal team rather than from Neota. Customers use the platform to publish advice applications to their own clients and to the public, such as Simonsen Vogt Wiig's free guidance tool. Nothing addresses disclosure, supervision or jurisdiction for those applications.
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.
There is a governance framework with real mechanisms, and it sits on the customer side. Models are approved centrally by the customer's administrators, and no model runs by default. Every call is logged with prompt, response, model, cost and approver, and outputs are validated against the customer's rules, with human approval where the customer sets it. Neota sells this governance as its product, and the same controls apply to Neota's own AI Task Node. Nothing is published on how Neota tests the node before release, who is accountable internally, or uneven performance.
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.
Most of the ground is covered, except a subprocessor list and an incident commitment. The Security page states AES-256 encryption in transit and at rest, role based access with single sign on, regular third party penetration testing and hosting on AWS or Microsoft Azure. The Privacy Policy says application data is encrypted, deleted at the end of a session unless the site owner directs retention, and stored in the country or region the site owner chooses.
AI calls run through the customer's own model account. No subprocessor list or incident notification timeline is published, and a security pack is available on request.
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 addressed only through a standard limitation. The Terms of Use (1 June 2026) provide the services as is, tell users to have a qualified person review outputs before relying on them, and exclude indirect and consequential damages. They limit aggregate liability as set out in the customer's agreement, which is not published. No indemnity or position on incorrect AI output is published.
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.
Connections into legal systems are named with what they do, but there is no documentation for implementers. The Integrations page and FAQ list prebuilt connectors for iManage, NetDocuments, SharePoint and Box (store, retrieve and file documents), Microsoft 365 and a Word Toolbar, and DocuSign and Adobe Sign (route for signature). They also list Salesforce, Dynamics 365 and HubSpot (push and pull data), Slack, Teams, Gmail and Outlook, PostgreSQL, MS SQL, Power BI and Tableau.
Inbound and outbound REST APIs are offered with a sample call, and an MCP server is in preview. What syncs in which direction and what a customer must configure are not documented publicly, and training runs through Neota University.
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.
Deployment options, residency choice and the location of AI processing are stated, but not the regions available or what changes between options. The Security page offers hosting on AWS or Microsoft Azure, and the Pricing page offers cloud, on premises and private cloud. Neota's FAQ says the deployment region is chosen to fit the customer's residency requirements, and the Privacy Policy says site data is stored in the country or region the owner directs. AI runs inside the customer's own Bedrock or Azure boundary. No list of regions is published.
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 certification is named without scope, date or a published route to the certificate. The Security page states ISO 27001 certification and regular third party penetration testing, and offers a security pack through the contact form. No certificate number, scope, certification body, date or trust center is published.
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 model providers are named, where they run is stated, and no model changes without the customer's approval. The Integrations and home pages name OpenAI, Anthropic Claude, Google Gemini, Azure AI Foundry, Amazon Bedrock and models the customer hosts itself. Neota's FAQ says deployment sits inside the customer's own AWS Bedrock or Azure boundary under the customer's own provider agreements, and the audit record names the model on every call.
The August 2026 release says models are approved centrally by the customer and none is invoked by default, so the customer controls any change rather than relying on notice from Neota.
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 are published without the figure. Neota's pricing page says it is priced per solution or use case rather than per user, on a tiered subscription in which the cost per solution falls as more are built. Professional services are sold at a fixed fee. Deployment options include cloud, on premises and private cloud, and a Discovery Sprint with a recoverable upfront investment is the way to start. The FAQ adds that price reflects solutions in scope, users and environments. No rate is published.
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.
Segments and uses are described with substance, but limits are not stated. Neota serves corporate legal departments, law firms (including services for their clients), and enterprise compliance, risk, procurement, HR, insurance and government teams. Case studies cover offshore funds, commercial contracting, matter onboarding and AML, freedom of information in the public sector and FCPA compliance. Customers are in North America, Europe and Asia Pacific. Nothing says what the platform does not support or where the AI tasks are unsuitable.
6 public documents
The public pages on file for Neota Logic, 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.
