Everlaw vs iCONECT: how they compare in 2026
Everlaw and iCONECT reach the same review buyers from opposite ends of the deployment question. Everlaw is one cloud service for law firms, corporate legal teams and government, with FedRAMP Moderate and GovRAMP Moderate authorization for public sector work. Deep Dive answers questions across matters of more than 20 million documents and cites the source files, and Coding Suggestions gives each document a tiered call with a stated justification. Writing Assistant, StoryBuilder and machine translation in more than 100 languages carry the work from review into motions and trial preparation. Everlaw also connects to Claude, Harvey and Gemini, so outside AI tools answer from the evidence it holds. iCONECT goes where the buyer's data sits: local servers, a customer cloud account, a partner's data center or iCONECT's own Azure SaaS. It pairs continuous active learning with a check on human tagging, adds generative summaries and redaction, and handles breach notification in a separate product. Everlaw suits teams that want review through trial in one hosted workspace, and iCONECT suits teams that install the software themselves or run breach extraction beside discovery.
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 platform covers upload, processing, review, production and trial preparation, and was sold before the generative layer arrived in 2024. The models drive a core layer on top of it. Coding Suggestions automates first pass review, Deep Dive answers natural language questions across matters of more than 20 million documents, and Review Assistant and Writing Assistant summarize, extract and draft. Predictive Coding and Clustering apply machine learning that predates the generative features. Everlaw now presents itself as the evidence layer for legal AI, serving outside AI tools through its integrations, while the document review platform still runs without the generative layer.
Machine learning runs core review and breach response work on a document review platform that would still function without it. iCONECT's eDiscovery product is built around processing, an Elasticsearch index, deduplication, redaction and production. The models sit in several core capabilities: continuous active learning through Sentio technology; Oversight, which the vendor says is included in standard eDiscovery licensing and finds false negatives and false positives in reviewer tagging; AI email threading; and AI assisted identification and extraction of personal information in the cyber data mining product, where users can send documents to a model of their choice. Generative AI features listed on the eDiscovery and law firm pages add document summaries, classification by content or legal relevance, entity redaction, image description, transcription and translation. The vendor describes itself as a data intelligence AI platform, and in August 2026 announced an integration with eDiscovery AI that is still under development. Without the models, a full review and production system remains.
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.
Everlaw AI cites source documents in its results so users can verify output, and Deep Dive answers draw on facts extracted from specific documents, retrieved from a vector database of the customer's own documents. Everlaw says grounding curtails hallucinations without removing them. Coding Suggestions gives tiered recommendations with a justification for every document, and the AI product page says it can exceed human review performance. No accuracy rate, recall or precision figure, test set or evaluation method from Everlaw itself is published. The 98.2% recall figure comes from one customer's layered workflow combining keyword culling, Coding Suggestions and Predictive Coding.
The Oversight post of 17 May 2024 says the tool reaches a level of precision once thought unattainable and helps teams rectify discrepancies, with no recall, precision, elusion or validation figures and no test set. The cyber data mining page says each extracted data element is linked through audit trails to its original source file, creating a defensible chain of custody, which lets a reviewer trace a notification entry back to the document. How the generative features are grounded is not described: whether a document summary cites passages, how classification by legal relevance is validated, or how automatic privilege redaction is confirmed. No error rate or statement on invented content is 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.
Control is the first of Everlaw's generative AI principles, beside Confidence and Transparency, Privacy and Security. Users can opt in or out of Everlaw AI, and an icon marks every generative feature. Everlaw AI cites the source documents in its results so users can check their work, and each statement in a draft is followed by the document meant to support it, one click away. The customer terms require the customer to evaluate output for accuracy, including through human review, before relying on it. Coding Suggestions gives tiered coding recommendations with a justification for every document. In the Dinsmore & Shohl study, attorneys validated its output against a 120 document ground truth set. No threshold at which a document must go to a person, and no limit on what Coding Suggestions decides unaided, is published.