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neotalogic.com/ai-solutions3 signals
Refusal and Uncertainty Behavior, Billing and Fee Posture, Court Disclosure Support
Read Sep 18, 2026
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neotalogic.com/faq2 signals
Client Data in Training, Ethical Walls and Matter Segregation
Read Sep 18, 2026
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neotalogic.com/privacy2 signals
Prompt and Output Retention, Third Party Request and Subpoena Notice
Read Sep 18, 2026
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Fabricated Citation Record
Read Sep 18, 2026
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neotalogic.com1 signal
Bar Guidance Alignment
Read Sep 18, 2026
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neotalogic.com/security1 signal
Outside Counsel Guideline Readiness
Read Sep 18, 2026
Quoted per solution
- Neota charges for each solution you build, not for each person who uses it.
- The more solutions you build, the less each one costs.
- Setup and building help is sold as professional services at a fixed fee.
- You start with a paid Discovery Sprint that builds a first working version.
- No prices are published, so you have to ask for a quote.
Per solution or use case, not per user, on a tiered subscription whose cost per solution falls as more are built; Neota's FAQ says price reflects solutions in scope, users and environments. Deployment options include cloud, on premises and private cloud. Sources: https://www.neotalogic.com/pricing and https://www.neotalogic.com/faq.
Implementation: Professional services at a fixed fee. A Discovery Sprint to scope and build a first working solution carries an upfront investment described as recoverable. No figures published.
Legal Signals
What each signal meansA 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.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
A public policy or trust page states no training on customer content, with no matching term located in the published agreement.
A public FAQ says customer data is not used to train models, with no matching term in a published agreement. The reason given is structural: Neota does not send customer data to a Neota model; customers connect their own model under their own provider agreement, inside their own AWS Bedrock or Azure boundary. No customer agreement is published, and the Terms of Use do not address training.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The customer controls the retention window, by product configuration or by contractual instruction, but zero retention is not stated as available.
The customer controls retention. The Privacy Policy says application data is encrypted, and when a session ends it is either deleted automatically or kept for a period the site owner directs. Zero retention is not stated as available for AI activity, because the audit trail logs every prompt and response, and how long that log is kept is not stated.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
The product maintains its own permission model, documented, requiring the firm to keep it aligned.
The product keeps its own permission model, described at two levels. Building access is managed in Workbench with role based permissions and optional single sign on. Access to each application is defined by the customer down to who can start a workflow, see a matter or approve. It does not inherit permissions from the document system.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
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 says Neota may disclose personal information in response to a subpoena, court order or other governmental request, with no commitment or reservation on notifying the customer. No customer agreement 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?
No located public material identifies the corpus behind the product’s answers.
The applications run on the customer's own rules, documents and data with the customer's chosen model; no outside legal corpus is described.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
No check of cited authority for subsequent history is described.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The vendor describes refusal or abstention behavior in public materials.
Neota describes what happens when the AI is uncertain. Each AI task captures a confidence score as a workflow variable, and a decision gateway can branch on it against a threshold the customer sets. Low confidence results or failed checks can be routed to a named person, held, or returned to the requester for more information. The path is configured for each application rather than fixed.
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 addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
The AI Hallucination Cases database maintained by Damien Charlotin, and trade press reporting, record no court finding on fabricated or hallucinated content in output from Neota Logic.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Public materials refer to professional responsibility in general terms without naming guidance.
Professional responsibility is referred to in general terms. Neota's home page says human oversight ensures decisions meet legal and professional standards, and its FAQ lists regulators, clients, courts and insurers as parties who may ask for the audit trail. No ethics opinion, court AI order or rule, or judicial or bar guidance is named, including ABA Formal Opinion 512.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
A usable record of AI assisted work exists with no published fee guidance.
A usable record of work done with AI exists, with no published fee guidance. Law firms are among the buyers and build services for their clients on the platform. The audit trail records each AI call by session and matter with its token count and cost. Nothing addresses how firms should bill or disclose work done with AI. The Harneys case study describes that firm moving to fixed fees on its own account.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The material exists behind a sales conversation or an executed agreement.
Disclosure material exists behind a request. The Security page offers a security pack through the contact form, and no subprocessor list is published. The model providers are named on the Integrations page, but they run under each customer's own account, so a firm would disclose its own provider rather than one chosen by Neota.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
The product exports a per document record covering model used, sources retrieved and human verification.
An exportable record for each session covers the AI's part in the work. The AI Solutions page shows each AI call recorded against its session and matter with the prompt version, the clause and citation captured, the model used, tokens, confidence and the approving person. The record is hashed as immutable, and the page says the whole trail is exportable.