The Oversight post of 17 May 2024 says a subject matter expert, attorney or experienced reviewer seeds a model with as few as fifty documents, and that Oversight reports tagging errors for the team to correct. The cyber data mining page lets a team define its criteria so that verification, whether manual or automatic, fits its needs, and says GenAI reviews are used where appropriate. The eDiscovery page says redaction, including of an entire document because of privilege, can happen automatically, and that document classification sorts documents by legal relevance automatically, with no review step described for either. Nothing states what the generative features may not be used for, when a person must check their output, or what happens when a classification or redaction is wrong. For the generative features, review is a setting the customer chooses.
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.
Dinsmore & Shohl's study, published on 24 March 2026, describes a review of 26,000 contracts after a client's cyber incident. Partner Jennifer Mitchell and ediscovery director Peter Pepiton first culled about 20,000 drafts and duplicates. They then ran Coding Suggestions against attorney written criteria, validated it on a 120 document ground truth set, and finished with Predictive Coding. Recall rose from about 92% on the first Coding Suggestions pass to 98.2% after formal statistical validation. The home page adds stories from an unnamed Am Law 200 firm and an unnamed Fortune 500 company. Government agencies use Everlaw under its FedRAMP Moderate and GovRAMP authorizations.
Releases on iCONECT's site record that ProFile Discovery selected the platform for its law firm and corporate legal department environments (26 January 2021) and that Everest Discovery launched a cyber breach response service built on it (27 January 2025), with a quote from Everest's owner and president; other releases name Pictera Solutions, Right Discovery and Iota Analytics as customers. The Why iCONECT page names NASA and the FDIC among users. The law firm page presents seven large matters, among them the Vioxx, Yasmin and Pradaxa litigation, Oracle v. SAP and the Columbia investigation, without naming the firm, iCONECT's role or a result. No case study with a measured result is published on the site.
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 customer terms bar Everlaw from using inputs or outputs to train or fine tune a generative AI model for general use through the service, and inputs and outputs remain case materials the customer owns. The enterprise language models follow a zero data retention policy, using data only to generate a response and deleting it on completion. Data is not shared between customers, and the models hold no persistent knowledge of a customer's case that a data injection could extract. The vector database behind Deep Dive keeps numerical embeddings created from customer documents, which retrieval needs. Everlaw describes its environments as built for sensitive case data, privileged communications and personal information. No retention period is stated for the embeddings.
The only legal documents on the site are a terms of use (31 July 2024) and a privacy policy (June 2024), both written for the website. No customer agreement, data processing addendum or statement on training with customer documents is published. The eDiscovery and law firm pages cite SOC 2 certification, rigorous data protection and handling protocols and controlled access, and the SOC 2 Type 2 report on the SaaS platform covers the confidentiality criterion. The cyber data mining page lets users send documents to a model of their choice, including models from OpenAI, Microsoft and Google, and nothing published states what those providers may keep or use. The platform can be deployed on premises, which keeps documents in a firm's own environment, but nothing addresses privilege handling, segregation between matters, or what happens to documents sent to a model.
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.
The buyers are law firms, corporate legal departments and government legal teams, with no consumer product. The customer terms require the customer to review output for accuracy before relying on it and disclaim any warranty on AI output. Everlaw is a document review and case building platform rather than an advice tool, and it publishes nothing on advice versus tooling, on competence or supervision duties, or on jurisdiction limits.
The terms of use say information on iCONECT's pages is distributed on the understanding that the authors are not rendering legal, accounting or other professional advice. That sentence governs website content, not the review platform. The product classifies documents by legal relevance, redacts for privilege and summarizes documents for law firms, corporations, public sector organizations and service providers, and nothing published states that its output is not legal judgment, that a supervising lawyer must review it, or how it fits a lawyer's competence and supervision duties. No ethics opinion or court decision on technology assisted review is named.
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.
Everlaw publishes an AI Governance Framework built on three generative AI principles: Control, Confidence, and Transparency, Privacy and Security. Third party technologies are evaluated from technical, legal, privacy and security perspectives before adoption, and accuracy assessments inform which language models Everlaw uses. Users can opt in or out of Everlaw AI, and the framework sets out protections against data injection and exfiltration. On bias, the framework says Everlaw cannot manage bias inside third party foundation models and does not use prompt based mitigation, because that could mask bias in the case documents themselves. No accountable owner of AI governance is named and no testing results are published.
The platform page and a post of 10 May 2024 describe iCONECT's path as a responsible adoption of generative AI that enhances the platform without compromising data integrity or security. No person is named as accountable for model behavior, and no testing before release, evaluation results or principles are published. The SOC 2 Type 2 report covers information security controls and not the conduct of the models. Nothing addresses uneven output across languages and document types in classification by legal relevance or personal information identification. Users choosing between models from OpenAI, Microsoft and Google for personal information identification are not told how iCONECT evaluated them.
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.
Everlaw's language models follow a zero data retention policy, so data sent for processing is used only to generate a response and deleted on completion. Everlaw itself keeps customer data only as long as the customer stores it on the platform. A Pinecone vector database stores embeddings of customer documents to power Deep Dive. The data processing addendum commits to notice of a verified security incident without undue delay, with information as it becomes known and steps to contain and remediate. Subprocessors are listed with function and country, and additions or replacements are notified at least 10 days ahead. Termination instructs Everlaw to delete customer data within a commercially reasonable timeframe. Customers choose the AWS instance where data is stored and processed. No period is stated for deletion after termination or for keeping the embeddings behind Deep Dive.
The eDiscovery and law firm pages cite SOC 2 certification, regular security training and penetration testing, workstation and server security, data protection and handling protocols and controlled access, and the platform page cites encryption, access controls, regular security audits and adherence to GDPR and HIPAA standards. The SOC 2 Type 2 audit of the SaaS platform, completed on 22 September 2025 by A-LIGN, covers security, availability, processing integrity, confidentiality and privacy. The cyber data mining page says ingestion, extraction, review and modification actions are logged with audit trails. The privacy policy (June 2024) covers the website and not data processed in the platform. No retention period, deletion commitment, breach notice timing, subprocessor list or statement on what model providers keep when documents are sent to them is published.
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.
Everlaw's Customer Terms of Service, last updated 1 October 2025, carry an indemnity from Everlaw against third party claims that the service infringes intellectual property rights. Claims that Everlaw AI Assistant output infringes are excluded, along with customer negligence, breach, alteration and combination with other products. Each party's liability is capped at the fees paid or payable in the 12 months before the liability arises, and indirect and consequential damages are excluded. Everlaw's cap for an unpaid subscription is $100. Everlaw warrants only compliance with applicable law. It makes no warranty on the accuracy, completeness or reliability of AI output, and the customer must review output before relying on it. The terms state that Everlaw is not an insurance company and point the customer to its own insurance for losses outside Everlaw's express obligations.
No customer agreement, license terms or SaaS terms are published. The terms of use (31 July 2024, California law) disclaim liability for direct, indirect, special, incidental or consequential damages arising from the website and its content; they do not govern the software. No indemnity, warranty, cap or allocation of risk is published for missed documents, wrong classifications, failed redactions or errors in personal data extraction, on a product used to decide what is produced to an opposing party and who is notified after a breach.
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.
Everlaw connects to the AI tools legal teams already use, naming Claude, ChatGPT Enterprise, Google Gemini, Microsoft Copilot, Harvey, Legora and Thomson Reuters as integration partners, each described in a line. Claude can retrieve and analyze case materials directly, and ChatGPT Enterprise uses Everlaw as an evidence layer. API and MCP connectors let firms and partners build custom tools on Everlaw as the evidentiary system of record. Cloud connectors collect data straight from Microsoft 365, Zoom and Google Workspace. No public page sets out which objects each integration moves, in which direction, or what a firm must configure.
iCONECT's release of 10 June 2021 says its Ligl integration, available then, lets organizations identify, hold, preserve and collect enterprise documents in Ligl, process and cull them, and push relevant documents to iCONECT for review. The cyber data mining page lets users send selected documents to a model of their choice, including models from OpenAI, Microsoft and Google. The partners page shows Microsoft, Nuix, LexisNexis, Sentio, Opus 2 and Heureka Software as technology partners, as logos without descriptions, alongside more than 25 hosting partners. An integration with eDiscovery AI was announced on 24 August 2026 as under development, with availability to follow. The platform page says iCONECT integrates with the most common applications in its three markets, without naming them. Nothing describes connections to a firm's document management, matter management or litigation support systems, and no integration documentation is public.
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.
Everlaw runs on Amazon Web Services, and customers choose the instance where data is stored and processed: United States, United Kingdom, EU in Germany, Canada or Australia. AI processing follows the instance. Google and OpenAI process in the EU for UK and EU customers, and OpenAI processes in Canada for the Canadian instance, under the same zero retention and no training terms. Government agencies run on Everlaw's FedRAMP Moderate and GovRAMP authorized environments. The transparency report says Everlaw is subject to United States law and that data may also be subject to the laws of the chosen instance's country. No tenancy model is described.
The eDiscovery page offers on premises, hybrid, cloud and SaaS deployment. The post of 19 July 2024 on system architecture describes in house deployment, cloud deployment on Microsoft Azure, Google Cloud, AWS or other providers, and hosting through iCONECT's network of legal service providers. The release of 23 August 2023 launching iCONECT SaaS says it runs on Microsoft Azure. A firm can therefore keep the platform and its documents on its own infrastructure. Not stated are where iCONECT's SaaS stores or processes data, which regions are available, and whether SaaS customers are separated at the tenant level. Nor is it stated where documents go when they are sent to a model from OpenAI, Microsoft or Google for personal information identification, or whether the generative features work in an on premises deployment.
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.
Everlaw holds FedRAMP Moderate and GovRAMP Moderate authorizations, SOC 2 Type 2 and SOC 3 reports, ISO 27001:2022, ISO 27017 and ISO 27018 certification, Cyber Essentials Plus, and CCPA and GDPR compliance. Its security and compliance portal at trust.everlaw.com lists the SOC 2 Type II report with a 2026 bridge letter and a penetration test executive summary. It also lists a HIPAA HITECH assessment, a CAIQ dated May 2026, a SIG Lite and the ISO statement of applicability. Reports open through an access request on the portal. The portal also carries an architecture diagram, the AI governance framework and a 2026 disaster recovery test summary.
iCONECT's release of 29 September 2025 says A-LIGN completed a SOC 2 Type 2 audit of its SaaS platform on 22 September 2025 covering security, availability, processing integrity, confidentiality and privacy, and the home page carries an A-LIGN badge. No audit period is stated, no trust center is published, and the report is offered neither for download nor on request. The eDiscovery and law firm pages add regular penetration testing and security training, and the platform page claims adherence to GDPR and HIPAA standards without any certification behind them.
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.
Everlaw's subprocessor list, updated 2 October 2026, names Amazon Web Services and Google as cloud and AI service providers, OpenAI as an AI service provider and Pinecone for the vector database behind Deep Dive. It gives countries of processing by instance, with Google and OpenAI processing in the EU for UK and EU customers and OpenAI in Canada for the Canadian instance. The integrations page says Google Gemini powers retrieval and context engineering. The data processing addendum commits to notice at least 10 days before a subprocessor is added or replaced, with 15 days to object. The AI governance framework says the language models follow zero data retention terms and that accuracy assessments inform which models Everlaw uses. No model or version is named for any feature.
The cyber data mining page lets users send selected documents for personal information identification to a model of their choice, including models from OpenAI, Microsoft and Google. The platform page says iCONECT integrated Sentio technology, which carries its continuous active learning, and acquired AI source code from Ayfie in 2021. Nothing published names the model behind document summaries, classification, image description, transcription or translation, states whether iCONECT or the customer holds the model provider relationship, says where those models run, or commits to notice when a 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.
Everlaw's pricing page lists what the platform includes rather than what it costs. Cloud connectors, processing at one million documents an hour, transcription, redactions, productions, Predictive Coding, Clustering, timelines, transcript analysis, onboarding, training, standard data migration and unlimited user licenses are included. Coding Suggestions, Deep Dive, machine translation and custom extractions run on credits, with single document use free of credits. An intake portal with case management and compliance reporting is an add on. No figure, tier or unit of charge for the platform is published, and pricing runs through a demo request.
The law firm page offers flexible pricing with monthly or annual terms, the Why iCONECT page describes predictable pricing through monthly and yearly plans, and the release of 23 August 2023 launching iCONECT SaaS describes Price Protect, which applies discounts automatically as data volume grows without renegotiating the contract. That points to data volume as a driver and term length as a choice, without stating the unit, the rate or what the generative features add. No price, rate per gigabyte, user fee or tier is published, and every route to a number runs through a demo request.
Firm and Practice Coverage
Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.
Everlaw sells to law firms, corporate legal departments and government agencies at federal, state and local level. Public sector use cases include litigation, investigations and Freedom of Information Act requests. Private sector use cases include document review, early case assessment, legal holds, internal investigations, data privacy, depositions and trial preparation. Its practice scope is ediscovery, investigation and litigation from data upload through production to trial, with no claim to transactional or advisory work. Regional instances run in the United States, United Kingdom, Germany, Canada and Australia. Segmentation by firm size, industry breakouts and any statement of what the platform is not built for are not published.
The site addresses law firms, corporations, public sector organizations and service providers, each with its own page, across three products: eDiscovery, cyber data mining for breach response, and data governance. The law firm page covers litigation, investigations and responsive actions, the cyber data mining page covers breach notification work for incident response professionals, and the release of 24 August 2026 names law firms, corporations, legal service providers and public sector organizations as customers. Named users include NASA and the FDIC. What is not stated is which languages the generative features and personal information identification support, which privacy regimes the breach tools are built around beyond references to GDPR and HIPAA, and which deployment options carry the generative features.
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?
Under its Customer Terms of Service, Everlaw will not use inputs or outputs to train or fine tune a generative AI model for general use through the service. Inputs and outputs are case materials the customer owns. The AI governance framework says the enterprise language models follow zero data retention terms, deleting data on completion and never using it to train their models. Predictive Coding learns from the coding decisions within a customer's own matter.
No customer agreement, license terms or data processing addendum is published, and no page states a position on training with customer documents. The terms of use (31 July 2024) and the privacy policy (June 2024) cover the website only. Oversight's matter model is seeded by the customer's own reviewers with its own documents, which is not vendor training, and the cyber data mining page lets users send documents to models from OpenAI, Microsoft or Google with nothing published on whether those providers may train on them.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Data sent to the language models is deleted on completion and not kept after the request. Everlaw keeps customer data only as long as the customer stores it on the platform, and does not retain deleted data unless the law requires it. The Pinecone vector database behind Deep Dive stores numerical embeddings created from customer documents, which retrieval needs. Termination instructs Everlaw to delete customer data within a commercially reasonable timeframe, and no period is stated for the embeddings or for deletion after termination.
Nothing published states how long documents, extracted data, summaries or other AI outputs are kept, or when they are deleted, in the SaaS platform or by a model provider. The privacy policy covers website data only.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Everlaw says data submitted and responses received are not shared between customers, and the models hold no persistent knowledge across requests. Nothing published sets out how separation is enforced between users, teams or matters inside one customer, where walls operate. A firm running two adverse matters on the platform has no published description of whether Deep Dive retrieval can cross between them.
Nothing describes walls between matters or teams, or how the generative features and continuous active learning are kept within a matter. The eDiscovery and law firm pages cite controlled access and the SaaS launch release mentions user setup and matter management, without describing how access is segregated.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Everlaw's data processing addendum says that if it must respond to a request for customer data, it will promptly notify the customer and provide a copy of the request unless legally prohibited. Its government request transparency report adds that Everlaw reviews each request, may seek to narrow or object to it, and emails the customer before disclosing. Notice is withheld only where the law prohibits it, after an account takeover or in an emergency, and is given once a prohibition lifts. United States authorities must use a subpoena, court order, warrant or national security request.
No published agreement addresses legal demands for customer data held in the platform. The privacy policy (June 2024), which covers the website, says iCONECT may disclose a website user's name, city, state, telephone number and email address to law enforcement on a verified request without a subpoena; it does not reach documents processed in the platform.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No primary law corpus sits behind Everlaw. Retrieval runs against the customer's own case documents, uploaded into the platform and indexed as embeddings in a vector database, so the source material is the evidence in the matter. No vendor supplied legal collection, license basis or update cadence applies.
iCONECT works on a customer's own documents and data and does not describe retrieval of case law or other legal sources; no outside body of legal sources applies.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Everlaw's corpus is the evidence in a matter rather than published case law, so its output cites documents, not authority. Writing Assistant drafts arguments from the evidence, and any legal authority in that writing comes from elsewhere. No treatment signal or check of subsequent history is described.
The product does not cite legal authority, so no check of subsequent history applies, and none is described.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Everlaw does not describe what the product does when the documents do not support an answer, and shows no confidence signal for an answer. It says grounding curtails hallucinations, and answers cite source documents so a user can check them. Deep Dive answers questions across matters of more than 20 million documents, and its behavior when the evidence is absent is not described.
Nothing published describes what the summaries, classification or personal information identification do when a document gives them no basis for an answer, or how low confidence is shown.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
Damien Charlotin's AI Hallucination Cases database, which tracks court decisions worldwide on hallucinated AI content, has no entry naming Everlaw. Everlaw generates answers and drafts from a matter's own evidence rather than from case law.
The AI Hallucination Cases database maintained by Damien Charlotin, which records court decisions worldwide that address hallucinated AI content and the tool involved where known, has no entry naming iCONECT. iCONECT reviews, classifies and redacts a customer's own documents for eDiscovery and breach response rather than drafting filings.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Everlaw names no ethics opinion or bar guidance, including ABA Formal Opinion 512. Its AI governance framework and generative AI principles govern its own conduct rather than the professional duties of the lawyers who use it. It also does not connect its AI features to the Federal Rules of Civil Procedure or to case law on technology assisted review.
The terms of use (31 July 2024) state that information on iCONECT's pages is distributed on the understanding that the authors are not rendering legal, accounting or other professional advice. The clause governs website content, not the review platform. No ethics opinion, bar guidance or court decision on technology assisted review is named on the product pages or in iCONECT's posts.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Everlaw's savings claims are about throughput: Coding Suggestions automates first pass review with results it says can exceed human review, and Deep Dive answers questions across very large matters in seconds. Everlaw sells to law firms, where that review time is billed to clients. Nothing published addresses how AI assisted review is recorded or billed, or whether clients are told.
iCONECT's pages claim savings without addressing billing. The eDiscovery page says AI email threading and deduplication reduce the dataset and that AI automations eliminate repetitive steps, the Why iCONECT page displays a counter for ROI savings delivered, and a customer release quotes Everest Discovery on reducing costs. The platform is sold to law firms and to service providers whose review charges reach clients, and nothing published addresses how AI assisted review is billed or disclosed.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A subprocessor list, updated 2 October 2026, names AWS, Google, OpenAI, Pinecone, Zendesk and Datadog with function and country. Everlaw's customer terms, data processing addendum and government request transparency report sit beside it. The trust portal carries SOC 2 and SOC 3 reports, a penetration test summary, a CAIQ and a SIG Lite behind an access request. Security, endpoint detection and response tools are left off the public list and are available by email.
No subprocessor list or disclosure material for a client's AI terms is published. The cyber data mining page names OpenAI, Microsoft and Google as model choices for one feature, which is not a list of the providers that process customer data, and the SOC 2 report is not offered for download or on request.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Each Everlaw AI result cites the source documents behind it, and an ediscovery platform keeps review and production histories at document level, so what an answer relied on can be traced. No export per document records the model used, the sources retrieved and the human check together, and no model is named for any feature. Courts have long engaged with technology assisted review in ediscovery, and Everlaw does not connect its AI disclosure material to that case law.
The cyber data mining page says ingestion, extraction, review and modification actions are logged with audit trails that link each extracted data element to its source file, creating a defensible chain of custody for regulatory inquiries and legal review. Oversight produces reports of tagging errors, and the law firm page lists reviewer productivity reporting. Nothing records which model produced a summary or classification, and no export for disclosing AI use or validating continuous active learning to a court is described.
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.
- Primary Law Corpus Provenance
- Good Law Verification
- Refusal and Uncertainty Behavior
Which one fits
Choose Everlaw if
- Your matters run to tens of millions of documents. Deep Dive answers plain language questions across more than 20 million documents and cites the files behind each answer.
- You work in a government office. Everlaw holds FedRAMP Moderate and GovRAMP Moderate authorization and sells dedicated offerings to federal, state and local agencies.
- Review should feed straight into motions and trial. StoryBuilder and Writing Assistant turn coded evidence into timelines and drafts tied to the record of the matter.
Choose iCONECT if
- Your security policy rules out a vendor cloud. iCONECT can be installed on your own hardware or in a hybrid arrangement, so documents stay on servers you run.
- Breach response belongs to the same team as discovery. iCONECT's breach product finds personal information in breached data and lets you pick the OpenAI, Microsoft or Google model that reads it.
- You want reviewers checked while they work. Oversight, included in standard eDiscovery licensing, points out documents a model believes were coded wrongly.
In summary
Everlaw
Everlaw, based in Oakland, California, sells a cloud native platform for eDiscovery, investigations, legal holds, depositions and trial preparation. EverlawAI includes Deep Dive for natural language questions with source citations, Coding Suggestions for first pass review, Review Assistant, Writing Assistant, predictive coding and clustering. According to the AI Legal Index, Everlaw holds SOC 2 Type 2 certification and FedRAMP and GovRAMP Moderate authorization. It serves law firms, corporations and federal, state and local government.
iCONECT
iCONECT is a platform for document review, breach data mining and data governance, built by iCONECT Development, LLC since 1999. Buyers can license it for their own servers or cloud, use a hosting partner, or subscribe to SaaS on Microsoft Azure. Review uses continuous active learning and Oversight, a check for tagging errors. Generative features cover summaries, document and image classification, entity redaction, transcription and translation. According to the AI Legal Index, iCONECT sells monthly or annual terms and publishes no rates.
Questions buyers ask
Can Everlaw run on a firm's own servers the way iCONECT can?
Everlaw is delivered as a cloud service, authorized at FedRAMP Moderate for federal work. iCONECT can be installed on local servers, in a hybrid setup, in a customer's own cloud account or bought as SaaS. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
How do Everlaw and iCONECT explain AI coding decisions?
Everlaw's Coding Suggestions gives each document a tiered recommendation with a justification. iCONECT's continuous active learning ranks documents by likely relevance, and Oversight reports tags it believes a reviewer got wrong. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
Do Everlaw and iCONECT translate foreign language documents?
Everlaw offers machine translation in more than 100 languages, and translating a single document uses no credits. iCONECT lists translation among its generative features without naming the languages covered. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
Which one connects to outside AI assistants?
Everlaw connects to Claude, Harvey and Gemini so answers from those tools draw on the evidence held in Everlaw. iCONECT lets a breach team send selected documents to a model from OpenAI, Microsoft or Google. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
What do Everlaw and iCONECT publish on price?
Everlaw lists its plans and the features in each, with AI usage measured in credits, and shows no rates. iCONECT offers monthly or annual terms and publishes no figures. From the AI Legal Index, based on each vendor's own published materials as of October 13, 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.
Everlaw is headquartered in Oakland, California. iCONECT is made by iCONECT Development, LLC. Neither vendor reviewed this page.